{"as_of":"2026-08-11T06:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:44789df0848c9dc417b4c4fcee8a7f8b2bcf80c3620a642abb82d555c0a12cbc","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":3,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":3,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:05:45.447639Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-02T08:26:48.122920Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2010.11506","last_updated":"2020-10-22T07:48:38Z","snapshot_observed_at":"2026-08-09T17:03:17.769507Z","submitted_at":"2020-10-22T07:48:38Z","title":"Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data","version":1},"cited_work":{"arxiv_id":"2010.11506","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2010.11506","snapshot_observed_at":"2026-07-02T08:26:48.122920Z","title":"Calibrated language model fine-tuning for in-and out-of-distribution data","venue":null,"work_id":"3ce23b3f-f825-431f-b2e6-a2ba4f1dde4f","year":2010},"citing_paper":{"arxiv_id":"2308.05374","last_updated":"2024-03-21T00:21:14Z","snapshot_observed_at":"2026-08-02T17:09:20.540788Z","submitted_at":"2023-08-10T06:43:44Z","title":"Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-17T22:30:44.520703Z"},"links":{"cited_paper":"/paper/2010.11506","citing_paper":"/paper/2308.05374"},"observation_digest":"sha256:e620a8429904dcb6b3dd901ba59de791410313c3b3cfcf522d6f63f4bbd3221f","observation_id":"02fc6cbc-f215-4fa1-8e02-00973a04b52d","resolution":{"observed_at":"2026-05-17T22:30:44.794254Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11506","last_updated":"2020-10-22T07:48:38Z","snapshot_observed_at":"2026-08-09T17:03:17.769507Z","submitted_at":"2020-10-22T07:48:38Z","title":"Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11506","snapshot_observed_at":"2026-08-07T13:05:45.447639Z","title":"Calibrated language model fine-tuning for in-and out-of-distribution data","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2505.22787","last_updated":"2025-05-28T18:58:09Z","snapshot_observed_at":"2026-08-10T09:02:54.247480Z","submitted_at":"2025-05-28T18:58:09Z","title":"Can Large Language Models Match the Conclusions of Systematic Reviews?","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-07T13:05:45.447639Z"},"links":{"cited_paper":"/paper/2010.11506","citing_paper":"/paper/2505.22787"},"observation_digest":"sha256:b54dfe02a54a7603c6af5fb8e2e7c4412684d0e5ae91f70192d390083504ac96","observation_id":"8ec6626c-2a83-4b3f-978a-1cc08e17c7ec","resolution":{"observed_at":"2026-08-07T13:05:45.447639Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11506","last_updated":"2020-10-22T07:48:38Z","snapshot_observed_at":"2026-08-09T17:03:17.769507Z","submitted_at":"2020-10-22T07:48:38Z","title":"Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data","version":1},"cited_work":{"arxiv_id":"2010.11506","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2010.11506","snapshot_observed_at":"2026-07-02T08:26:48.122920Z","title":"Calibrated language model fine-tuning for in-and out-of-distribution data","venue":null,"work_id":"3ce23b3f-f825-431f-b2e6-a2ba4f1dde4f","year":2010},"citing_paper":{"arxiv_id":"2606.05436","last_updated":"2026-06-03T20:58:43Z","snapshot_observed_at":"2026-07-06T23:45:28.379468Z","submitted_at":"2026-06-03T20:58:43Z","title":"Ten Headache Specialists versus Artificial Intelligence for Clinical Literature Summarization: A Critical Evaluation and Comparison","version":1},"reference_index":130,"source":"arxiv_source","source_observed_at":"2026-06-28T06:03:59.798126Z"},"links":{"cited_paper":"/paper/2010.11506","citing_paper":"/paper/2606.05436"},"observation_digest":"sha256:0471dd89bd5919b8617f0fbe5a6b0a4d19a35f802718cda35b117088e4ef9fd4","observation_id":"3b59c499-3055-4932-b254-6153d92b26e1","resolution":{"observed_at":"2026-07-02T08:26:48.124340Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2010.11506/citation-record","integrity":"/paper/2010.11506/integrity","json":"/paper/2010.11506/citation-record.json","paper":"/paper/2010.11506"},"outbound":[],"paper":{"arxiv_id":"2010.11506","last_updated":"2020-10-22T07:48:38Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T17:03:17.769507Z","submitted_at":"2020-10-22T07:48:38Z","title":"Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2010.11506."}