{"as_of":"2026-08-18T19:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:dbc086ebf985f76d48a091f29815c1e7bf42bf6e8f0c32adf8b85cc550076702","coverage":[{"denominator":84,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":84,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T10:31:49.730633Z","state":"measured"},{"denominator":86,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":86,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+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":"2026-08-15T23:21:13.677943Z","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":"2026-05-13T05:17:18.159042Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.18085","snapshot_observed_at":"2026-08-15T23:21:13.677943Z","title":"K., and Cuzzolin, F","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.04950","last_updated":"2025-06-27T13:25:34Z","snapshot_observed_at":"2026-08-17T17:01:27.667174Z","submitted_at":"2025-05-08T05:10:38Z","title":"Epistemic Artificial Intelligence is Essential for Machine Learning Models to Truly 'Know When They Do Not Know'","version":3},"reference_index":162,"source":"pdf_text","source_observed_at":"2026-08-15T23:21:13.677943Z"},"links":{"cited_paper":"/paper/2504.18085","citing_paper":"/paper/2505.04950"},"observation_digest":"sha256:29e97761e48e03cdc10572ed90af24659db344eb61ef483df440f7ce6554d5fc","observation_id":"f92c8779-ca40-4534-9df7-7166a838f5d0","resolution":{"observed_at":"2026-08-15T23:21:13.677943Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"cited_work":{"arxiv_id":"2504.18085","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.18085","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Random-set large language models.arXiv preprint arXiv:2504.18085","venue":null,"work_id":"6d44c24e-6658-474f-806b-1a6ac16670c3","year":null},"citing_paper":{"arxiv_id":"2605.11987","last_updated":"2026-05-12T11:38:13Z","snapshot_observed_at":"2026-08-12T15:17:34.632078Z","submitted_at":"2026-05-12T11:38:13Z","title":"Random-Set Graph Neural Networks","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-13T05:15:55.175024Z"},"links":{"cited_paper":"/paper/2504.18085","citing_paper":"/paper/2605.11987"},"observation_digest":"sha256:e5acfe111ad61e6d0cc4c36b83b2c1e33adc28ebfac1faffcab6c8bb92fe089a","observation_id":"a1b1469e-2989-4229-b31d-7dbdbe0046a5","resolution":{"observed_at":"2026-05-13T05:17:18.161092Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2504.18085/citation-record","integrity":"/paper/2504.18085/integrity","json":"/paper/2504.18085/citation-record.json","paper":"/paper/2504.18085"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:31:49.402205Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.402205Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:f04a7852eabf20660c8cd2d72b7287a43322b2a23ec0f44082d8f5a6679419af","observation_id":"803e6cd7-ce34-4863-a1a5-686ba079667e","resolution":{"observed_at":"2026-08-16T10:31:49.402205Z","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":"2026-08-16T10:31:49.411617Z","title":"https://www.sbert.net/","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.411617Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:a3ffca68a7f4d877501ab80e7ab7ed3dfc3f86031afdbfd213890aa80497893c","observation_id":"17883381-7bac-41f8-af46-7267f958738d","resolution":{"observed_at":"2026-08-16T10:31:49.411617Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-17T09:58:46.058102Z","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":"2026-08-16T10:31:49.415832Z","title":"L., Almeida, D., Altenschmidt, J., Altman, S., Anadkat, S., et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.415832Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:9cca3d428da25ad557285875bcf70c79aa2f41304949f4fc6d1683100b1d31c9","observation_id":"08c3d1ce-91f4-470a-b88a-814559fb0128","resolution":{"observed_at":"2026-08-16T10:31:49.415832Z","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":"2026-08-16T10:31:49.420058Z","title":"R., Bl \\\"o mer, J., Kuntze, D., and Sohler, C","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.420058Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:6ca3a547da7704666f412a885a2caa436a902478c687fa10988e45ade4aaca46","observation_id":"300896c3-d6f6-471f-8d9a-8ad670924ce4","resolution":{"observed_at":"2026-08-16T10:31:49.420058Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10403","last_updated":"2023-09-13T20:35:45Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-17T17:46:53Z","title":"PaLM 2 Technical Report","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.10403","snapshot_observed_at":"2026-08-16T10:31:49.423754Z","title":"M., Firat, O., Johnson, M., Lepikhin, D., Passos, A., Shakeri, S., Taropa, E., Bailey, P., Chen, Z., et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.423754Z"},"links":{"cited_paper":"/paper/2305.10403","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:ee265ed11d73a781c3d976a92954eb4ce1bf963ce3cd77233cd3d7b5f5a06935","observation_id":"5474295a-f410-49aa-b152-e461bc6f0b46","resolution":{"observed_at":"2026-08-16T10:31:49.423754Z","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":"2026-08-16T10:31:49.427728Z","title":"and Cuzzolin, F","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.427728Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:25afd027edaa4e852ed06012ed873ed83cd9d5a3c13b3c1d69fa0e80fb6b3655","observation_id":"4e11b79f-69e8-4ac5-81b0-3ec5098f5ccd","resolution":{"observed_at":"2026-08-16T10:31:49.427728Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.05862","last_updated":"2022-04-12T15:02:38Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-12T15:02:38Z","title":"Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.05862","snapshot_observed_at":"2026-08-16T10:31:49.432193Z","title":"Training a helpful and harmless assistant with reinforcement learning from human feedback","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.432193Z"},"links":{"cited_paper":"/paper/2204.05862","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:3edcc97345d061f196b4408a1e673542d55ad2584d8c16d50397d8284f91de8c","observation_id":"12c29d0d-8b2c-4cc0-8068-6de08884ac28","resolution":{"observed_at":"2026-08-16T10:31:49.432193Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.12264","last_updated":"2025-05-20T19:59:52Z","snapshot_observed_at":"2026-08-16T14:17:16.557466Z","submitted_at":"2024-02-19T16:26:00Z","title":"Uncertainty quantification in fine-tuned LLMs using LoRA ensembles","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.12264","snapshot_observed_at":"2026-08-16T10:31:49.435715Z","title":"and Linander, H","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.435715Z"},"links":{"cited_paper":"/paper/2402.12264","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:2bab17e02551079599905fe81f89bf6fe37395bdca06733b8bd766de6e2aa784","observation_id":"0722cc8b-e0d4-476e-9034-77cdcee796c8","resolution":{"observed_at":"2026-08-16T10:31:49.435715Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.04624","last_updated":"2023-08-08T23:30:20Z","snapshot_observed_at":"2026-08-16T15:09:49.615027Z","submitted_at":"2023-08-08T23:30:20Z","title":"Benchmarking LLM powered Chatbots: Methods and Metrics","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.04624","snapshot_observed_at":"2026-08-16T10:31:49.439924Z","title":"Benchmarking llm powered chatbots: methods and metrics","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.439924Z"},"links":{"cited_paper":"/paper/2308.04624","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:2d782982dd735cc2ec0356ba4088bd3dec0631e311c3d7344df6ddea8ac37706","observation_id":"c84ef91f-04a1-432b-8215-a76615f1af0e","resolution":{"observed_at":"2026-08-16T10:31:49.439924Z","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":"2026-08-16T10:31:49.443383Z","title":"Weight uncertainty in neural network","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.443383Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:324843e697a52278acbb3c12848debf0d56093181e136f0fcca61637426ffa94","observation_id":"b2d6b323-0682-4f84-b87e-2e8f1ffd7563","resolution":{"observed_at":"2026-08-16T10:31:49.443383Z","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":"2026-08-16T10:31:50.610146Z","title":null,"venue":null,"work_id":"02ca7d61-97a0-4f0e-ad2a-7aa8874aae79","year":1995},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.446171Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:ce8e9f65bef72caafa0d931113ddc19c483f933c55a987d8a775835e2f1ec089","observation_id":"9796c20c-ae6d-4342-9ca2-2d7e3d14867f","resolution":{"observed_at":"2026-08-16T10:31:50.614478Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.596363Z","title":"and Klir, G","venue":null,"work_id":"e5763561-efd9-4db8-b886-a0c93ef6432b","year":2008},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.449931Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:ce0b42698cbd62cc6190eed8601f20123ca279d909f884e7b921ce1a745fb92b","observation_id":"ed3148b2-ded3-4e9f-b068-47ccb4ce3f26","resolution":{"observed_at":"2026-08-16T10:31:50.601068Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.00957","last_updated":"2024-10-23T15:40:23Z","snapshot_observed_at":"2026-08-16T14:22:22.143426Z","submitted_at":"2024-02-01T19:25:58Z","title":"Credal Learning Theory","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.00957","snapshot_observed_at":"2026-08-16T10:31:49.452729Z","title":"Credal learning theory","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.452729Z"},"links":{"cited_paper":"/paper/2402.00957","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:953a66847db259fcbe8803c09e807671c1663b6f6eb9a1e231e9c80cd509ce4d","observation_id":"a93fe2c1-ce69-46fe-9173-04efe5b993a5","resolution":{"observed_at":"2026-08-16T10:31:49.452729Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03744","last_updated":"2024-10-21T04:10:50Z","snapshot_observed_at":"2026-08-16T14:21:07.996112Z","submitted_at":"2024-02-06T06:23:12Z","title":"INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.03744","snapshot_observed_at":"2026-08-16T10:31:49.456549Z","title":"Inside: Llms' internal states retain the power of hallucination detection","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.456549Z"},"links":{"cited_paper":"/paper/2402.03744","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:cc2fa8cb1d81e42c6c6b21943ce5cab843a265253d337480d67d5328eeffe649","observation_id":"f56ab1f7-f6e6-4a6b-b9c5-3ec34c421ee3","resolution":{"observed_at":"2026-08-16T10:31:49.456549Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-14T02:43:01.480086Z","submitted_at":"2021-10-27T04:49:45Z","title":"Training Verifiers to Solve Math Word Problems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.14168","snapshot_observed_at":"2026-08-16T10:31:49.460680Z","title":"Training verifiers to solve math word problems","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.460680Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:699a150ac1d66e0010f0d0208dc2755becedf2d1300f1150a13ea8859bdc9649","observation_id":"930498c7-6df2-412a-9b15-ac38a7b94ea0","resolution":{"observed_at":"2026-08-16T10:31:49.460680Z","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":"2026-08-16T10:31:50.582512Z","title":"On the credal structure of consistent probabilities","venue":null,"work_id":"362a1d0c-a2ac-4670-8648-4dc6a437d874","year":2008},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.463622Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:8be2ff510be67a78f760a8e893e3644e8320361ec950a641475cd341a9467450","observation_id":"a3a05ef9-1e62-49cc-8710-a4af8b32f03b","resolution":{"observed_at":"2026-08-16T10:31:50.586865Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.569419Z","title":"Complexes of outer consonant approximations","venue":null,"work_id":"d5ba2077-9f06-46d0-978e-9305f22f68ac","year":2009},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.466348Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:a63a5d576568eed94ef194b33f55b6bdc32807758d63d88b91aa577e2a0bb2f9","observation_id":"8c0b1989-70a4-4dd5-8a45-69211c97bc51","resolution":{"observed_at":"2026-08-16T10:31:50.573761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.555313Z","title":"Credal semantics of Bayesian transformations in terms of probability intervals","venue":null,"work_id":"c4c71029-fad8-410f-84ab-98c60f9f1b20","year":2010},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.469163Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:ab2b242b142b76aff2ace12248abea0b9a5325b11a39458ba4602b564d11f2ee","observation_id":"217a660f-fb7d-4bd7-b7cf-16404388fb07","resolution":{"observed_at":"2026-08-16T10:31:50.560460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.542531Z","title":"Geometric conditioning of belief functions","venue":null,"work_id":"a848dc11-9553-4742-9677-9d9029983a98","year":2010},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.471989Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:332670e76dee32ef1317b151cd432b805a451c078bc4e72c370baca1df825ed9","observation_id":"5014ac39-9818-4142-816e-323021deab03","resolution":{"observed_at":"2026-08-16T10:31:50.546892Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.531022Z","title":"The geometry of consonant belief functions: simplicial complexes of necessity measures","venue":null,"work_id":"0a5fc4ce-a356-43c0-89d3-57745b0913e6","year":2010},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.474912Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:87159dd0cf14034772e702a9ed8a4796e465bc445ca55c21b43cef7ac1d187c6","observation_id":"89c6c527-6e8c-44b0-a38d-60a29c822f52","resolution":{"observed_at":"2026-08-16T10:31:50.535441Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.519372Z","title":"Three alternative combinatorial formulations of the theory of evidence","venue":null,"work_id":"69a99165-437a-45d9-a069-02a4cb529fb6","year":2010},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.478356Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:365d331a16b74a16f132d3d29dd8c681501cae6dcf9da778627ec8892d65865e","observation_id":"7ace9947-ba5b-47a9-a91a-0700fc0add0a","resolution":{"observed_at":"2026-08-16T10:31:50.523067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.507491Z","title":"On consistent approximations of belief functions in the mass space","venue":null,"work_id":"ae945d4f-a9ad-477e-bda7-6c5706965692","year":2011},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.481571Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:f2fbad71532c327bd6e7a072470729380d8bcd8dbaceb74c696da71568e11e84","observation_id":"812fa2b8-9943-43f5-a6a2-0e6d71408d97","resolution":{"observed_at":"2026-08-16T10:31:50.511918Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.493475Z","title":"Geometric conditional belief functions in the belief space","venue":null,"work_id":"6972021b-08c3-4e90-96a6-7344d4fefe63","year":2011},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.484371Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:55ca318e6276a307f030c3d0ddeb289df1624ee39c85bfca67be8999a40b27e0","observation_id":"ec85916d-bdb9-40c6-b029-c36fde08ed88","resolution":{"observed_at":"2026-08-16T10:31:50.498128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.481197Z","title":"Lp consonant approximations of belief functions","venue":null,"work_id":"7812dd46-f83e-4e5d-9400-cc732ceebdce","year":2013},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.487029Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:90b446f6142a1bc6fbb588cbd110138d1ba0393c6cc8652f438cb6b04edfa9af","observation_id":"57113d52-1328-4b91-a344-cf0901743029","resolution":{"observed_at":"2026-08-16T10:31:50.485599Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.467709Z","title":"Belief functions: theory and applications","venue":null,"work_id":"e27544fb-8c9c-45b4-9da8-6b2e5eca9352","year":2014},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.490436Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:4a78c4e83a0b1bf85956be58fe0fb652a9adecd7343fb41059248c09ecb09f1d","observation_id":"c24a668f-6383-474f-960b-168e0c8aae97","resolution":{"observed_at":"2026-08-16T10:31:50.472361Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.454052Z","title":"Generalised max entropy classifiers","venue":null,"work_id":"7055ea06-e964-4f85-b4e3-59bc7bd2a709","year":2018},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.493355Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:2c81b69daafc300dc5b35d84a9befa9d98c917faef4cf466c1a49d2f6a7ac904","observation_id":"56663488-8027-4327-9014-af5de2794f90","resolution":{"observed_at":"2026-08-16T10:31:50.459125Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1810.10341","last_updated":"2018-10-18T14:00:48Z","snapshot_observed_at":"2026-08-14T18:12:39.918746Z","submitted_at":"2018-10-18T14:00:48Z","title":"Visions of a generalized probability theory","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1810.10341","snapshot_observed_at":"2026-08-16T10:31:49.496982Z","title":"Visions of a generalized probability theory","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.496982Z"},"links":{"cited_paper":"/paper/1810.10341","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:4747c1df9960453cde33010a205bad3cc965feba95cd1d7baa9d96f87cad5d9e","observation_id":"0541fb14-e14a-4103-be63-61dac9e41ee6","resolution":{"observed_at":"2026-08-16T10:31:49.496982Z","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":"2026-08-16T10:31:50.439743Z","title":"The Geometry of Uncertainty: The Geometry of Imprecise Probabilities","venue":null,"work_id":"f4e78d24-e206-4cf3-906f-6874332e0b4d","year":2020},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.500998Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:e00c8c06aaa4973811ed5c43b0001ada699738b7ae84c1c1dc6bde20381ba1e0","observation_id":"fe1bcbd8-38c8-4f3b-81f1-a3dc2e46c7c3","resolution":{"observed_at":"2026-08-16T10:31:50.444747Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.09435","last_updated":"2023-12-19T18:17:59Z","snapshot_observed_at":"2026-08-18T12:36:02.403103Z","submitted_at":"2023-12-19T18:17:59Z","title":"Reasoning with random sets: An agenda for the future","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.09435","snapshot_observed_at":"2026-08-16T10:31:49.504317Z","title":"Reasoning with random sets: An agenda for the future","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.504317Z"},"links":{"cited_paper":"/paper/2401.09435","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:ba5c4951addafa4ae06681bd5ba0799f44de80307c101b2db88d7276cca3d350","observation_id":"b17f97c4-2c96-4d55-9a1e-620220cd7545","resolution":{"observed_at":"2026-08-16T10:31:49.504317Z","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":"2026-08-16T10:31:50.426011Z","title":"Uncertainty measures: A critical survey","venue":null,"work_id":"eed27d46-de45-4e58-8db4-d732a73e41dc","year":2024},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.508367Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:b9634afc9e98636df9397e091120e494bea9d420adc7a13a22bfbad00fa3b78b","observation_id":"8c8d848b-c9b0-413f-a6b1-03401456446e","resolution":{"observed_at":"2026-08-16T10:31:50.430196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.412103Z","title":"and Frezza, R","venue":null,"work_id":"8d310e55-5162-4fa8-9ad7-af0fc36f62f5","year":2000},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.511954Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:0c1dd85ec6633316e2a26e1a274f13f155cde7dbfa0469d133195e943cc1ac5d","observation_id":"a8941d93-abd8-4ff6-8c6e-931491cd46aa","resolution":{"observed_at":"2026-08-16T10:31:50.416700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.397938Z","title":"and Frezza, R","venue":null,"work_id":"84f8e365-d128-48e0-9f2b-9ee4798495b3","year":2001},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.515487Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:c93bc3817d74805c6162eeeade2152597b4e4ee928b990f98c86ae08f764d3c3","observation_id":"4eb67b19-e945-422f-ae31-671154645dd8","resolution":{"observed_at":"2026-08-16T10:31:50.402779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.384734Z","title":null,"venue":null,"work_id":"35cdea6f-d1e8-4220-b065-b6cb66eb40b6","year":2008},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.519375Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:a7d64cecc3ddec9d72a129b1529ace46b764c2adf38c7380393ac1175c9ca891","observation_id":"73822193-ddc9-4dd6-9c90-d033668b2366","resolution":{"observed_at":"2026-08-16T10:31:50.389750Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.372488Z","title":"Distributed combination of belief functions","venue":null,"work_id":"7d0d6eb8-9948-4993-9a4f-3d2e27464281","year":2021},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.523216Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:76c274f6e095642ad88e49a1c39b9055004cbafcac22ae8239e17856c068dcca","observation_id":"b3964c3b-424c-4cb4-a80a-840f5c114e97","resolution":{"observed_at":"2026-08-16T10:31:50.376802Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:49.526740Z","title":"Detecting hallucinations in large language models using semantic entropy","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.526740Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:9f84a9eec22bb3fe8ffd06952ab536c10599e06fcd670cfbbc8999fadc5ad868","observation_id":"d67ca968-3d3a-46b9-b512-1bbbdd982779","resolution":{"observed_at":"2026-08-16T10:31:49.526740Z","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":"2026-08-16T10:31:50.355779Z","title":"and Ghahramani, Z","venue":null,"work_id":"4a04e425-010d-4d76-8429-faf04ada1549","year":2016},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.530556Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:5bf25e12fb662a5bfee518a467868a39610ec2a9b6993a449f7db3691fb9870e","observation_id":"c723f5bc-baa1-48e1-9990-8c41ca9c8a01","resolution":{"observed_at":"2026-08-16T10:31:50.359756Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.344538Z","title":"C., Khan, S., Cuzzolin, F., and Lukasiewicz, T","venue":null,"work_id":"3ca0badb-7a53-4fb3-afb3-3b2d6679ca99","year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.534473Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:832bb634c10bad23772cc7fe75b416f4f887eac8416e80def629687cedf65c42","observation_id":"56bac10c-312c-498b-a44e-94ffa5bd7106","resolution":{"observed_at":"2026-08-16T10:31:50.348523Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.06352","last_updated":"2022-03-24T19:35:39Z","snapshot_observed_at":"2026-08-16T17:56:51.540416Z","submitted_at":"2021-09-13T22:46:03Z","title":"Uncertainty-Aware Machine Translation Evaluation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.06352","snapshot_observed_at":"2026-08-16T10:31:49.538454Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.538454Z"},"links":{"cited_paper":"/paper/2109.06352","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:184e0eed970a054d103e2cb61a0926349d990b5e049a80a2d41d687bf0a3542f","observation_id":"f605332f-b9c7-41e9-aab2-867b772f5ff4","resolution":{"observed_at":"2026-08-16T10:31:49.538454Z","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":"2026-08-16T10:31:50.332779Z","title":"and Cuzzolin, F","venue":null,"work_id":"71ba6b77-de6d-4786-921f-45cfc0a68638","year":2017},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.542467Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:b6c216ab79fdc9f342c8d35de75eefc8e795a6cbcf03b5d31f02ef3769917e32","observation_id":"1a6ebd79-8e83-4303-9197-0ba5f8023ec3","resolution":{"observed_at":"2026-08-16T10:31:50.337211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.319694Z","title":"trlx: A framework for large scale reinforcement learning from human feedback","venue":null,"work_id":"3ecf1731-22ca-48ce-9955-384047c4d927","year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.546086Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:913d2cd524e3300cbac0b8691d6e1cfc22f67cd066aa32d048b8da1c2b184e57","observation_id":"bead3bee-4a43-4257-9800-efa79e8782a4","resolution":{"observed_at":"2026-08-16T10:31:50.324339Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-17T18:04:53.578114Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-16T10:31:49.550116Z","title":"J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.550116Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:da26a71d040a02ec6bc8621feceb40827e20380a04c005f44a23b2d30ae2ee89","observation_id":"461ae896-22b2-4108-b123-6e3916c8f941","resolution":{"observed_at":"2026-08-16T10:31:49.550116Z","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":"2026-08-16T10:31:49.554752Z","title":"and Waegeman, W","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.554752Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:53fce896855f5ad89cb2fd8c89da6579a0a306cc710de75192b29555a6247836","observation_id":"0755c706-1a01-47a1-9ad7-9d78adf0a760","resolution":{"observed_at":"2026-08-16T10:31:49.554752Z","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":"2026-08-16T10:31:50.299731Z","title":null,"venue":null,"work_id":"3200e764-f84f-4fbf-a79b-64b33837be55","year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.558718Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:8a00fe4d44dfb6a126ab7621f76cb2be733f813ae3bb6d6f4ad968e74acfcc81","observation_id":"a84c267d-0b10-45a1-988e-90fce96b609a","resolution":{"observed_at":"2026-08-16T10:31:50.304852Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06825","last_updated":"2023-10-10T17:54:58Z","snapshot_observed_at":"2026-08-17T20:30:34.016254Z","submitted_at":"2023-10-10T17:54:58Z","title":"Mistral 7B","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06825","snapshot_observed_at":"2026-08-16T10:31:49.562498Z","title":"Q., Sablayrolles, A., Mensch, A., Bamford, C., Chaplot, D","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.562498Z"},"links":{"cited_paper":"/paper/2310.06825","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:a9770a1f6dfce6d866bbf82d5e1061708f54f4e1fae9c1fa6da0d3f43c6459b4","observation_id":"690cf610-2bdf-4ccf-bb9b-4913b5cd6572","resolution":{"observed_at":"2026-08-16T10:31:49.562498Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2207.05221","last_updated":"2022-11-21T16:38:35Z","snapshot_observed_at":"2026-08-14T05:42:29.067319Z","submitted_at":"2022-07-11T22:59:39Z","title":"Language Models (Mostly) Know What They Know","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2207.05221","snapshot_observed_at":"2026-08-16T10:31:49.566497Z","title":"Language models (mostly) know what they know","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.566497Z"},"links":{"cited_paper":"/paper/2207.05221","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:c2b4c6bd8e5a5363f8831bedd0b2aa211d92a10c173fa35b20b45634fa596089","observation_id":"ef9c34e6-07bb-4826-ac4d-81ad16b506ef","resolution":{"observed_at":"2026-08-16T10:31:49.566497Z","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":"2026-08-16T10:31:49.570290Z","title":"and Gal, Y","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.570290Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:e60c5ffd491c8425dbc55434fe57c2bd5e23933e76a4860cf616c55eae111620","observation_id":"ad8b7678-82e4-441e-b82b-27a8ec7d533f","resolution":{"observed_at":"2026-08-16T10:31:49.570290Z","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":"2026-08-16T10:31:50.282168Z","title":null,"venue":null,"work_id":"c3cbed6a-6f0f-4631-90b0-739ef82b86c1","year":1965},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.573377Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:53a176f8cdb097cf28a598d22f0b099303c5fd5ada445d882b1dbe24ba15f18a","observation_id":"fd6b4b7d-d209-4c3a-a4a0-5ef235696b34","resolution":{"observed_at":"2026-08-16T10:31:50.286290Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.09664","last_updated":"2023-04-15T12:55:45Z","snapshot_observed_at":"2026-07-06T14:53:27.667483Z","submitted_at":"2023-02-19T20:10:07Z","title":"Semantic Uncertainty: Linguistic Invariances for Uncertainty Estimation in Natural Language Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.09664","snapshot_observed_at":"2026-08-16T10:31:49.577592Z","title":"Semantic uncertainty: Linguistic invariances for uncertainty estimation in natural language generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.577592Z"},"links":{"cited_paper":"/paper/2302.09664","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:75758d63f30e3582096f005fbeee103143ed782461266e8eb0e4fe4aa18396ca","observation_id":"31b71195-9748-40a9-af00-d8529e4c82d0","resolution":{"observed_at":"2026-08-16T10:31:49.577592Z","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":"2026-08-16T10:31:50.269397Z","title":"The enterprise of knowledge: An essay on knowledge, credal probability, and chance","venue":null,"work_id":"c7551f9e-c113-4334-80fa-95180fa0a6ca","year":1980},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.581834Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:e64da93e23b1af1ed4303cc190ea0cc0fbee87f0acfe75ac3768202ba9c9d511","observation_id":"7787870b-288d-4c54-9c5a-523d0ad2df50","resolution":{"observed_at":"2026-08-16T10:31:50.273836Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:49.585445Z","title":"Solving quantitative reasoning problems with language models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.585445Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:8f55e682fb994dbe10b481040d2ecff7703919469912920b2f8bef25385df69e","observation_id":"76b4830f-4006-4ecf-a4c2-dc21d3296f1a","resolution":{"observed_at":"2026-08-16T10:31:49.585445Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2205.14334","last_updated":"2022-06-13T05:04:53Z","snapshot_observed_at":"2026-08-09T23:45:38.167954Z","submitted_at":"2022-05-28T05:02:31Z","title":"Teaching Models to Express Their Uncertainty in Words","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2205.14334","snapshot_observed_at":"2026-08-16T10:31:49.589327Z","title":"Teaching models to express their uncertainty in words","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.589327Z"},"links":{"cited_paper":"/paper/2205.14334","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:28f061760f2066fa9bfb11ebc60dfcb0d0fb77b3465b6fc832e09f33631cf102","observation_id":"25d06172-a773-4762-831b-ab70f5952dfb","resolution":{"observed_at":"2026-08-16T10:31:49.589327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.05772","last_updated":"2025-02-14T20:42:16Z","snapshot_observed_at":"2026-08-18T18:01:38.948808Z","submitted_at":"2023-07-11T20:00:35Z","title":"Random-Set Neural Networks (RS-NN)","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.05772","snapshot_observed_at":"2026-08-16T10:31:49.593153Z","title":"K., Mubashar, M., Wang, K., Shariatmadar, K., and Cuzzolin, F","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.593153Z"},"links":{"cited_paper":"/paper/2307.05772","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:d05bba48ed84e822bf7b7b0cba36361a30d68a7885f5635693a9beddde4b68ca","observation_id":"2d3fe1bc-5196-4414-9265-f98b43def211","resolution":{"observed_at":"2026-08-16T10:31:49.593153Z","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":"2026-08-16T10:31:50.251642Z","title":"K., Mubashar, M., Wang, K., Shariatmadar, K., and Cuzzolin, F","venue":null,"work_id":"ca5076d3-470e-4797-8ff1-07173361e2e8","year":2025},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.597880Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:581fe3b1b9cbbdf94d3fb97f8a326d9f475fe19d2fa177c2a5e48b83b0038ecb","observation_id":"90032560-c661-4c0a-99fc-80c693acc2a9","resolution":{"observed_at":"2026-08-16T10:31:50.256115Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.239000Z","title":"Random sets and integral geometry","venue":null,"work_id":"37eed647-03cd-42fd-850e-4ef7b15be7bb","year":1975},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.602349Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:6bbcece09882e8e8c95a89aa8c7e9790ea2c1dfdbcbc061791b9e620d331f7db","observation_id":"ae8787fa-95a8-4db4-b15d-76ea1e71d313","resolution":{"observed_at":"2026-08-16T10:31:50.243535Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.00661","last_updated":"2020-05-02T00:09:16Z","snapshot_observed_at":"2026-08-18T19:33:38.559641Z","submitted_at":"2020-05-02T00:09:16Z","title":"On Faithfulness and Factuality in Abstractive Summarization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.00661","snapshot_observed_at":"2026-08-16T10:31:49.606343Z","title":"On faithfulness and factuality in abstractive summarization","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.606343Z"},"links":{"cited_paper":"/paper/2005.00661","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:76e1f9adde5cdf4f5f274d0c8a8f9f621d6c666c9a83b7cc6508bdc66eee0875","observation_id":"7348c3a1-b98b-4f18-b471-ab855cfcecdd","resolution":{"observed_at":"2026-08-16T10:31:49.606343Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.14983","last_updated":"2022-06-26T22:11:23Z","snapshot_observed_at":"2026-08-18T14:17:57.183891Z","submitted_at":"2020-12-30T00:12:36Z","title":"Reducing conversational agents' overconfidence through linguistic calibration","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.14983","snapshot_observed_at":"2026-08-16T10:31:49.611654Z","title":"J., Szlam, A., Boureau, Y.-L., and Dinan, E","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.611654Z"},"links":{"cited_paper":"/paper/2012.14983","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:476ea52703aa7191bc6d37bf5ad412b121927de4008cc91c4ac914a9a8dd9dab","observation_id":"323c904a-c8fa-40d6-afd8-5e22b819794e","resolution":{"observed_at":"2026-08-16T10:31:49.611654Z","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":"2026-08-16T10:31:49.616168Z","title":"Can a suit of armor conduct electricity? a new dataset for open book question answering","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.616168Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:3145b6be1f480bf950716e36f2ea2f24957c49216830d9d6816d1332d10a8463","observation_id":"afd106fc-7cc9-4303-b664-41391d0f8887","resolution":{"observed_at":"2026-08-16T10:31:49.616168Z","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":"2026-08-16T10:31:50.221019Z","title":"Random sets and random functions","venue":null,"work_id":"1df5692d-b8e4-4118-b52a-402f8df2a5cd","year":2017},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.621380Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:78a159ea7a5adf88a9fb2bdb0111fc3b575e162d169b2ae5d3db713a8f8e8b21","observation_id":"09d4f75d-b79e-43ff-bc01-b953b85ca6c4","resolution":{"observed_at":"2026-08-16T10:31:50.225318Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.208445Z","title":null,"venue":null,"work_id":"fa6e7716-4396-404b-89b6-e7f1bb4f4afc","year":2005},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.625078Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:01de5d8d7e56a5889c5a4a7a74062e35edbc710c746aa29294e19b3e5047820c","observation_id":"fb433943-313f-44d2-8e51-096f1a89181e","resolution":{"observed_at":"2026-08-16T10:31:50.212913Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1109.2378","last_updated":"2011-09-12T05:49:11Z","snapshot_observed_at":"2026-08-15T21:00:50.761660Z","submitted_at":"2011-09-12T05:49:11Z","title":"Modern hierarchical, agglomerative clustering algorithms","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1109.2378","snapshot_observed_at":"2026-08-16T10:31:49.630058Z","title":"Modern hierarchical, agglomerative clustering algorithms","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.630058Z"},"links":{"cited_paper":"/paper/1109.2378","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:89cad24a4d72a789ca2ee3fcebaa9903a0bfc308931483c835c92cf5fb692f78","observation_id":"187e0872-6710-4d99-9b08-3224d03aec85","resolution":{"observed_at":"2026-08-16T10:31:49.630058Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1808.08745","last_updated":"2018-08-27T09:08:18Z","snapshot_observed_at":"2026-08-14T18:36:49.421687Z","submitted_at":"2018-08-27T09:08:18Z","title":"Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.08745","snapshot_observed_at":"2026-08-16T10:31:49.634318Z","title":"B., and Lapata, M","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.634318Z"},"links":{"cited_paper":"/paper/1808.08745","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:890841b82673fdb3e0255ec4743a1c048b9799e6813dbc8865587be57d3af488","observation_id":"75f6ec2b-0ab2-4196-b30e-64f982da8d98","resolution":{"observed_at":"2026-08-16T10:31:49.634318Z","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":"2026-08-16T10:31:50.196930Z","title":null,"venue":null,"work_id":"aa79a89c-6929-44cb-8f50-cd7e4d516c6d","year":1978},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.638543Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:a796d277be39d91eac4c451b51f851a581fd98a13da5534553a0451df6d36695","observation_id":"9f9747df-4cd3-4403-830d-af7eceb44e41","resolution":{"observed_at":"2026-08-16T10:31:50.201277Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2211.01568","last_updated":"2023-05-10T21:32:21Z","snapshot_observed_at":"2026-08-16T16:18:58.576785Z","submitted_at":"2022-11-03T03:24:46Z","title":"Fine-Tuning Language Models via Epistemic Neural Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.01568","snapshot_observed_at":"2026-08-16T10:31:49.642330Z","title":"M., Van Roy, B., McAleese, N., Aslanides, J., and Irving, G","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.642330Z"},"links":{"cited_paper":"/paper/2211.01568","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:02ed13c323d2d2ce286be0169124e31ddd4120755550f897392c5ccb08dfea68","observation_id":"6a40973f-2b54-4348-a648-22555657e211","resolution":{"observed_at":"2026-08-16T10:31:49.642330Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.13213","last_updated":"2025-08-07T01:33:12Z","snapshot_observed_at":"2026-08-16T14:16:51.725018Z","submitted_at":"2024-02-20T18:24:47Z","title":"Probabilities of Chat LLMs Are Miscalibrated but Still Predict Correctness on Multiple-Choice Q&A","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.13213","snapshot_observed_at":"2026-08-16T10:31:49.646760Z","title":"Softmax probabilities (mostly) predict large language model correctness on multiple-choice q&a","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.646760Z"},"links":{"cited_paper":"/paper/2402.13213","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:d59672470b7d2f32d38efa59e1b8a82ec288580f68bf50b2e1029667dada7470","observation_id":"e1c54e9e-7f57-4eb7-a829-f1a5b5b07179","resolution":{"observed_at":"2026-08-16T10:31:49.646760Z","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":"2026-08-16T10:31:49.651590Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.651590Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:53ce105cce1d1d09d7d858bd72d7be5a0d5afd642e4bea0ea072aff469247b8f","observation_id":"84815a39-4c16-4378-a4b9-1c4a5e349018","resolution":{"observed_at":"2026-08-16T10:31:49.651590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.12950","last_updated":"2024-01-31T19:47:26Z","snapshot_observed_at":"2026-08-18T03:59:39.242039Z","submitted_at":"2023-08-24T17:39:13Z","title":"Code Llama: Open Foundation Models for Code","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.12950","snapshot_observed_at":"2026-08-16T10:31:49.655470Z","title":"E., Adi, Y., Liu, J., Sauvestre, R., Remez, T., et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.655470Z"},"links":{"cited_paper":"/paper/2308.12950","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:7d2c89069b5cbcd97212e57cbf0ad030d107fb908335d73485640bd33a8118b0","observation_id":"5594b84e-da93-4e83-a7fd-53b4e7008bb5","resolution":{"observed_at":"2026-08-16T10:31:49.655470Z","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":"2026-08-16T10:31:50.184064Z","title":"Is the volume of a credal set a good measure for epistemic uncertainty? In Uncertainty in Artificial Intelligence, pp.\\ 1795--1804","venue":null,"work_id":"b0127867-53b1-4bf7-b29c-712c524a8900","year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.659798Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:e4085624c425b237e6457f001702715902eb282fa99697f8cf207f46392ec7d3","observation_id":"5b902e62-91e6-4e70-9bbe-10d33f45b689","resolution":{"observed_at":"2026-08-16T10:31:50.188445Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.171706Z","title":"A mathematical theory of evidence, volume 42","venue":null,"work_id":"e0a530c6-7aca-4d1a-9ddd-6c79dc8dd956","year":1976},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.663989Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:c87ba3af032492b27d661c3c0df9f3bdf4db470ef0e79aa65afc5c30cd812748","observation_id":"cccd9254-3cb6-4889-b976-31667b58fa11","resolution":{"observed_at":"2026-08-16T10:31:50.175836Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.157293Z","title":"A theory of statistical evidence","venue":null,"work_id":"8201f22e-43ef-4dfa-b10f-e1089435c87d","year":1976},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.668439Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:d9dd3b999ed00959537923beab900561aac38eb18d3efb47fe803880cf4ca9bd","observation_id":"42a9d1ee-f313-4f94-ab94-56919ee7dbee","resolution":{"observed_at":"2026-08-16T10:31:50.161837Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:49.672543Z","title":"Decision making in the tbm: the necessity of the pignistic transformation","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.672543Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:33f7f387cc57e9a01ffa995b8fa7a0197917a5335cc00a809b95220da41cfedb","observation_id":"77e6c16c-50ff-46a4-bdd1-4d7f1d82e78b","resolution":{"observed_at":"2026-08-16T10:31:49.672543Z","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":"2026-08-16T10:31:50.143253Z","title":"Decision making in the TBM: the necessity of the pignistic transformation","venue":null,"work_id":"e91b08c5-96c4-494e-8331-4b0142818708","year":2005},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.677184Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:39b2107a6fa9e852975da73e339d33486ae8947b58c4e219e9f6bfbf868a9432","observation_id":"18f0ac3e-8d5d-4df8-bf4a-ddd9155902b9","resolution":{"observed_at":"2026-08-16T10:31:50.148336Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.132162Z","title":"and Kennes, R","venue":null,"work_id":"5c7aaeae-7210-4bb8-a9a6-369574d13d08","year":1994},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.681761Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:3f4f11117e016ad24e481ee8e16b006dab7edb7852ad84f8b16d2942f8448292","observation_id":"47e9f218-3ae9-4845-bcac-c3acafb3d4f7","resolution":{"observed_at":"2026-08-16T10:31:50.136071Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-16T10:31:49.686589Z","title":"Llama 2: Open foundation and fine-tuned chat models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.686589Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:8ba8bfcbad7fc22c39298b58e37cbb5dbb5e05ee39116193adf72fb0dbe9e721","observation_id":"aa039014-e081-496d-94e2-930f19ff79c6","resolution":{"observed_at":"2026-08-16T10:31:49.686589Z","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":"2026-08-16T10:31:50.121048Z","title":"Credal deep ensembles for uncertainty quantification","venue":null,"work_id":"2d469a13-9cba-4803-b074-3ea411973650","year":2024},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.691860Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:0f16e07f0544d8b4703d32992db1bcf4efc9fa724ac48fd8dc80a338a47e4a81","observation_id":"bed967cf-7939-41b6-a024-d2eb4ea617c9","resolution":{"observed_at":"2026-08-16T10:31:50.125015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.108297Z","title":"K., Cuzzolin, F., Moens, D., and Hallez, H","venue":null,"work_id":"dd792cf3-1625-47e8-8344-f04b8ca738f3","year":2025},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.696071Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:b5f55f15a7d75f7a443b52113a9ef8cfe8b44b7ebfa46c92da5361247da59e8e","observation_id":"e02e2e49-3d22-405f-a191-e35215e6fd20","resolution":{"observed_at":"2026-08-16T10:31:50.112033Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.095248Z","title":"Uncertainty estimation and reduction of pre-trained models for text regression","venue":null,"work_id":"21541181-df9d-46a7-8ae9-b61b6f7fe7f8","year":2022},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.700377Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:bbebb18d1095b0f1388935a38ce17ed29eb60c9833fac0e11d55053ef3c9e0d2","observation_id":"bbd0beb9-7ed1-47a4-a7d9-71763596a8f8","resolution":{"observed_at":"2026-08-16T10:31:50.099699Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.11675","last_updated":"2025-01-27T16:00:59Z","snapshot_observed_at":"2026-08-16T13:42:12.095432Z","submitted_at":"2024-06-17T15:55:38Z","title":"BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.11675","snapshot_observed_at":"2026-08-16T10:31:49.705093Z","title":"Blob: Bayesian low-rank adaptation by backpropagation for large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.705093Z"},"links":{"cited_paper":"/paper/2406.11675","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:7540db8cb1e480b21349e85bd75735413d36af5d990400dee555c613f51c8643","observation_id":"cf6c3e31-2c63-4524-b22b-a566ec5dd741","resolution":{"observed_at":"2026-08-16T10:31:49.705093Z","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":"2026-08-16T10:31:49.708611Z","title":"V., Zhou, D., et al","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.708611Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:1f6ffd0f56f1efd3c1e6f3d3b23766083224c85ae65dba7fa916bd555ed9cb7f","observation_id":"7ae3427f-d7b1-4d63-b41d-215c9aa8eb48","resolution":{"observed_at":"2026-08-16T10:31:49.708611Z","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":"2026-08-16T10:31:49.712494Z","title":null,"venue":null,"work_id":null,"year":1989},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.712494Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:8560df61ecdbb019e283f896cffcecdee685128841f7b8c79e7d6440dc0c0626","observation_id":"1a5faffb-906d-4a84-b453-e7590e578ee6","resolution":{"observed_at":"2026-08-16T10:31:49.712494Z","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":"2026-08-16T10:31:50.070838Z","title":"A brief overview of chatgpt: The history, status quo and potential future development","venue":null,"work_id":"ae14be2e-86a4-48f8-9b84-afcc0b34bf75","year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.716437Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:5818c1d11e4c66d3299125445b42862af261668bbc28633a98d39d2b6250bc74","observation_id":"4ea22c3e-c2c0-48ea-b28c-7b871033cc23","resolution":{"observed_at":"2026-08-16T10:31:50.075159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T10:31:50.058089Z","title":null,"venue":null,"work_id":"740cc213-395b-4607-b1d7-99daefce996e","year":2008},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.719642Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:ea14d1ea13d35b4ff193952bf5a0407171ae75a0988a762e9b5793f39b5753d9","observation_id":"c1f3087c-20cc-4a19-845f-d9bbd6ce3a79","resolution":{"observed_at":"2026-08-16T10:31:50.062786Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.13111","last_updated":"2024-02-05T21:16:52Z","snapshot_observed_at":"2026-08-16T15:05:55.945948Z","submitted_at":"2023-08-24T23:06:21Z","title":"Bayesian Low-rank Adaptation for Large Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.13111","snapshot_observed_at":"2026-08-16T10:31:49.723132Z","title":"X., Robeyns, M., Wang, X., and Aitchison, L","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.723132Z"},"links":{"cited_paper":"/paper/2308.13111","citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:35e5f117fefe5240458a8900a0f19ce32c194b7f97deb725ab24368a781c61fb","observation_id":"80960e21-27a5-4022-bbc3-f6ae9dde5dc2","resolution":{"observed_at":"2026-08-16T10:31:49.723132Z","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":"2026-08-16T10:31:49.726626Z","title":"H., Kolehmainen, J., Shivakumar, P","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.726626Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:ee05749f317a44d60e0f9b42f9a7d02cdf529aac635e01cf32237089c0ddc89a","observation_id":"93246ddc-c573-4cd5-b04c-ea5493b6a199","resolution":{"observed_at":"2026-08-16T10:31:49.726626Z","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":"2026-08-16T10:31:50.037945Z","title":"and Fagiuoli, E","venue":null,"work_id":"f5c315e7-e102-42b0-b19f-22e0d8ce71db","year":2003},"citing_paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models","version":1},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-08-16T10:31:49.730633Z"},"links":{"citing_paper":"/paper/2504.18085"},"observation_digest":"sha256:c6e6b3c4a65837d6b918066c30bb996190d502554d36968e67d48c5af5c48b22","observation_id":"f000f887-1833-4d38-9dcf-bccc674a3e7a","resolution":{"observed_at":"2026-08-16T10:31:50.043223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.18085","last_updated":"2025-04-25T05:25:27Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-16T12:10:44.738506Z","submitted_at":"2025-04-25T05:25:27Z","title":"Random-Set Large Language Models"},"reference_resolution":{"displayed":84,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":49,"verified_exact":0,"verified_fuzzy":35},"total_outbound_references":84},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 84 of 84 outbound references and 2 inbound Pith citation observations for arXiv:2504.18085."}