{"as_of":"2026-08-09T22:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2d12cdd7679a3f5127409c516816ce25f0c2083b556a4309aa775acf1b100627","coverage":[{"denominator":90,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":90,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:36:15.819379Z","state":"measured"},{"denominator":91,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":91,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-06-26T17:46:00.822375Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T03:39:30.608876Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"cited_work":{"arxiv_id":"2506.07575","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.07575","snapshot_observed_at":"2026-07-04T03:39:30.608876Z","title":"Uncertainty- o: One model-agnostic framework for unveiling uncertainty in large multimodal models.arXiv preprint arXiv:2506.07575, 2025","venue":null,"work_id":"0290cb83-fe4b-49e4-81fb-300a36f97fd5","year":2025},"citing_paper":{"arxiv_id":"2606.19868","last_updated":"2026-06-18T07:27:34Z","snapshot_observed_at":"2026-08-09T02:21:37.900133Z","submitted_at":"2026-06-18T07:27:34Z","title":"A Systematic Evaluation of Black-Box Uncertainty Estimation Methods for Large Language Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-06-26T17:46:00.822375Z"},"links":{"cited_paper":"/paper/2506.07575","citing_paper":"/paper/2606.19868"},"observation_digest":"sha256:b656a999ac788d37c5291df3205175f83b113ccf9c10bab86eab16770731b709","observation_id":"3e5cf70d-aa8e-41f0-8b38-dbe3e1ebd562","resolution":{"observed_at":"2026-07-04T03:39:30.610855Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.07575/citation-record","integrity":"/paper/2506.07575/integrity","json":"/paper/2506.07575/citation-record.json","paper":"/paper/2506.07575"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-07T05:36:15.429855Z","title":"Gpt-4 technical report","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.429855Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:9cdb6b069912162cf684eda00a287c74d4a2ae1c28b4e0e4b224dba44070d5fe","observation_id":"70721b71-9a16-4c3f-991a-9fbf08de0d47","resolution":{"observed_at":"2026-08-07T05:36:15.429855Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.435545Z","title":"How many opinions does your llm have? improving uncertainty estimation in nlg","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.435545Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:60c9feb41749e63fa5f6ca6e095ad70dd233390ff433f4517cf1380841a56cb7","observation_id":"dd960f05-75e3-4b49-a081-7afd2d699de5","resolution":{"observed_at":"2026-08-07T05:36:15.435545Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.13507","last_updated":"2023-10-25T18:43:02Z","snapshot_observed_at":"2026-08-09T01:06:06.990078Z","submitted_at":"2023-05-22T21:52:24Z","title":"Multimodal Automated Fact-Checking: A Survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.13507","snapshot_observed_at":"2026-08-07T05:36:15.440448Z","title":"Multimodal automated fact-checking: A survey","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.440448Z"},"links":{"cited_paper":"/paper/2305.13507","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:7acd8d1bc3e100978115b554ea706c257efa7f7a911fc229c5cd3b4d52479309","observation_id":"9ab4718f-62d3-46dd-b731-b3e6c9d34225","resolution":{"observed_at":"2026-08-07T05:36:15.440448Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.13712","last_updated":"2024-07-02T01:39:50Z","snapshot_observed_at":"2026-07-06T15:31:09.320113Z","submitted_at":"2023-05-23T05:59:21Z","title":"Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.13712","snapshot_observed_at":"2026-08-07T05:36:15.445213Z","title":"Knowledge of knowledge: Ex- ploring known-unknowns uncertainty with large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.445213Z"},"links":{"cited_paper":"/paper/2305.13712","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:5ff11669272d1dfe603753e0c8810ffb4fafd871a7cd285b1143e957eae08a39","observation_id":"e39b9aa9-92d2-4f03-9716-e2b4b419173d","resolution":{"observed_at":"2026-08-07T05:36:15.445213Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.450516Z","title":"Predicting and understanding human action decisions during skillful joint-action using supervised machine learning and explainable-ai","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.450516Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:6769f6d7711747e4c093e6e202a83038975ef243b47cb0de39df5af9615e4d0b","observation_id":"a6bc3eba-a7d4-4d35-9603-09149144f8b9","resolution":{"observed_at":"2026-08-07T05:36:15.450516Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.455158Z","title":"Qwen-vl: A versatile vision-language model for un- derstanding, localization, text reading, and beyond, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.455158Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:68496c7a3458770adc2ea8af0624346f7e82eb501ae529e4242c81a963f0efa8","observation_id":"5b218547-f80c-47a5-a32e-b5b5f7b2d477","resolution":{"observed_at":"2026-08-07T05:36:15.455158Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.18930","last_updated":"2025-04-01T18:36:08Z","snapshot_observed_at":"2026-08-06T19:08:14.800394Z","submitted_at":"2024-04-29T17:59:41Z","title":"Hallucination of Multimodal Large Language Models: A Survey","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.18930","snapshot_observed_at":"2026-08-07T05:36:15.461202Z","title":"Halluci- nation of multimodal large language models: A survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.461202Z"},"links":{"cited_paper":"/paper/2404.18930","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:7e87a9e5b2d0d84e6b7814d400fa9f13a7b2efbbf65f0494bbe509b742dc544b","observation_id":"c5614c95-8b66-486c-9645-aac77201f808","resolution":{"observed_at":"2026-08-07T05:36:15.461202Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.466099Z","title":"Lan- guage models are few-shot learners","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.466099Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:5eb8ca05c3cfc14d4420d2f43bbf81f48bf68f1407457eaa062bbec8031c7a81","observation_id":"5db89a14-a179-4fcf-82e6-514f3fea699e","resolution":{"observed_at":"2026-08-07T05:36:15.466099Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.471048Z","title":"The revolution of multimodal large language models: a survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.471048Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:cc30a0b8a6d09537e37017e7b886c74dbec6019783c59c15e82494c27e48f8ca","observation_id":"7793d10b-c01a-4ba6-b99c-5e5d07611216","resolution":{"observed_at":"2026-08-07T05:36:15.471048Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.475421Z","title":"Rational use of cognitive resources in human planning","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.475421Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:7528a6e87605555932783b76e1cfa0b99b45ad8fd2b7c73eb40ab91f90ebbd23","observation_id":"dcc92c32-0aee-4b3b-a192-185d53e1dbd8","resolution":{"observed_at":"2026-08-07T05:36:15.475421Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.01322","last_updated":"2024-03-28T15:53:45Z","snapshot_observed_at":"2026-07-06T17:54:07.815827Z","submitted_at":"2024-03-28T15:53:45Z","title":"A Review of Multi-Modal Large Language and Vision Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.01322","snapshot_observed_at":"2026-08-07T05:36:15.479733Z","title":"A review of multi-modal large language and vision models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.479733Z"},"links":{"cited_paper":"/paper/2404.01322","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:cdd96ae8ba4447067662d0da19d3383704f41ca48b94627131e8683e87248470","observation_id":"71f318e2-1579-4182-b768-4d14b299a69d","resolution":{"observed_at":"2026-08-07T05:36:15.479733Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1512.03012","last_updated":"2015-12-09T19:42:48Z","snapshot_observed_at":"2026-08-07T11:28:03.211074Z","submitted_at":"2015-12-09T19:42:48Z","title":"ShapeNet: An Information-Rich 3D Model Repository","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1512.03012","snapshot_observed_at":"2026-08-07T05:36:15.484473Z","title":"Shapenet: An information-rich 3d model repository","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.484473Z"},"links":{"cited_paper":"/paper/1512.03012","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:e62723e682f98e2da55ac72a43b76b13eeb20b8e20671823cf9773dde4479a56","observation_id":"778e27d7-e173-4975-b03c-8f1f85040522","resolution":{"observed_at":"2026-08-07T05:36:15.484473Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1504.00325","last_updated":"2015-04-03T20:21:16Z","snapshot_observed_at":"2026-08-04T18:05:27.145522Z","submitted_at":"2015-04-01T18:13:43Z","title":"Microsoft COCO Captions: Data Collection and Evaluation Server","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1504.00325","snapshot_observed_at":"2026-08-07T05:36:15.489481Z","title":"Microsoft coco captions: Data collection and evaluation server","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.489481Z"},"links":{"cited_paper":"/paper/1504.00325","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:795d51d910fe58f70b21f3fa3ee4bff87a76816d7a42a52fcc98f61910488e40","observation_id":"8e19de4c-965d-4307-a9e4-d5dd6321d415","resolution":{"observed_at":"2026-08-07T05:36:15.489481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03190","last_updated":"2024-05-27T11:52:56Z","snapshot_observed_at":"2026-07-06T17:25:35.493362Z","submitted_at":"2024-02-05T16:56:11Z","title":"Unified Hallucination Detection for Multimodal Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.03190","snapshot_observed_at":"2026-08-07T05:36:15.494189Z","title":"Unified hallucination detection for multi- modal large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.494189Z"},"links":{"cited_paper":"/paper/2402.03190","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:4a1434bd80d03ec330ccdc2043369af591c0bc1dc71ccc92245b0bf4d58397a5","observation_id":"376f40cc-73b1-4818-95c8-fbb7dec15dbc","resolution":{"observed_at":"2026-08-07T05:36:15.494189Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.14660","last_updated":"2024-12-25T06:05:36Z","snapshot_observed_at":"2026-07-06T20:09:53.938772Z","submitted_at":"2024-12-19T09:10:07Z","title":"Unveiling Uncertainty: A Deep Dive into Calibration and Performance of Multimodal Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.14660","snapshot_observed_at":"2026-08-07T05:36:15.499186Z","title":"Unveiling uncertainty: A deep dive into calibration and performance of multimodal large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.499186Z"},"links":{"cited_paper":"/paper/2412.14660","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:e3a39894f5a59a6a5d810bfe1d114933ea37960eb87165958aa8607662d1d417","observation_id":"ebdf2bfd-a829-47a8-b447-09ce69d6f26a","resolution":{"observed_at":"2026-08-07T05:36:15.499186Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.503666Z","title":"Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.503666Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:bb2ee3774c6ddf98bd635d1d43d6ad5ae6eb8cf03d60112ade078e60df4d09da","observation_id":"325846ed-c0dd-43d1-93f4-c8591d9a2503","resolution":{"observed_at":"2026-08-07T05:36:15.503666Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.507721Z","title":"I don’t know: Explicit modeling of uncertainty with an [idk] token","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.507721Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:5af76c97568a5251f616292a06517b96299890df0991d28cad84002400576f8d","observation_id":"e3efa6ed-bb55-4cda-9db9-f157a4f2a760","resolution":{"observed_at":"2026-08-07T05:36:15.507721Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.511842Z","title":"Human uncertainty in concept-based ai systems","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.511842Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:2606c0907c81508753cda14b727b8470d842a6d8de85084be053c4169f1541b1","observation_id":"ca946fa2-aa29-4d04-ab07-3c5d5c2bb9ce","resolution":{"observed_at":"2026-08-07T05:36:15.511842Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.516267Z","title":"Objaverse: A universe of annotated 3d objects","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.516267Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:d4184763bae57ae67660257b1e07fcc64161c953042eea656a941ca0ef62f99c","observation_id":"ed92ce87-3568-4fcf-a237-420118f28b56","resolution":{"observed_at":"2026-08-07T05:36:15.516267Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.520063Z","title":"Retrieve only when it needs: Adaptive re- trieval augmentation for hallucination mitigation in large lan- guage models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.520063Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:02c6de0232dcf664f0b77b452ffbeca644feacae44f168b3fe9e8bd2106dd27d","observation_id":"97b9a2c7-0104-4af2-9a91-389aedb00c99","resolution":{"observed_at":"2026-08-07T05:36:15.520063Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.523790Z","title":"Clotho: An audio captioning dataset","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.523790Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:f246dfe3448e765ea395444a5197ce7aacdddd983bd387cae14223740de2ee9e","observation_id":"7af75ba0-58a5-4ae3-a999-229f03909fb8","resolution":{"observed_at":"2026-08-07T05:36:15.523790Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.13861","last_updated":"2024-10-21T15:42:46Z","snapshot_observed_at":"2026-07-06T19:35:30.732080Z","submitted_at":"2024-10-17T17:59:57Z","title":"PUMA: Empowering Unified MLLM with Multi-granular Visual Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13861","snapshot_observed_at":"2026-08-07T05:36:15.528322Z","title":"Puma: Empowering unified mllm with multi- granular visual generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.528322Z"},"links":{"cited_paper":"/paper/2410.13861","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:021730c63cc24eae0dc73f9840885a73d5e67c2b69e6a637789328bb144e0635","observation_id":"e38279b1-d0d4-49ef-bde6-99226a0032bb","resolution":{"observed_at":"2026-08-07T05:36:15.528322Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2412.06474","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.344034Z","title":"From uncertainty to trust: Enhancing re- liability in vision-language models with uncertainty-guided dropout decoding","venue":null,"work_id":"09241cc3-74eb-495b-b618-843d28ed5886","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.532369Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:3f3b80543ecd5b82fc202d1f4a79ec00f0e87d732229f3d3c8a115ecc0b3efcf","observation_id":"0b6b566e-5ccb-4483-b7ed-342084bcd31f","resolution":{"observed_at":"2026-08-07T05:36:16.352161Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:17.144358Z","title":"Detecting hallucinations in large language models using semantic entropy","venue":null,"work_id":"f44a78d0-fd16-458c-97cd-e89dee3f7fa8","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.536133Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:695ee0022921ca5f1c7c70b64390d8e3bb10e7b77ab1d73d33c700d02909fd9b","observation_id":"e806c30d-0123-4821-90e1-c11fae348f40","resolution":{"observed_at":"2026-08-07T05:36:17.149174Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.03230","last_updated":"2024-05-07T11:55:10Z","snapshot_observed_at":"2026-08-08T08:08:54.459593Z","submitted_at":"2024-05-07T11:55:10Z","title":"Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.03230","snapshot_observed_at":"2026-08-07T05:36:15.540187Z","title":"Video-of-thought: Step-by-step video reasoning from perception to cognition","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.540187Z"},"links":{"cited_paper":"/paper/2501.03230","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:8477bfe5b6419371debc610db0870b6c99201ad5134000ac6b7c30322927586c","observation_id":"2347e678-cf70-4e00-b626-809cef25365c","resolution":{"observed_at":"2026-08-07T05:36:15.540187Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.19806","last_updated":"2024-10-08T08:39:04Z","snapshot_observed_at":"2026-08-05T07:34:18.685637Z","submitted_at":"2024-10-08T08:39:04Z","title":"Vitron: A Unified Pixel-level Vision LLM for Understanding, Generating, Segmenting, Editing","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.19806","snapshot_observed_at":"2026-08-07T05:36:15.544341Z","title":"Vitron: A unified pixel-level vision llm for understanding, generating, segmenting, editing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.544341Z"},"links":{"cited_paper":"/paper/2412.19806","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:ab0b264decb74d83f18e386551cd1c9a8011d0956659f7b141bf0bd50ed402ef","observation_id":"237fe246-e200-4e68-aaf0-7fab4d12797f","resolution":{"observed_at":"2026-08-07T05:36:15.544341Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:17.128750Z","title":"Enhancing video-language representations with structural spatio-temporal alignment","venue":null,"work_id":"1533642f-511b-4d22-891c-b4d9a41195f9","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.549346Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:94ee5bd5df5d833c863593a3db00a85911e151ccaa71cca436275cacd055a7fe","observation_id":"fb6d6d4e-0c6d-4329-bc25-88955f8ba0c2","resolution":{"observed_at":"2026-08-07T05:36:17.133079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:17.113480Z","title":"Imagebind: One embedding space to bind them all","venue":null,"work_id":"ba393dcb-c134-42ab-a3a7-49fb405ae688","year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.553009Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:e856049892a9031a6f8267a4e9ad806a680129c7a35b6f0ad3c5c261ff2c122d","observation_id":"df0cea6e-45ab-46c4-8b2b-f957556efdca","resolution":{"observed_at":"2026-08-07T05:36:17.117688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:17.098037Z","title":"Large language models respond to influence like humans","venue":null,"work_id":"459d079d-809a-400f-96e5-b9d8d8f46ea3","year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.557255Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:8926176d55c0c65e1152c4c233a216ca449fe482e5101d3cbdd1c55a6af617b2","observation_id":"c1842dab-1c97-42e8-bd92-e5701d9ac166","resolution":{"observed_at":"2026-08-07T05:36:17.102771Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:17.082600Z","title":"Onellm: One framework to align all modalities with language","venue":null,"work_id":"462d1ae0-4d0e-4557-b919-048f2225bef4","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.561326Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:8cf88cfa0f3b78d97290abed4462f72d0ffb903353cc7f5367ee3232b471d282","observation_id":"81acf36e-e34b-44a2-be82-0777b77a5356","resolution":{"observed_at":"2026-08-07T05:36:17.087585Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.564981Z","title":"Denoising dif- fusion probabilistic models","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.564981Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:648e528188c8ed6aeee58876126c59fc71a58117220336f7a0afe2c2346ec594","observation_id":"d5bb6bb3-9efb-4b11-92e7-c5a62c1a9e69","resolution":{"observed_at":"2026-08-07T05:36:15.564981Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.15769","last_updated":"2024-08-28T13:05:55Z","snapshot_observed_at":"2026-08-06T13:29:37.152582Z","submitted_at":"2024-08-28T13:05:55Z","title":"A Survey on Evaluation of Multimodal Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.15769","snapshot_observed_at":"2026-08-07T05:36:15.568736Z","title":"A survey on evaluation of multimodal large language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.568736Z"},"links":{"cited_paper":"/paper/2408.15769","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:276480021b58a1dcc24ec913b243a0688ceea4b49c21a33d049f43bdc861a63b","observation_id":"c2252e6d-8f3a-4ad4-81d6-87a0f853c88b","resolution":{"observed_at":"2026-08-07T05:36:15.568736Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.14683","last_updated":"2024-06-16T18:43:50Z","snapshot_observed_at":"2026-07-06T17:34:03.539565Z","submitted_at":"2024-02-22T16:40:33Z","title":"Visual Hallucinations of Multi-modal Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.14683","snapshot_observed_at":"2026-08-07T05:36:15.573134Z","title":"Visual hallucinations of multi-modal large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.573134Z"},"links":{"cited_paper":"/paper/2402.14683","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:bb4b6de3a539fc3bdaf19c8ba55e3f7698fe081bf038def4b21996153d6b2b18","observation_id":"467d2227-2375-4c1c-98e8-3e3dbcb4cde6","resolution":{"observed_at":"2026-08-07T05:36:15.573134Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21276","last_updated":"2024-10-25T17:43:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-10-25T17:43:01Z","title":"GPT-4o System Card","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.21276","snapshot_observed_at":"2026-08-07T05:36:15.578298Z","title":"Gpt-4o system card","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.578298Z"},"links":{"cited_paper":"/paper/2410.21276","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:ea2cfaff3a17ae4f6ecf0cd3e3a10fbd97854fd9bb558de619d5d7d1416b86fe","observation_id":"6677854a-7a7f-4690-9f27-78863eb71b10","resolution":{"observed_at":"2026-08-07T05:36:15.578298Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.05335","last_updated":"2023-07-20T16:24:14Z","snapshot_observed_at":"2026-08-08T00:02:42.043436Z","submitted_at":"2022-10-11T10:54:54Z","title":"MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model","version":3},"cited_work":{"arxiv_id":"2210.05335","doi":null,"metadata_source":"pith","pith_arxiv_id":"2210.05335","snapshot_observed_at":"2026-08-07T05:36:16.174627Z","title":"MAP: Multimodal Uncertainty-Aware Vision-Language Pre-training Model","venue":"cs.CV","work_id":"61825ff7-e0b0-41f2-88be-1824e0809ed4","year":2022},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.582961Z"},"links":{"cited_paper":"/paper/2210.05335","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:f0bf8e0c2f69199b011b9ed3de8119f0592b9667f2d9a2f8f6c881e30cce98dc","observation_id":"c84a9f05-7ab1-4223-8e26-233241932b2d","resolution":{"observed_at":"2026-08-07T05:36:16.179278Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.587156Z","title":"Mimic-cxr, a de- identified publicly available database of chest radiographs with free-text reports","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.587156Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:e81f17c6a19c5fed04f1f37e317a25664abad34c108b41b70c92d025e39f38a9","observation_id":"01ea5bc5-5f9c-4ccd-9054-63993b4d147f","resolution":{"observed_at":"2026-08-07T05:36:15.587156Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.01519","last_updated":"2025-04-20T08:45:26Z","snapshot_observed_at":"2026-07-06T17:11:04.789413Z","submitted_at":"2024-01-03T03:01:29Z","title":"Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.01519","snapshot_observed_at":"2026-08-07T05:36:15.591683Z","title":"Ex- ploring the frontiers of llms in psychological applications: A comprehensive review","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.591683Z"},"links":{"cited_paper":"/paper/2401.01519","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:0acd463d1d6a308f486d28f72560f56bf81cf57d751dda94f9b5def46ace6c5a","observation_id":"bcf371ae-1231-4d40-aa0c-495b7b9177e1","resolution":{"observed_at":"2026-08-07T05:36:15.591683Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:17.050299Z","title":"Audiocaps: Generating captions for audios in the wild","venue":null,"work_id":"ac18f856-c323-4490-aa1b-1366bc30f814","year":2019},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.596504Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:ab8ceae4f5126b99036887fe635bb6a346ba54d0aadcdf93c31c28e633aba4d0","observation_id":"75ec342a-cbb9-4f81-b4e8-667fd903db5d","resolution":{"observed_at":"2026-08-07T05:36:17.054522Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.15352","last_updated":"2023-03-05T09:14:16Z","snapshot_observed_at":"2026-08-07T16:54:38.689558Z","submitted_at":"2022-09-30T10:17:05Z","title":"AudioGen: Textually Guided Audio Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.15352","snapshot_observed_at":"2026-08-07T05:36:15.600823Z","title":"Audiogen: Textually guided audio gen- eration","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.600823Z"},"links":{"cited_paper":"/paper/2209.15352","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:1a9a471289d6639be8e9687223ba946d0047b8504edbd6c6a7d2ca2902938c7e","observation_id":"4e14ef2e-2a4b-44a6-abc1-7ad47759d318","resolution":{"observed_at":"2026-08-07T05:36:15.600823Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.14979","last_updated":"2024-12-05T02:38:38Z","snapshot_observed_at":"2026-08-09T14:17:19.560504Z","submitted_at":"2024-07-20T21:06:33Z","title":"RGB2Point: 3D Point Cloud Generation from Single RGB Images","version":4},"cited_work":{"arxiv_id":"2407.14979","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.14979","snapshot_observed_at":"2026-08-07T05:36:16.127620Z","title":"RGB2Point: 3D Point Cloud Generation from Single RGB Images","venue":"cs.CV","work_id":"8e326dad-a212-43e5-9b52-11884978cfc5","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.605520Z"},"links":{"cited_paper":"/paper/2407.14979","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:396365bdd1b89f781a9fdc628bb89e506a7891bc830cc5bb00901f9026ac492d","observation_id":"5fe5e464-8070-4b80-bcc6-c7ed9502e635","resolution":{"observed_at":"2026-08-07T05:36:16.132027Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.13388","last_updated":"2024-06-06T13:25:09Z","snapshot_observed_at":"2026-07-06T17:19:52.125879Z","submitted_at":"2024-01-24T11:36:44Z","title":"UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion","version":3},"cited_work":{"arxiv_id":"2401.13388","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.13388","snapshot_observed_at":"2026-08-07T05:36:16.108618Z","title":"UNIMO-G: Unified Image Generation through Multimodal Conditional Diffusion","venue":"cs.CV","work_id":"328391e6-ebfa-4dce-adeb-5755fe691d9a","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.609922Z"},"links":{"cited_paper":"/paper/2401.13388","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:64959f1de521104375f6d20396bc0f7dceab5b4e843a4e4cdfbda3f0bb58724c","observation_id":"8d212d59-c7e4-41a7-8a5a-fbfbdaee565d","resolution":{"observed_at":"2026-08-07T05:36:16.113155Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10355","last_updated":"2023-10-26T02:52:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-17T16:34:01Z","title":"Evaluating Object Hallucination in Large Vision-Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.10355","snapshot_observed_at":"2026-08-07T05:36:15.614324Z","title":"Evaluating object hallucination in large vision-language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.614324Z"},"links":{"cited_paper":"/paper/2305.10355","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:179f7e645b38458f06d0a760b1d63c47b9ed1394f400778232b4f55382d09902","observation_id":"d1f731e9-3188-434b-9555-0abe0b85a997","resolution":{"observed_at":"2026-08-07T05:36:15.614324Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.10122","last_updated":"2024-10-01T12:07:31Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-11-16T10:59:44Z","title":"Video-LLaVA: Learning United Visual Representation by Alignment Before Projection","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.10122","snapshot_observed_at":"2026-08-07T05:36:15.619085Z","title":"Video-llava: Learning united visual repre- sentation by alignment before projection.arXiv:2311.10122,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.619085Z"},"links":{"cited_paper":"/paper/2311.10122","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:31083705ed20610b833218b37f07a9583db57cc07f215bde52e8fc6058b8779b","observation_id":"ec0414f0-53ca-4d81-9263-dc1580cfc322","resolution":{"observed_at":"2026-08-07T05:36:15.619085Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:17.036970Z","title":"Clotho-aqa: A crowd- sourced dataset for audio question answering","venue":null,"work_id":"37889fba-5fe9-4b82-b891-477bf6353d08","year":2022},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.623493Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:9e7621a719e060508c2222a591f42410b5240829355d753e82f9dcbbb2cef3ad","observation_id":"bf64d6b2-be98-4356-a98e-0283d0c71af2","resolution":{"observed_at":"2026-08-07T05:36:17.040842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.14565","last_updated":"2024-03-19T22:53:25Z","snapshot_observed_at":"2026-08-06T22:33:34.254048Z","submitted_at":"2023-06-26T10:26:33Z","title":"Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.14565","snapshot_observed_at":"2026-08-07T05:36:15.627411Z","title":"Mitigating hallucination in large multi-modal models via robust instruction tuning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.627411Z"},"links":{"cited_paper":"/paper/2306.14565","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:5c09a81521d5b73b2764949334bc160a8ee6a77728e5c0dc4e8139cc2b3e8db5","observation_id":"8b24cdc6-a01c-4e9a-8db5-3475d99d59cc","resolution":{"observed_at":"2026-08-07T05:36:15.627411Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:17.023576Z","title":"Visual instruction tuning","venue":null,"work_id":"ce6cbce7-dec1-4854-91c7-81de0191f1e5","year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.632144Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:d7452bb979809e92f8313ada4093bfd7261ca8dfcb72fa1fe19dcf83e8f4cd52","observation_id":"2dd78eba-5d68-4e87-ae0e-31bd69f75c75","resolution":{"observed_at":"2026-08-07T05:36:17.027803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08320","last_updated":"2023-10-13T01:43:04Z","snapshot_observed_at":"2026-08-05T15:11:09.163965Z","submitted_at":"2023-03-15T02:16:39Z","title":"VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08320","snapshot_observed_at":"2026-08-07T05:36:15.636162Z","title":"Videofusion: Decomposed diffusion models for high-quality video generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.636162Z"},"links":{"cited_paper":"/paper/2303.08320","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:83eec72d403c1822e02e83a8948fbc9a0b92adb72cf2d61d020f95c9b9b47675","observation_id":"ae0d8297-91b7-4cc9-9557-3208a3e74c0d","resolution":{"observed_at":"2026-08-07T05:36:15.636162Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:17.010802Z","title":"Unibind: Llm-augmented unified and balanced representa- tion space to bind them all","venue":null,"work_id":"d5fa46df-2999-43c2-9f19-9d759cac7e41","year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.640261Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:037c68443a05f9c681bc90a3a926c96a9d0d7bb1fb484fe590956f23cfddd64a","observation_id":"cac0082e-be49-4cd1-b3af-e2c5b8aaacd0","resolution":{"observed_at":"2026-08-07T05:36:17.014887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.996306Z","title":"Openeqa: Embodied question answering in the era of foun- dation models","venue":null,"work_id":"9221a2d7-61b0-4c88-a087-47274ff301d0","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.644736Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:a24bcab8f339e97f9bc120577a4aef0d9aedfec1c6e72f002c4d3a035dfb6a42","observation_id":"daefd627-3d13-41eb-a34c-88f115b96a00","resolution":{"observed_at":"2026-08-07T05:36:17.000738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.08751","last_updated":"2022-12-16T23:22:59Z","snapshot_observed_at":"2026-07-06T14:31:54.932806Z","submitted_at":"2022-12-16T23:22:59Z","title":"Point-E: A System for Generating 3D Point Clouds from Complex Prompts","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.08751","snapshot_observed_at":"2026-08-07T05:36:15.648822Z","title":"Point-e: A system for generating 3d point clouds from complex prompts","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.648822Z"},"links":{"cited_paper":"/paper/2212.08751","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:283810c6d8c9c8f7815dccb4bb19b8aeb97fbd4a0c10bd31c12dc24c619d3d1a","observation_id":"8a27a624-c870-4bdd-bafd-a7999d2625b2","resolution":{"observed_at":"2026-08-07T05:36:15.648822Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.981693Z","title":"Human uncertainty makes clas- sification more robust","venue":null,"work_id":"f5be5112-1456-43d4-bf4e-be8a6ce7fed7","year":2019},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.653333Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:8b51e7f088aac741c9e6395e44de8fe1cf2f4ac601c4d9f6be2ba784a7ad6228","observation_id":"af333303-2975-4ef3-846b-bf441ccd6fd3","resolution":{"observed_at":"2026-08-07T05:36:16.986280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02906","last_updated":"2024-06-17T16:53:49Z","snapshot_observed_at":"2026-08-07T09:15:19.297634Z","submitted_at":"2024-01-05T17:05:42Z","title":"MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02906","snapshot_observed_at":"2026-08-07T05:36:15.657440Z","title":"Mllm-protector: Ensuring mllm’s safety without hurting per- formance","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.657440Z"},"links":{"cited_paper":"/paper/2401.02906","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:8ce923d6431a02375bb7aa67412236bc68d985c90157290c3a8be8d0c7b12556","observation_id":"54ad4906-8783-4811-9f0b-c3012997d958","resolution":{"observed_at":"2026-08-07T05:36:15.657440Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.968326Z","title":"Flickr30k entities: Collecting region-to-phrase corre- spondences for richer image-to-sentence models","venue":null,"work_id":"ab29f5d4-b8a1-4831-b196-31dc4341684e","year":2015},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.661704Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:bae57d2706bcad1055d97e4c6b09acfc4be4f9d900a53ab4d3a60893ed2b9917","observation_id":"7e38aa81-7496-4998-b151-13add24a20ee","resolution":{"observed_at":"2026-08-07T05:36:16.972679Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.954228Z","title":"Robust speech recognition via large-scale weak supervision","venue":null,"work_id":"94a8ba5e-de47-45b0-8bfc-84c43b69b096","year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.665572Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:b1af25ece44777742c58bd8e75f3e510f9c3f7d153c386a763c42368c1031d66","observation_id":"0440a7a7-ffff-4e94-8d09-61ab9705dc2c","resolution":{"observed_at":"2026-08-07T05:36:16.958347Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1809.02156","last_updated":"2019-03-29T23:48:52Z","snapshot_observed_at":"2026-08-04T05:57:07.163978Z","submitted_at":"2018-09-06T18:25:18Z","title":"Object Hallucination in Image Captioning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.02156","snapshot_observed_at":"2026-08-07T05:36:15.669523Z","title":"Object hallucination in image cap- tioning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.669523Z"},"links":{"cited_paper":"/paper/1809.02156","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:3a3b09a6da01da93a86488fc553212ef73bc0b45a9cc55df6ba3e69a4e6af486","observation_id":"07b9fbbe-98d3-49d7-ba6f-307a9daff762","resolution":{"observed_at":"2026-08-07T05:36:15.669523Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.939149Z","title":"High-resolution image syn- thesis with latent diffusion models","venue":null,"work_id":"e7381a1d-db90-47ce-a7e6-84423795aaef","year":2022},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.673597Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:66ba7579c000bc3754c7d73ffb26ed2a40930bcbbcfb40588a2b4db93346293e","observation_id":"faefea57-4f5e-4ad6-9d7d-de744989a0d0","resolution":{"observed_at":"2026-08-07T05:36:16.944222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.05563","last_updated":"2025-07-01T22:08:39Z","snapshot_observed_at":"2026-07-06T20:03:11.541819Z","submitted_at":"2024-12-07T06:56:01Z","title":"A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.05563","snapshot_observed_at":"2026-08-07T05:36:15.677482Z","title":"A survey on uncertainty quantification of large language models: Taxonomy, open research chal- lenges, and future directions","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.677482Z"},"links":{"cited_paper":"/paper/2412.05563","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:c69db38b65d833b333fd10c6832b719f1242bf18bedc08bf4f50d2997e50696b","observation_id":"eca5bd21-10f8-4cc3-91c8-1e66359ac523","resolution":{"observed_at":"2026-08-07T05:36:15.677482Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.923366Z","title":"Moma: Multimodal llm adapter for fast personalized image generation","venue":null,"work_id":"e859cdde-f485-45ab-8170-bc7c0c598be3","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.682096Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:9e8094265e74eade8500b78e5f25217b25d36a32e489e50d861c98b13fd61e70","observation_id":"5a5ddccc-f0da-48e1-ab39-cea1af7510ee","resolution":{"observed_at":"2026-08-07T05:36:16.927402Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.907717Z","title":"Pix3d: Dataset and methods for single-image 3d shape modeling","venue":null,"work_id":"a5f989a8-12e6-41c3-b307-ba4955a357c3","year":2018},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.686084Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:f31c062c2d9470689fd25172a3f655c22a2596f684996be6d45d7a23348771b4","observation_id":"6bbc8983-0700-42fc-adbe-2898be57e7a3","resolution":{"observed_at":"2026-08-07T05:36:16.913292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.893584Z","title":"Any-to-any generation via composable diffu- sion","venue":null,"work_id":"f134dabe-5217-4d89-ab73-cdc6b301c9d2","year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.690326Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:dfa7e604a263fc8b30ef9bcb83d72fff6d6cdd0d06a58fe819158d9e1655619f","observation_id":"dd0d44dc-603d-40b7-8a28-579308a563b1","resolution":{"observed_at":"2026-08-07T05:36:16.898734Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.879400Z","title":"Codi-2: In-context in- terleaved and interactive any-to-any generation","venue":null,"work_id":"43018479-2e01-4e6f-9f18-adedba9c5860","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.694155Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:ee24afc4ed6f3e6dde8de73560f6a454f9e0cb79379414df31850da1f8aa383a","observation_id":"49d04c41-9cc9-4a29-9a9a-9659e12366b7","resolution":{"observed_at":"2026-08-07T05:36:16.883874Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2004.02990","last_updated":"2021-01-24T09:49:19Z","snapshot_observed_at":"2026-08-09T17:53:12.264277Z","submitted_at":"2020-04-06T20:44:10Z","title":"Evaluating the Evaluation of Diversity in Natural Language Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.02990","snapshot_observed_at":"2026-08-07T05:36:15.698346Z","title":"Evaluating the evaluation of diversity in natural language generation","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.698346Z"},"links":{"cited_paper":"/paper/2004.02990","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:a7e9b92c60092a63e6138814dca3a1906c95167b41e31f4ff769ebeec2b93e10","observation_id":"476d3ee4-1bd3-480e-8dfe-036b1e821b17","resolution":{"observed_at":"2026-08-07T05:36:15.698346Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.15126","last_updated":"2023-10-10T11:57:26Z","snapshot_observed_at":"2026-08-01T17:12:16.290540Z","submitted_at":"2023-08-29T08:51:24Z","title":"Evaluation and Analysis of Hallucination in Large Vision-Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.15126","snapshot_observed_at":"2026-08-07T05:36:15.702798Z","title":"Evaluation and analysis of halluci- nation in large vision-language models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.702798Z"},"links":{"cited_paper":"/paper/2308.15126","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:b0fc4ec7bfc7b47a09808c131d5a9889a4288e9e71c18f32ec46cdd5e82cc6d7","observation_id":"8e9d0d8f-51dc-419f-a014-a59245f18cdf","resolution":{"observed_at":"2026-08-07T05:36:15.702798Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.04854","last_updated":"2024-06-07T11:37:45Z","snapshot_observed_at":"2026-08-07T05:36:07.498338Z","submitted_at":"2024-06-07T11:37:45Z","title":"Uncertainty Aware Learning for Language Model Alignment","version":1},"cited_work":{"arxiv_id":"2406.04854","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.04854","snapshot_observed_at":"2026-08-07T05:36:15.949675Z","title":"Uncertainty Aware Learning for Language Model Alignment","venue":"cs.CL","work_id":"a0392a55-a955-417c-9c36-4d569f197ebe","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.707773Z"},"links":{"cited_paper":"/paper/2406.04854","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:43723356f966c7ca436c4756af8f7cd95f9e2180a7343b1334022b59f03abc42","observation_id":"ae3f04ff-f2a2-460f-8022-02163d43b24e","resolution":{"observed_at":"2026-08-07T05:36:15.955675Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.865638Z","title":"Multimodal large language models: A sur- vey","venue":null,"work_id":"a8f89f49-d2c7-451d-9cdf-e08cc7d5102d","year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.712088Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:cb5242f7d3c02897b069bce94b4b98d80e6329f8351a6a8636108db8d51c0219","observation_id":"8e788e5a-7fc5-4718-a811-dd04f9b82aea","resolution":{"observed_at":"2026-08-07T05:36:16.870372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.15310","last_updated":"2024-09-05T08:47:34Z","snapshot_observed_at":"2026-08-05T20:59:08.258366Z","submitted_at":"2024-09-05T08:47:34Z","title":"Visual Prompting in Multimodal Large Language Models: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.15310","snapshot_observed_at":"2026-08-07T05:36:15.716207Z","title":"Visual prompting in multimodal large language models: A survey","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.716207Z"},"links":{"cited_paper":"/paper/2409.15310","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:285e9ecfa5e64e179be1eec49ddb4c2bb58a71546f0530fdf689ec6e3a487ba1","observation_id":"7aaf53df-d37c-4d31-b5c1-7996665ae2f2","resolution":{"observed_at":"2026-08-07T05:36:15.716207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.720986Z","title":"Next-gpt: Any-to-any multimodal llm","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.720986Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:ee640901dbb597cdd2184f3b9ffd822fbb8b72ee4a8a16ddedf961eccf96eab9","observation_id":"12192345-6dc4-4ee5-8aa6-b83f32a2c336","resolution":{"observed_at":"2026-08-07T05:36:15.720986Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.843093Z","title":"Self-correcting llm-controlled diffusion models","venue":null,"work_id":"b93fc7b6-bea3-4afe-9b74-463dc3ed33d5","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.724944Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:27dbec908892a713add0b71df68da2db69900bd762075864fdb96424d705d699","observation_id":"3020b22e-730f-449a-a1b0-7c92dec595ea","resolution":{"observed_at":"2026-08-07T05:36:16.847851Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.829267Z","title":"Can graph learning improve planning in llm-based agents? In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024","venue":null,"work_id":"1b30ed3b-2ed2-4e8b-bf6d-39010b08d7dd","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.728850Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:82fb5dd997ad1cd30300bd07c8ca83fa9d44ffc6735e6690b80e7db0df126ff2","observation_id":"1d991fb0-35ef-43ac-8b4d-0d762251ead3","resolution":{"observed_at":"2026-08-07T05:36:16.834135Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.814720Z","title":"3d shapenets: A deep representation for volumetric shapes","venue":null,"work_id":"b3bd9769-fecf-4b79-a170-c28419e65af4","year":1912},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.732697Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:fbb65f0e0054b6af6407d158d28ef559165cb9ff249056904c3ffbf41a692258","observation_id":"2548339c-b73b-4fa1-af65-6be55726c9a3","resolution":{"observed_at":"2026-08-07T05:36:16.819142Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.737268Z","title":"Next-qa: Next phase of question-answering to explaining temporal actions","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.737268Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:abbc3a446b419d2f4d54d26c39a03966b9830f64751e76fe76765c882766f3bf","observation_id":"2ae6169d-5f76-4e1c-8488-ab0d4516dd1c","resolution":{"observed_at":"2026-08-07T05:36:15.737268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.13063","last_updated":"2024-03-17T04:38:48Z","snapshot_observed_at":"2026-07-06T15:45:39.649725Z","submitted_at":"2023-06-22T17:31:44Z","title":"Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.13063","snapshot_observed_at":"2026-08-07T05:36:15.741481Z","title":"Can llms express their un- certainty? an empirical evaluation of confidence elicitation in llms","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.741481Z"},"links":{"cited_paper":"/paper/2306.13063","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:0cc65d7a31390f1c2776cb9b7b1ec06d2c3749798f9a755079e87538b20cdfe2","observation_id":"68d2ece3-1225-4022-bb25-888c3f0296f0","resolution":{"observed_at":"2026-08-07T05:36:15.741481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.793059Z","title":"Video question answer- ing via gradually refined attention over appearance and mo- tion","venue":null,"work_id":"9e9faa12-e431-460c-b33b-73932c7a68a2","year":2017},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.745559Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:0246c69abe3a40a95be4c926bfe145c710edab351e7a300d66adc882da0563dc","observation_id":"d77d7aba-9da5-4367-b1f5-502704668300","resolution":{"observed_at":"2026-08-07T05:36:16.797287Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:15.749730Z","title":"Msr-vtt: A large video description dataset for bridging video and language","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.749730Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:70268d3e2e593946d9c0a1ca8dbf422b6d0a01ae58b11fabb3856d6fb8c1d218","observation_id":"17999f8c-8899-4ab5-b676-2c98cabc63c4","resolution":{"observed_at":"2026-08-07T05:36:15.749730Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.770475Z","title":"Pointllm: Empowering large lan- guage models to understand point clouds","venue":null,"work_id":"92d3d037-674b-41eb-8387-f7c3a140e8fb","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.753669Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:13a53bf63ec5c8777536b23b1424ff18f7e172077e28a8c8ef7a1c450ed2fd76","observation_id":"7af7cedc-e546-45e1-930f-9a1318550ad7","resolution":{"observed_at":"2026-08-07T05:36:16.774727Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.756594Z","title":"Cstr vctk corpus: English multi-speaker corpus for cstr voice cloning toolkit (version 0.92)","venue":null,"work_id":"c6ead2bb-93da-44b3-aa87-06228200cf08","year":2019},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.757713Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:dcc6a36bd07f0884561b92bf3e94c96333d21e22d2c490460ee021d2d67dfdd9","observation_id":"094700cd-9f89-41d9-a81a-2f388c89175c","resolution":{"observed_at":"2026-08-07T05:36:16.760808Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.02490","last_updated":"2024-12-01T05:46:03Z","snapshot_observed_at":"2026-08-08T03:31:37.699253Z","submitted_at":"2023-08-04T17:59:47Z","title":"MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.02490","snapshot_observed_at":"2026-08-07T05:36:15.761382Z","title":"Mm-vet: Evaluating large multimodal models for integrated capabilities","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.761382Z"},"links":{"cited_paper":"/paper/2308.02490","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:35e273f58ab3f2bf910d2ae44f23a98b7c490b4d36e0e2a5fb70b43f3d57632f","observation_id":"a5cad0f1-76b9-4ebd-a0dd-7ac05c6960c3","resolution":{"observed_at":"2026-08-07T05:36:15.761382Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.12226","last_updated":"2025-09-08T07:04:17Z","snapshot_observed_at":"2026-07-06T17:32:15.447061Z","submitted_at":"2024-02-19T15:33:10Z","title":"AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.12226","snapshot_observed_at":"2026-08-07T05:36:15.766361Z","title":"Anygpt: Unified multimodal llm with dis- crete sequence modeling","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.766361Z"},"links":{"cited_paper":"/paper/2402.12226","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:dff742f33e436a6d9a8783a7fc012b67c3b2002eb42ff438575d46d311af2f13","observation_id":"acd1e886-8c71-4176-9c05-ff8507bccb95","resolution":{"observed_at":"2026-08-07T05:36:15.766361Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.02858","last_updated":"2023-10-25T06:23:31Z","snapshot_observed_at":"2026-07-06T15:38:39.712379Z","submitted_at":"2023-06-05T13:17:27Z","title":"Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.02858","snapshot_observed_at":"2026-08-07T05:36:15.771552Z","title":"Video-llama: An instruction-tuned audio-visual language model for video un- derstanding","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.771552Z"},"links":{"cited_paper":"/paper/2306.02858","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:a0f60ddfb4128030d5684a450e3462b5b55f00c368e4477b13675eb847b8b32b","observation_id":"45cee82c-6fd7-4084-85f8-f5d2d5618ef3","resolution":{"observed_at":"2026-08-07T05:36:15.771552Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.742553Z","title":"Approaching outside: scaling unsupervised 3d object detec- tion from 2d scene","venue":null,"work_id":"49457ff4-4bb5-435a-a1c5-a15c4ba7a2b1","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.775728Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:8a8dd10506af2296ab5c3bb63cf6eee744f45a0842bf68f8d860411adf2584d2","observation_id":"7611bbc7-6cac-430a-b7d1-240cca9eed78","resolution":{"observed_at":"2026-08-07T05:36:16.747296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00619","last_updated":"2024-10-08T14:13:38Z","snapshot_observed_at":"2026-08-04T02:27:20.841925Z","submitted_at":"2024-08-01T15:01:07Z","title":"Harnessing Uncertainty-aware Bounding Boxes for Unsupervised 3D Object Detection","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00619","snapshot_observed_at":"2026-08-07T05:36:15.779306Z","title":"Harnessing uncertainty-aware bounding boxes for unsuper- vised 3d object detection","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.779306Z"},"links":{"cited_paper":"/paper/2408.00619","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:847000ff72d3950ed458a7634507032369faf5228177d7b05126f5f5fffbd9ff","observation_id":"50519c5e-2aab-46ab-9f8b-fea6a440e93e","resolution":{"observed_at":"2026-08-07T05:36:15.779306Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11919","last_updated":"2024-11-28T13:35:56Z","snapshot_observed_at":"2026-07-06T19:52:11.774784Z","submitted_at":"2024-11-18T04:06:04Z","title":"VL-Uncertainty: Detecting Hallucination in Large Vision-Language Model via Uncertainty Estimation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.11919","snapshot_observed_at":"2026-08-07T05:36:15.783537Z","title":"Vl- uncertainty: Detecting hallucination in large vision-language model via uncertainty estimation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.783537Z"},"links":{"cited_paper":"/paper/2411.11919","citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:cd5f7a249df2a3d84f8a9c84ae32f473e35f80a778c889d76af0312bc0bc0559","observation_id":"a5cf42fd-d216-42ae-a7d1-3d8de849d069","resolution":{"observed_at":"2026-08-07T05:36:15.783537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.728446Z","title":"Prompt highlighter: Interactive control for multi- modal llms","venue":null,"work_id":"21c64278-e5d5-4006-8644-4405757b48cd","year":2024},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.788459Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:430e2df4085a6e205a1ffff56ccd3dabc44c383ea9bba88efaf9f37c5c61f6b3","observation_id":"51bd2dbd-eea2-411e-b2b7-7b3920ad1b1b","resolution":{"observed_at":"2026-08-07T05:36:16.732868Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.714397Z","title":"As a result, any fluctuation in answers of LMM directly reflects its uncertainty","venue":null,"work_id":"4e812b64-bd7b-454b-ab48-ce6e937e162e","year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.792698Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:05512e164f4f3b2ed62d2a03a8c14ca0830958b73d800c94697919e63acc2f9f","observation_id":"bc126e85-5740-401c-b7a4-a282d1e3069e","resolution":{"observed_at":"2026-08-07T05:36:16.719241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.698267Z","title":"We conduct experiments with 18 benchmarks","venue":null,"work_id":"32f0de35-71da-43c8-b4ba-e1fb84628bc5","year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.797322Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:8a3cf2bfe6d38096af993784909139ffc47e70b12a5809688a6347180d668b47","observation_id":"59e14804-32b7-419f-aa1b-2e1e6a5dc455","resolution":{"observed_at":"2026-08-07T05:36:16.703460Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.682050Z","title":"We report the ablation of text clustering methods (see Tab","venue":null,"work_id":"f9b44dad-bbf7-4675-ad77-37d636602819","year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.801877Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:983ccff25d4ceb9959308420b8080b8f91ebdc7aa54cd03b53fb37a61056684c","observation_id":"2c3f1bf3-685f-42ab-8bcc-49e730a33205","resolution":{"observed_at":"2026-08-07T05:36:16.687117Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.667165Z","title":"Definitions and Assumptions","venue":null,"work_id":"6f0f1440-ac66-4828-af05-3961024c928e","year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.805895Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:e302f95df1a55e8ef892675b4dc989241335d8e5e414f390366c63ba3c5cbe81","observation_id":"a29543ef-6ce6-4957-a66d-3b7cd3d2b15a","resolution":{"observed_at":"2026-08-07T05:36:16.671652Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.652730Z","title":"For those input prompts, the predictions from the large model is yi = M (xi), and yj = M (xj), respectively","venue":null,"work_id":"ed10ecf1-93bc-4e13-b4a5-0557eb653d28","year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.811029Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:ff9a7b22a179eb8b4d7ad2276a92dabcfe576ff17822bc05d6db3631c929363d","observation_id":"7c2f0cd5-22ec-45d7-8c1e-9acca061a8f3","resolution":{"observed_at":"2026-08-07T05:36:16.657634Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.639064Z","title":"Assume the large model parameters θ are random variables with a prior distribution P (θ)","venue":null,"work_id":"ac0a6a0e-614f-4bd2-b90c-cff0d56b37f3","year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.815113Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:1931fb108b4f5c0a3e5db76d8fa04c5a03b8e81004ccb234cf9078840f08aae1","observation_id":"f4f9f391-c9db-42c5-93a9-ecf227b8ab9e","resolution":{"observed_at":"2026-08-07T05:36:16.643193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:36:16.625176Z","title":null,"venue":null,"work_id":"8d9ceb1a-710c-4d46-8255-1c5502baabca","year":null},"citing_paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-07T05:36:15.819379Z"},"links":{"citing_paper":"/paper/2506.07575"},"observation_digest":"sha256:3dd3afe5b36e18568f43a1562fdfcbe548df26641d6f88de1407f6fdd9529fb6","observation_id":"b780146d-e00e-45f0-8537-459bcb0c434f","resolution":{"observed_at":"2026-08-07T05:36:16.629270Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.07575","last_updated":"2025-06-09T09:20:20Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-08T12:50:28.189950Z","submitted_at":"2025-06-09T09:20:20Z","title":"Uncertainty-o: One Model-agnostic Framework for Unveiling Uncertainty in Large Multimodal Models"},"reference_resolution":{"displayed":90,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":52,"verified_exact":5,"verified_fuzzy":32},"total_outbound_references":90},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 90 of 90 outbound references and 1 inbound Pith citation observation for arXiv:2506.07575."}