{"as_of":"2026-08-08T12:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e76210d69d45822b9176842c61755a6400e16b4fdb68722d9fee845d52561f09","coverage":[{"denominator":34,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":34,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:31:57.090248Z","state":"measured"},{"denominator":35,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":35,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T23:13:20.622187Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T23:13:23.801132Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"cited_work":{"arxiv_id":"2506.13681","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.13681","snapshot_observed_at":"2026-08-06T23:13:23.801132Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","venue":"cs.CL","work_id":"1b0c2edb-3efa-428f-9b7a-9022b5eb7a7b","year":2025},"citing_paper":{"arxiv_id":"2506.19882","last_updated":"2025-07-07T02:00:46Z","snapshot_observed_at":"2026-08-07T11:24:36.780605Z","submitted_at":"2025-06-24T02:19:30Z","title":"Position: Machine Learning Conferences Should Establish a \"Refutations and Critiques\" Track","version":3},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-06T23:13:20.622187Z"},"links":{"cited_paper":"/paper/2506.13681","citing_paper":"/paper/2506.19882"},"observation_digest":"sha256:7dbadd3cafcafa3258060d38319b6668dd37ce8e84e477cc674a8645918cdb9d","observation_id":"b699c5cc-096b-4905-afd9-1ec58f34a800","resolution":{"observed_at":"2026-08-06T23:13:23.915811Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2506.13681/citation-record","integrity":"/paper/2506.13681/integrity","json":"/paper/2506.13681/citation-record.json","paper":"/paper/2506.13681"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:31:55.441350Z","title":"A learning algorithm for boltzmann machines","venue":null,"work_id":null,"year":1985},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.441350Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:b77f013ab0a726b9e1a9730964739c77fa9d65f24de9addb917962ba1d7c23aa","observation_id":"e8dcc021-4f6c-4f67-91dc-c33f88444fc4","resolution":{"observed_at":"2026-08-07T00:31:55.441350Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2007.14966","last_updated":"2021-01-14T21:36:02Z","snapshot_observed_at":"2026-07-06T09:42:53.060640Z","submitted_at":"2020-07-29T17:22:26Z","title":"Mirostat: A Neural Text Decoding Algorithm that Directly Controls Perplexity","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.14966","snapshot_observed_at":"2026-08-07T00:31:55.463720Z","title":"Mirostat: A neural text decoding algorithm that directly controls perplexity","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.463720Z"},"links":{"cited_paper":"/paper/2007.14966","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:504c08652ce6aa54ab3987a5246fadd20dde016b4d9fea7eb65e01ee6a21edbf","observation_id":"2a7b3092-29d8-4d1a-9d8a-47ce63def399","resolution":{"observed_at":"2026-08-07T00:31:55.463720Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.14782","last_updated":"2026-05-31T00:04:33Z","snapshot_observed_at":"2026-08-07T18:21:12.072228Z","submitted_at":"2024-05-23T16:50:49Z","title":"Lessons from the Trenches on Reproducible Evaluation of Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.14782","snapshot_observed_at":"2026-08-07T00:31:55.489701Z","title":"Lee, Haonan Li, Charles Lovering, Niklas Muennighoff, Ellie Pavlick, Jason Phang, Aviya Skowron, Samson Tan, Xiangru Tang, Kevin A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.489701Z"},"links":{"cited_paper":"/paper/2405.14782","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:2f2f8593dee82d12a4ef6457949530b5330dd520114f213b9d92614eb5f8eced","observation_id":"ae03c04a-fd84-42c9-a0de-1407915bc635","resolution":{"observed_at":"2026-08-07T00:31:55.489701Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.04132","last_updated":"2024-03-07T01:22:38Z","snapshot_observed_at":"2026-08-02T17:55:33.750637Z","submitted_at":"2024-03-07T01:22:38Z","title":"Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.04132","snapshot_observed_at":"2026-08-07T00:31:55.513078Z","title":"Gonzalez, and Ion Stoica","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.513078Z"},"links":{"cited_paper":"/paper/2403.04132","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:254ab5e766c34c0c8542d3e8f3229849b4da1a53fff9d2fbbe7349af349f746a","observation_id":"3c9e3d06-27a1-4597-a771-bcf490d1e2bd","resolution":{"observed_at":"2026-08-07T00:31:55.513078Z","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":"2026-08-07T00:31:58.139210Z","title":"All that’s ‘human’is not gold: Evaluating human evaluation of generated text","venue":null,"work_id":"1a6d1d89-cb1c-4626-8395-f6bb45d64778","year":2021},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.537274Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:9826c3604293b5696abbf281e4167cf6c85feda3ecec68a8ab2c445446a23349","observation_id":"9b3e1509-4d3a-431d-b48a-814c81cce5b3","resolution":{"observed_at":"2026-08-07T00:31:58.183104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.14168","last_updated":"2021-11-18T00:23:45Z","snapshot_observed_at":"2026-08-07T01:45:38.840969Z","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":"2026-08-07T00:31:55.565400Z","title":"Training verifiers to solve math word problems, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.565400Z"},"links":{"cited_paper":"/paper/2110.14168","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:92746f3dfafd249f469ee022f68357fda530d4347e1deeb1422975109ce2eecb","observation_id":"9dac3f31-58ca-4613-a4ef-147a0fa15ce6","resolution":{"observed_at":"2026-08-07T00:31:55.565400Z","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":"2026-08-07T00:31:55.593366Z","title":"Alpacafarm: A simulation framework for methods that learn from human feedback","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.593366Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:3da27949577595830996d988d218f4563fd3925a46b6a9c85056258141fe2994","observation_id":"cebc7a95-0549-483c-855c-5a9d1e63926f","resolution":{"observed_at":"2026-08-07T00:31:55.593366Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1805.04833","last_updated":"2018-05-13T07:07:08Z","snapshot_observed_at":"2026-07-06T06:38:48.758485Z","submitted_at":"2018-05-13T07:07:08Z","title":"Hierarchical Neural Story Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.04833","snapshot_observed_at":"2026-08-07T00:31:55.619376Z","title":"Hierarchical neural story generation","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.619376Z"},"links":{"cited_paper":"/paper/1805.04833","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:fc33d512203f3299c2daf8311acfbb5536c0fbb45d8197b7a44f4344bcc4844e","observation_id":"f1b2d0a9-8605-4548-b823-3041c1e64597","resolution":{"observed_at":"2026-08-07T00:31:55.619376Z","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":"2026-08-07T00:31:55.637364Z","title":"A framework for few-shot language model evaluation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.637364Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:1d8da737518933516f4c53728784ac53275b48b1b6432658ce31d526765d7df5","observation_id":"f79fa9a3-b52d-4d9c-82f3-8e145a4be9a8","resolution":{"observed_at":"2026-08-07T00:31:55.637364Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-07T00:31:55.669362Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.669362Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:a2cba1f7bd5e3096c1531cc75053eb0bc30e3958b09e756576b29dad0fbf1115","observation_id":"4b9a0148-f519-44b5-ae65-fe3a2859a2e8","resolution":{"observed_at":"2026-08-07T00:31:55.669362Z","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":"2026-08-07T00:31:57.976772Z","title":"Truncation sampling as language model desmoothing","venue":null,"work_id":"bd0f8019-13c2-48e8-b7f8-c5cc36a6c70d","year":2022},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.702401Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:87a14fbfb131f91350340261287d53e6f91dbfebf08ec8e467d8b3d73cea8567","observation_id":"fed55ea1-2044-49be-9455-f1d2eea268bd","resolution":{"observed_at":"2026-08-07T00:31:58.045129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:31:55.748459Z","title":"The curious case of neural text degeneration","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.748459Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:fbf8663d9091440be1d0fe0a4476b69f361fa9559d93f4ce4ea1ed12cd5b10f4","observation_id":"78bfc7e5-da21-453d-ba15-e801554402c9","resolution":{"observed_at":"2026-08-07T00:31:55.748459Z","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":"2026-08-07T00:31:57.850985Z","title":"Twenty years of confusion in human evaluation: Nlg needs evaluation sheets and standardised definitions","venue":null,"work_id":"c55ea220-da6b-4dfc-8367-10ea71b8de3c","year":2020},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.782082Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:6ce7d04128e38e3b7a338233cbc61d0a4d009e1ffe79afd270cc50d8724bf398","observation_id":"d0b60f6a-0eed-4a4f-99de-a18e3c05246f","resolution":{"observed_at":"2026-08-07T00:31:57.899068Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03556","last_updated":"2024-12-19T22:37:45Z","snapshot_observed_at":"2026-07-06T20:01:45.826971Z","submitted_at":"2024-12-04T18:51:32Z","title":"Best-of-N Jailbreaking","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03556","snapshot_observed_at":"2026-08-07T00:31:55.835946Z","title":"Best-of-n jailbreaking, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.835946Z"},"links":{"cited_paper":"/paper/2412.03556","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:8f29e761c750e55abc18d3ec61b00d9c690f4305fe72cc0d4f9b974ca52d5c8d","observation_id":"09d6e90e-bba0-4890-9cb1-187c5f4cdcb6","resolution":{"observed_at":"2026-08-07T00:31:55.835946Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06825","last_updated":"2023-10-10T17:54:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","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":"2026-08-07T00:31:55.879471Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.879471Z"},"links":{"cited_paper":"/paper/2310.06825","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:dc86cc1d9a7fcf224738bb3b3f68352a8149ebdb609e0a75cd4b0df80928b9a3","observation_id":"06acc435-58f0-4929-bef1-202e0f9db2c6","resolution":{"observed_at":"2026-08-07T00:31:55.879471Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2101.06561","last_updated":"2022-11-01T01:00:24Z","snapshot_observed_at":"2026-08-05T22:30:03.856168Z","submitted_at":"2021-01-17T00:40:47Z","title":"GENIE: Toward Reproducible and Standardized Human Evaluation for Text Generation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.06561","snapshot_observed_at":"2026-08-07T00:31:55.913375Z","title":"Smith, and Daniel S","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.913375Z"},"links":{"cited_paper":"/paper/2101.06561","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:12d9809d5942413410edf4e6293e58e3cab9990e893be6ca2b921d5171aae4c9","observation_id":"615b277e-dbe7-4134-9274-7e992d1817d0","resolution":{"observed_at":"2026-08-07T00:31:55.913375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2211.09110","last_updated":"2023-10-01T21:44:23Z","snapshot_observed_at":"2026-08-01T19:14:56.803459Z","submitted_at":"2022-11-16T18:51:34Z","title":"Holistic Evaluation of Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2211.09110","snapshot_observed_at":"2026-08-07T00:31:55.961100Z","title":"Holistic evaluation of language models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:55.961100Z"},"links":{"cited_paper":"/paper/2211.09110","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:c627afc86f3550320d56c9877d4043e3102778bb9ec27d2fd4a7df841c20ad0c","observation_id":"9b4e5a4b-cb9c-4437-9fbb-da517ee04f3b","resolution":{"observed_at":"2026-08-07T00:31:55.961100Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2112.09332","last_updated":"2022-06-01T19:08:11Z","snapshot_observed_at":"2026-08-07T17:14:39.278754Z","submitted_at":"2021-12-17T05:43:43Z","title":"WebGPT: Browser-assisted question-answering with human feedback","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.09332","snapshot_observed_at":"2026-08-07T00:31:56.008652Z","title":"Webgpt: Browser-assisted question-answering with human feedback","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.008652Z"},"links":{"cited_paper":"/paper/2112.09332","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:8f6664bda1a6e5173c73d1a50e9bb854a56de413caff92533ff3ba6eb7643281","observation_id":"33e20b17-c968-485a-bb33-cfa6b64915d5","resolution":{"observed_at":"2026-08-07T00:31:56.008652Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-07T00:31:56.081070Z","title":"Qwen2.5 technical report, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.081070Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:4a4cae18e56fc97044099edc013b7ca194ab8abcbd09e48ca3897638dd44b670","observation_id":"313b3695-ad47-4e79-879f-e56df6c2a21b","resolution":{"observed_at":"2026-08-07T00:31:56.081070Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.12022","last_updated":"2023-11-20T18:57:34Z","snapshot_observed_at":"2026-08-04T22:55:15.345443Z","submitted_at":"2023-11-20T18:57:34Z","title":"GPQA: A Graduate-Level Google-Proof Q&A Benchmark","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.12022","snapshot_observed_at":"2026-08-07T00:31:56.121768Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.121768Z"},"links":{"cited_paper":"/paper/2311.12022","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:e36951084521a2d643a25d4c29d91746b4e874894ae309b0376883fa930da463","observation_id":"c239b07c-5622-45bd-94d1-0ca3336170a3","resolution":{"observed_at":"2026-08-07T00:31:56.121768Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.12442","last_updated":"2020-07-13T17:35:31Z","snapshot_observed_at":"2026-08-04T19:34:23.847782Z","submitted_at":"2020-06-22T17:23:47Z","title":"Open-Domain Conversational Agents: Current Progress, Open Problems, and Future Directions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.12442","snapshot_observed_at":"2026-08-07T00:31:56.162766Z","title":"Open-domain conversational agents: Current progress, open problems, and future directions, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.162766Z"},"links":{"cited_paper":"/paper/2006.12442","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:18d23d8801ad590d42e09ed219e2fd5e60d90be06fad0ed2c43930172c4fa673","observation_id":"ca7b6a6a-36c9-41d9-9879-c58c496484c9","resolution":{"observed_at":"2026-08-07T00:31:56.162766Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.17578","last_updated":"2025-02-24T19:01:47Z","snapshot_observed_at":"2026-08-07T17:52:10.217224Z","submitted_at":"2025-02-24T19:01:47Z","title":"How Do Large Language Monkeys Get Their Power (Laws)?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.17578","snapshot_observed_at":"2026-08-07T00:31:56.210081Z","title":"How do large language monkeys get their power (laws)?, 2025 a","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.210081Z"},"links":{"cited_paper":"/paper/2502.17578","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:bcb747e89e0028730307bf8d0d31f04f32bd2616672606c9d10b8f042ed22ef0","observation_id":"ac143d01-b5cc-471d-87fb-70751c3cedd8","resolution":{"observed_at":"2026-08-07T00:31:56.210081Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.18339","last_updated":"2025-02-24T01:01:02Z","snapshot_observed_at":"2026-08-07T17:54:35.134398Z","submitted_at":"2025-02-24T01:01:02Z","title":"Correlating and Predicting Human Evaluations of Language Models from Natural Language Processing Benchmarks","version":1},"cited_work":{"arxiv_id":"2502.18339","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.18339","snapshot_observed_at":"2026-08-07T00:31:57.209098Z","title":"Correlating and Predicting Human Evaluations of Language Models from Natural Language Processing Benchmarks","venue":"cs.CL","work_id":"a4d95c16-8d83-48fc-807c-8f1fef7bc937","year":2025},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.255771Z"},"links":{"cited_paper":"/paper/2502.18339","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:480cdbe5d7bc3c5bb95c7f490b402fe006a828ceff0e6586ca06ef6d54cb4767","observation_id":"523f81be-7186-450e-9f35-57f6dd470994","resolution":{"observed_at":"2026-08-07T00:31:57.274449Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:31:56.309943Z","title":"Learning to summarize with human feedback","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.309943Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:252389c4c54e6244e7591edfa71b3f9b476ddc6ac5855d611bf2a6fce73d6df1","observation_id":"a67831ca-7072-4711-b97e-397476428a2b","resolution":{"observed_at":"2026-08-07T00:31:56.309943Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00118","last_updated":"2024-10-02T15:22:49Z","snapshot_observed_at":"2026-08-02T16:20:09.773989Z","submitted_at":"2024-07-31T19:13:07Z","title":"Gemma 2: Improving Open Language Models at a Practical Size","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00118","snapshot_observed_at":"2026-08-07T00:31:56.373953Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.373953Z"},"links":{"cited_paper":"/paper/2408.00118","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:98c2f7a7073b0b92528628b3725ae3653ec56fe44e2cc63c735bb08621dab99c","observation_id":"c5db7987-a4ed-4a92-8dba-5edd52d2596c","resolution":{"observed_at":"2026-08-07T00:31:56.373953Z","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":"2026-08-07T00:31:57.726083Z","title":"Best practices for the human evaluation of automatically generated text","venue":null,"work_id":"f804955b-8381-48be-b985-1d1df866fc8f","year":2019},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.444503Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:28e4d0c78e76a0a6058322276e6f9b32fac5586bc82848cdcc601df4d09548e1","observation_id":"da8861f4-44c7-4d06-856f-0f855884c2d5","resolution":{"observed_at":"2026-08-07T00:31:57.775291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.03461","last_updated":"2025-02-05T18:58:19Z","snapshot_observed_at":"2026-08-05T09:14:32.339428Z","submitted_at":"2025-02-05T18:58:19Z","title":"Do Large Language Model Benchmarks Test Reliability?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.03461","snapshot_observed_at":"2026-08-07T00:31:56.526077Z","title":"Do large language model benchmarks test reliability? arXiv preprint arXiv:2502.03461, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.526077Z"},"links":{"cited_paper":"/paper/2502.03461","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:86c0974924eda771f409e5ee1bad8bd60457f66172da45af2747c541802ca2ee","observation_id":"a71ed187-186d-4b4f-9697-0ac273e92bb4","resolution":{"observed_at":"2026-08-07T00:31:56.526077Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.14074","last_updated":"2025-06-05T18:48:53Z","snapshot_observed_at":"2026-08-07T18:03:49.757094Z","submitted_at":"2025-02-19T19:59:16Z","title":"Investigating Non-Transitivity in LLM-as-a-Judge","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.14074","snapshot_observed_at":"2026-08-07T00:31:56.606349Z","title":"Investigating non-transitivity in llm-as-a-judge, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.606349Z"},"links":{"cited_paper":"/paper/2502.14074","citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:8755c4287450b7ca69f53012600043d28f2e2e267161b668a9cae1e468fd9f94","observation_id":"48d20450-4ce6-4684-b241-ea212b417015","resolution":{"observed_at":"2026-08-07T00:31:56.606349Z","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":"2026-08-07T00:31:57.606797Z","title":"A careful examination of large language model performance on grade school arithmetic","venue":null,"work_id":"f707f11b-0aeb-4378-aee9-9be0d9f96df0","year":2024},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.681151Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:02718d216320e8108876c49d5402969a6d322cbee8e8ea94b63580cec34092a1","observation_id":"0db17fcf-b662-4fd6-aa54-17928e53e6eb","resolution":{"observed_at":"2026-08-07T00:31:57.661575Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-07T00:31:56.784918Z","title":"Judging llm-as-a-judge with mt-bench and chatbot arena","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.784918Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:0c6b73cdc3ad76baafaddd801d740fb681b5ccfc9b97427e04a341eeebf834aa","observation_id":"970e9838-cdef-4d8c-a380-973dc9418e95","resolution":{"observed_at":"2026-08-07T00:31:56.784918Z","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":"2026-08-07T00:31:56.873071Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.873071Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:1142b0924e8e242a456f538509834274d44b312a72803728e3d10dc25951ed80","observation_id":"656dbe27-9ce0-4b9c-ba1a-4deeea2c5c50","resolution":{"observed_at":"2026-08-07T00:31:56.873071Z","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":"2026-08-07T00:31:56.947707Z","title":"@esa (Ref","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:56.947707Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:45588665c1bea71aa9568f07a0acb02a2423c99df3eb2305f91fb7d4f41f9555","observation_id":"f0efe822-62ee-4987-8c3d-439a686af387","resolution":{"observed_at":"2026-08-07T00:31:56.947707Z","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":"2026-08-07T00:31:57.035227Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:57.035227Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:f35d6f9e91f402e750d490783253dbcd1a5d78f5b972ea7f433b8617d525b071","observation_id":"ba3415b9-00c1-4e09-b128-b39339e4f8e9","resolution":{"observed_at":"2026-08-07T00:31:57.035227Z","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":"2026-08-07T00:31:57.090248Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-07T00:31:57.090248Z"},"links":{"citing_paper":"/paper/2506.13681"},"observation_digest":"sha256:c6fc8a9b50e2ce5cf9a818a126a0628b6f2be23a9d739ac5183a153f9b0dfa53","observation_id":"9963d8d9-259b-4585-85c8-9eb804606146","resolution":{"observed_at":"2026-08-07T00:31:57.090248Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.13681","last_updated":"2025-06-19T04:41:52Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-08T00:16:16.582814Z","submitted_at":"2025-06-16T16:38:04Z","title":"Min-p, Max Exaggeration: A Critical Analysis of Min-p Sampling in Language Models"},"reference_resolution":{"displayed":34,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":28,"verified_exact":0,"verified_fuzzy":5},"total_outbound_references":34},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2506.13681."}