{"as_of":"2026-08-09T22:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7cd577ee8c52c10aa84cb45fc75e9d8cdd772030c149a15b15d7ffd6013747de","coverage":[{"denominator":15,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":15,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T13:59:32.095450Z","state":"measured"},{"denominator":17,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":17,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T20:53:59.386831Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-07T14:23:13.514228Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.01943","snapshot_observed_at":"2026-08-09T20:53:59.386831Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2501.19243","last_updated":"2025-07-18T01:49:36Z","snapshot_observed_at":"2026-08-09T20:47:50.641676Z","submitted_at":"2025-01-31T15:58:15Z","title":"Accelerating Diffusion Transformer via Error-Optimized Cache","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-09T20:53:59.386831Z"},"links":{"cited_paper":"/paper/2502.01943","citing_paper":"/paper/2501.19243"},"observation_digest":"sha256:b430d83e879349bfedbdba49e0fc7cb131da1655c751338363bbafd7d7a63946","observation_id":"e1d98e76-d1b5-46b8-8c07-44b113e5db60","resolution":{"observed_at":"2026-08-09T20:53:59.386831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"cited_work":{"arxiv_id":"2502.01943","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.01943","snapshot_observed_at":"2026-08-07T14:23:13.514228Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","venue":"cs.CV","work_id":"9a35ee21-c0c2-40cc-a7f4-5c4c275daa72","year":2025},"citing_paper":{"arxiv_id":"2505.19139","last_updated":"2025-05-25T13:22:10Z","snapshot_observed_at":"2026-08-09T13:01:06.369126Z","submitted_at":"2025-05-25T13:22:10Z","title":"The Eye of Sherlock Holmes: Uncovering User Private Attribute Profiling via Vision-Language Model Agentic Framework","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:08.906388Z"},"links":{"cited_paper":"/paper/2502.01943","citing_paper":"/paper/2505.19139"},"observation_digest":"sha256:87eb1a112ebd458eefa80600e60bd95cbbb232f9c19bf51b4dce08346033fb8b","observation_id":"0d1ca2c1-1129-457f-89c3-30990c7f23e7","resolution":{"observed_at":"2026-08-07T14:23:13.527862Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/2502.01943/citation-record","integrity":"/paper/2502.01943/integrity","json":"/paper/2502.01943/citation-record.json","paper":"/paper/2502.01943"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2308.12966","last_updated":"2023-10-13T02:41:28Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-08-24T17:59:17Z","title":"Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.12966","snapshot_observed_at":"2026-08-09T13:59:32.037258Z","title":"Qwen-vl: A versatile vision- language model for understanding, localization, text read- ing, and beyond","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.037258Z"},"links":{"cited_paper":"/paper/2308.12966","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:0634c319b8d7bf33ca61d6454fd828038b7a54969b5b24fa4dbf40e6b3c7c9b7","observation_id":"d300ea80-1954-489b-ba0c-fc9b6d13275a","resolution":{"observed_at":"2026-08-09T13:59:32.037258Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-09T13:59:32.046276Z","title":"The llama 3 herd of models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.046276Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:2e070497553b24bf52218939f8cd9b93083b566cb7d9371781553785a02fcf9c","observation_id":"f5e5e68d-9ea2-4121-8ba0-2b6d5eb03d34","resolution":{"observed_at":"2026-08-09T13:59:32.046276Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01306","last_updated":"2024-11-19T18:12:45Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-02T10:53:36Z","title":"KTO: Model Alignment as Prospect Theoretic Optimization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01306","snapshot_observed_at":"2026-08-09T13:59:32.050746Z","title":"Kto: Model alignment as prospect theoretic optimization","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.050746Z"},"links":{"cited_paper":"/paper/2402.01306","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:2e1a2e074a1a104b1711815d82c846d8e8d07f65cede1d86c793b1904aab27fb","observation_id":"e1030011-aa2b-46ab-ba4f-e52b507eaa14","resolution":{"observed_at":"2026-08-09T13:59:32.050746Z","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":"2026-08-09T13:59:32.055043Z","title":"Token preference optimization with self-calibrated visual-anchored rewards for hallucination mitigation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.055043Z"},"links":{"citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:795845242b04f116010104a654229f5a48a321c17e644c8f432eaf8601cc97d2","observation_id":"f3ee954c-ba87-4845-992a-3e91f291e224","resolution":{"observed_at":"2026-08-09T13:59:32.055043Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.09421","last_updated":"2024-10-18T07:10:38Z","snapshot_observed_at":"2026-08-09T21:21:53.791829Z","submitted_at":"2024-10-12T07:56:47Z","title":"VLFeedback: A Large-Scale AI Feedback Dataset for Large Vision-Language Models Alignment","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.09421","snapshot_observed_at":"2026-08-09T13:59:32.058953Z","title":"Vlfeedback: A large- scale ai feedback dataset for large vision-language models alignment","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.058953Z"},"links":{"cited_paper":"/paper/2410.09421","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:a88b4c7bbfc5234561908df5954a2db3e08efdbb90c66bed28edfd8cc5fe8c53","observation_id":"afc6de6e-0e76-4ca9-b406-e94918da8df2","resolution":{"observed_at":"2026-08-09T13:59:32.058953Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-09T13:59:32.067667Z","title":"A., Burns, K., Darrell, T., and Saenko, K","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.067667Z"},"links":{"cited_paper":"/paper/1809.02156","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:f09196274272d9c217fe51c9dd518a848458b81347e5b2021c2c92544f01bdd9","observation_id":"1827db70-d2fa-4d20-9062-aa7a2cc4ba36","resolution":{"observed_at":"2026-08-09T13:59:32.067667Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.11839","last_updated":"2024-10-07T17:59:42Z","snapshot_observed_at":"2026-07-06T18:32:23.999019Z","submitted_at":"2024-06-17T17:59:58Z","title":"mDPO: Conditional Preference Optimization for Multimodal Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.11839","snapshot_observed_at":"2026-08-09T13:59:32.075831Z","title":"Y ., Xu, N., Zhang, S., Poon, H., and Chen, M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.075831Z"},"links":{"cited_paper":"/paper/2406.11839","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:be3137506a487a71bb0925949fd5e6b3f4c68d892eba00e41f6eea4027e5a654","observation_id":"dc4d2bb4-814a-4e9e-85d4-3a1042a8ed3e","resolution":{"observed_at":"2026-08-09T13:59:32.075831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.07397","last_updated":"2024-02-23T07:54:11Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-11-13T15:25:42Z","title":"AMBER: An LLM-free Multi-dimensional Benchmark for MLLMs Hallucination Evaluation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.07397","snapshot_observed_at":"2026-08-09T13:59:32.079834Z","title":"An llm-free multi-dimensional benchmark for mllms hallucination evaluation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.079834Z"},"links":{"cited_paper":"/paper/2311.07397","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:f026331cea725cbf90452309810268658a2e4c9239f0c23a44fbe50f0d6fe145","observation_id":"6b8ee613-5966-4523-bfb6-eb4e7f6a5114","resolution":{"observed_at":"2026-08-09T13:59:32.079834Z","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":"2026-08-09T13:59:32.084079Z","title":"Hallucidoctor: Mitigating hallu- cinatory toxicity in visual instruction data","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.084079Z"},"links":{"citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:ec68d69197ddf833ba02df4e0d5d68cf757ba75aa151205d2ff8ab7eb82273a7","observation_id":"2818b6cc-9dd6-48b4-93dc-b590be3d67e2","resolution":{"observed_at":"2026-08-09T13:59:32.084079Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.08739","last_updated":"2024-11-01T22:14:24Z","snapshot_observed_at":"2026-07-06T18:45:01.801741Z","submitted_at":"2024-07-11T17:59:47Z","title":"MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.08739","snapshot_observed_at":"2026-08-09T13:59:32.087633Z","title":"Automated multi-level preference for mllms","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.087633Z"},"links":{"cited_paper":"/paper/2407.08739","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:8b862c07a65e9bf8646f800af3af326a71f0955f4a7cc1639e550017eb4f748d","observation_id":"3d29311d-00d3-49c8-a2df-2333d5253a68","resolution":{"observed_at":"2026-08-09T13:59:32.087633Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.16839","last_updated":"2024-02-06T16:43:31Z","snapshot_observed_at":"2026-08-08T04:17:23.797697Z","submitted_at":"2023-11-28T14:54:37Z","title":"Beyond Hallucinations: Enhancing LVLMs through Hallucination-Aware Direct Preference Optimization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.16839","snapshot_observed_at":"2026-08-09T13:59:32.091465Z","title":"Beyond hallucinations: Enhancing lvlms through hallucination-aware direct preference optimization","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.091465Z"},"links":{"cited_paper":"/paper/2311.16839","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:014254bea612df3575a6d03d9f11cc982e55375c229a1b129f18baa1ac70aff3","observation_id":"c52c45a5-b6ec-4684-b814-9f0ec6370fcf","resolution":{"observed_at":"2026-08-09T13:59:32.091465Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.11411","last_updated":"2024-02-18T00:56:16Z","snapshot_observed_at":"2026-07-06T17:31:41.687799Z","submitted_at":"2024-02-18T00:56:16Z","title":"Aligning Modalities in Vision Large Language Models via Preference Fine-tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.11411","snapshot_observed_at":"2026-08-09T13:59:32.095450Z","title":"Provide a thorough description of the given image","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.095450Z"},"links":{"cited_paper":"/paper/2402.11411","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:30f98496758d7aae7b98ef3a5924e69c0f972d839047be91df3f2e573ed62778","observation_id":"be4c35ef-666a-4b22-8988-6876b949f27b","resolution":{"observed_at":"2026-08-09T13:59:32.095450Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-09T13:59:32.071785Z","title":"Proximal policy optimization algorithms","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.071785Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:2d5a92f2e984acd44727a80c2fe5c2add660ef12e3f48628d6c7605305dcb7f2","observation_id":"7a3907d2-9d6a-42de-96c3-f96a5d82304a","resolution":{"observed_at":"2026-08-09T13:59:32.071785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00253","last_updated":"2024-05-06T01:10:01Z","snapshot_observed_at":"2026-07-06T17:23:26.913214Z","submitted_at":"2024-02-01T00:33:21Z","title":"A Survey on Hallucination in Large Vision-Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.00253","snapshot_observed_at":"2026-08-09T13:59:32.063306Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.063306Z"},"links":{"cited_paper":"/paper/2402.00253","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:9145943e0972f9209d6d473c17078146d727db84cc1a23d6f0bcc578050777ed","observation_id":"f385371f-5a92-4cc4-8885-ffb5c3777982","resolution":{"observed_at":"2026-08-09T13:59:32.063306Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.14148","last_updated":"2025-04-21T04:04:53Z","snapshot_observed_at":"2026-08-09T06:03:53.936554Z","submitted_at":"2024-10-18T03:34:32Z","title":"Fine-Grained Verifiers: Preference Modeling as Next-token Prediction in Vision-Language Alignment","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.14148","snapshot_observed_at":"2026-08-09T13:59:32.042006Z","title":"Fine-grained verifiers: Preference modeling as next-token prediction in vision-language alignment","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-09T13:59:32.042006Z"},"links":{"cited_paper":"/paper/2410.14148","citing_paper":"/paper/2502.01943"},"observation_digest":"sha256:0bce73f19ce5be97e222df5ae7fb88daacf9e564d883d72ab400191e2a7388e5","observation_id":"641ebfa0-6ec9-42d1-927a-cfa270b16d45","resolution":{"observed_at":"2026-08-09T13:59:32.042006Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.01943","last_updated":"2025-02-11T03:55:29Z","latest_version":2,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T13:52:27.529038Z","submitted_at":"2025-02-04T02:30:36Z","title":"DAMA: Data- and Model-aware Alignment of Multi-modal LLMs"},"reference_resolution":{"displayed":15,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":15,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":15},"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 15 of 15 outbound references and 2 inbound Pith citation observations for arXiv:2502.01943."}