{"as_of":"2026-08-07T22:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0c40478a8f37085bbc22b3b47c98316aab6a620c293ebed835e8710ff0efd248","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":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T22:04:42.107573Z","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":"2026-05-20T22:13:46.933698Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2303.12748","last_updated":"2023-04-18T18:28:51Z","snapshot_observed_at":"2026-08-02T11:01:17.425713Z","submitted_at":"2023-03-11T17:14:04Z","title":"Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.12748","snapshot_observed_at":"2026-08-06T22:04:42.107573Z","title":"arXiv preprint arXiv:2303.12748 (2023) 14","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.22819","last_updated":"2025-06-28T08:57:57Z","snapshot_observed_at":"2026-08-06T21:54:55.937252Z","submitted_at":"2025-06-28T08:57:57Z","title":"Prompting without Panic: Attribute-aware, Zero-shot, Test-Time Calibration","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T22:04:42.107573Z"},"links":{"cited_paper":"/paper/2303.12748","citing_paper":"/paper/2506.22819"},"observation_digest":"sha256:b373237b97571a4c57442580050f1daeac6815024027906f4ed94158e2322d41","observation_id":"773bbd09-4484-4218-be89-fefda40de718","resolution":{"observed_at":"2026-08-06T22:04:42.107573Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.12748","last_updated":"2023-04-18T18:28:51Z","snapshot_observed_at":"2026-08-02T11:01:17.425713Z","submitted_at":"2023-03-11T17:14:04Z","title":"Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models","version":4},"cited_work":{"arxiv_id":"2303.12748","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2303.12748","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Enabling calibration in the zero-shot inference of large vision-language models","venue":null,"work_id":"f36314c1-8f60-4074-a164-9d030858bd5d","year":2023},"citing_paper":{"arxiv_id":"2605.09730","last_updated":"2026-05-15T19:01:49Z","snapshot_observed_at":"2026-08-02T16:37:22.296787Z","submitted_at":"2026-05-10T19:57:32Z","title":"RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-05-12T03:37:09.000442Z"},"links":{"cited_paper":"/paper/2303.12748","citing_paper":"/paper/2605.09730"},"observation_digest":"sha256:7dae754337f567e268d1d11b965d9edbcacf06b341413df242cc1a4cfaed74cc","observation_id":"dced7f5c-923d-41a1-8534-89eecc32b5c7","resolution":{"observed_at":"2026-05-12T07:11:26.641897Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.12748","last_updated":"2023-04-18T18:28:51Z","snapshot_observed_at":"2026-08-02T11:01:17.425713Z","submitted_at":"2023-03-11T17:14:04Z","title":"Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models","version":4},"cited_work":{"arxiv_id":"2303.12748","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2303.12748","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Enabling calibration in the zero-shot inference of large vision-language models","venue":null,"work_id":"f36314c1-8f60-4074-a164-9d030858bd5d","year":2023},"citing_paper":{"arxiv_id":"2605.09730","last_updated":"2026-05-15T19:01:49Z","snapshot_observed_at":"2026-08-02T16:37:22.296787Z","submitted_at":"2026-05-10T19:57:32Z","title":"RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-05-15T05:25:43.890367Z"},"links":{"cited_paper":"/paper/2303.12748","citing_paper":"/paper/2605.09730"},"observation_digest":"sha256:7ce9cc6f410bee046805bbc25a9af808ad471f8a71d4b84c0066a40490cc29e5","observation_id":"bb8d0319-e50c-49d0-acd0-d372645421b2","resolution":{"observed_at":"2026-05-15T05:29:47.941793Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.12748","last_updated":"2023-04-18T18:28:51Z","snapshot_observed_at":"2026-08-02T11:01:17.425713Z","submitted_at":"2023-03-11T17:14:04Z","title":"Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models","version":4},"cited_work":{"arxiv_id":"2303.12748","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2303.12748","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Enabling calibration in the zero-shot inference of large vision-language models","venue":null,"work_id":"f36314c1-8f60-4074-a164-9d030858bd5d","year":2023},"citing_paper":{"arxiv_id":"2605.09730","last_updated":"2026-05-15T19:01:49Z","snapshot_observed_at":"2026-08-02T16:37:22.296787Z","submitted_at":"2026-05-10T19:57:32Z","title":"RubricRefine: Improving Tool-Use Agent Reliability with Training-Free Pre-Execution Refinement","version":3},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-05-20T22:12:23.680155Z"},"links":{"cited_paper":"/paper/2303.12748","citing_paper":"/paper/2605.09730"},"observation_digest":"sha256:d9e1fe2688fad7d6f6fa738454e7081d8912264b8dfcbaf2f0300d26c8fb635e","observation_id":"2265549c-5571-4181-8322-96506af50edf","resolution":{"observed_at":"2026-05-20T22:13:46.938183Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2303.12748/citation-record","integrity":"/paper/2303.12748/integrity","json":"/paper/2303.12748/citation-record.json","paper":"/paper/2303.12748"},"outbound":[],"paper":{"arxiv_id":"2303.12748","last_updated":"2023-04-18T18:28:51Z","latest_version":4,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-02T11:01:17.425713Z","submitted_at":"2023-03-11T17:14:04Z","title":"Enabling Calibration In The Zero-Shot Inference of Large Vision-Language Models"},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2303.12748."}