{"as_of":"2026-08-08T21:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:59227fac9e4a2fdb7f397ded4c76cea206eb08bb9f53182317b5199844537f30","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":"2026-08-08T06:32:00.761636+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":"2026-08-06T18:08:17.752326Z","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":"2026-05-10T23:45:53.591816Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.14791","last_updated":"2024-02-23T07:02:09Z","snapshot_observed_at":"2026-08-04T21:05:00.813515Z","submitted_at":"2023-05-24T06:44:32Z","title":"Prompting Large Language Models for Counterfactual Generation: An Empirical Study","version":2},"cited_work":{"arxiv_id":"2305.14791","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.14791","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Prompting large language models for counterfactual generation: An empirical study","venue":null,"work_id":"ce916239-ee9f-497f-9292-b797604de196","year":2024},"citing_paper":{"arxiv_id":"2402.01207","last_updated":"2026-04-02T21:08:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-02T08:25:32Z","title":"Efficient Causal Graph Discovery Using Large Language Models","version":5},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-24T04:10:17.251713Z"},"links":{"cited_paper":"/paper/2305.14791","citing_paper":"/paper/2402.01207"},"observation_digest":"sha256:1833ef81ff4572c1dbcf80f3b5edd9c5d6052146101c163ef96e19446319ba3d","observation_id":"98c03554-aac8-46ef-bed2-15a30a57e50a","resolution":{"observed_at":"2026-05-09T04:25:28.690550Z","resolver_source":"arxiv_id","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":{"arxiv_id":"2305.14791","last_updated":"2024-02-23T07:02:09Z","snapshot_observed_at":"2026-08-04T21:05:00.813515Z","submitted_at":"2023-05-24T06:44:32Z","title":"Prompting Large Language Models for Counterfactual Generation: An Empirical Study","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.14791","snapshot_observed_at":"2026-08-06T18:08:17.752326Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.10596","last_updated":"2025-07-12T06:31:38Z","snapshot_observed_at":"2026-08-06T18:00:09.103200Z","submitted_at":"2025-07-12T06:31:38Z","title":"PLEX: Perturbation-free Local Explanations for LLM-Based Text Classification","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T18:08:17.752326Z"},"links":{"cited_paper":"/paper/2305.14791","citing_paper":"/paper/2507.10596"},"observation_digest":"sha256:305817d89dae20ad107f137dc819d909ee3634b10d00b3639c17d5ff598340c6","observation_id":"5d90b2d7-75ef-4a47-b8de-9f1d84e48304","resolution":{"observed_at":"2026-08-06T18:08:17.752326Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.14791","last_updated":"2024-02-23T07:02:09Z","snapshot_observed_at":"2026-08-04T21:05:00.813515Z","submitted_at":"2023-05-24T06:44:32Z","title":"Prompting Large Language Models for Counterfactual Generation: An Empirical Study","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.14791","snapshot_observed_at":"2026-08-06T17:29:44.295312Z","title":"Muser: A multi-view similar case retrieval dataset","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.10852","last_updated":"2025-08-02T01:45:01Z","snapshot_observed_at":"2026-08-08T02:45:01.978815Z","submitted_at":"2025-07-14T22:56:58Z","title":"LLMs on Trial: Evaluating Judicial Fairness for Large Language Models","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T17:29:44.295312Z"},"links":{"cited_paper":"/paper/2305.14791","citing_paper":"/paper/2507.10852"},"observation_digest":"sha256:958882d994677542ed9b711c83eb1ec7797c6f8e88a009e8004e051ec1681765","observation_id":"91ac5fc2-8473-4b29-aacf-c5f9ca45eed6","resolution":{"observed_at":"2026-08-06T17:29:44.295312Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.14791","last_updated":"2024-02-23T07:02:09Z","snapshot_observed_at":"2026-08-04T21:05:00.813515Z","submitted_at":"2023-05-24T06:44:32Z","title":"Prompting Large Language Models for Counterfactual Generation: An Empirical Study","version":2},"cited_work":{"arxiv_id":"2305.14791","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.14791","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Prompting large language models for counterfactual generation: An empirical study","venue":null,"work_id":"ce916239-ee9f-497f-9292-b797604de196","year":2024},"citing_paper":{"arxiv_id":"2604.06323","last_updated":"2026-04-09T08:31:16Z","snapshot_observed_at":"2026-08-05T11:56:20.326339Z","submitted_at":"2026-04-07T18:00:40Z","title":"Blockchain and AI: Securing Intelligent Networks for the Future","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-10T18:52:23.255538Z"},"links":{"cited_paper":"/paper/2305.14791","citing_paper":"/paper/2604.06323"},"observation_digest":"sha256:a27b4807713af6522e3b4de46951b7cf451f016533ca78e646d9b71975834e68","observation_id":"bf3a6445-8616-4562-afc7-066519138280","resolution":{"observed_at":"2026-05-10T23:45:53.596811Z","resolver_source":"arxiv_id","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/2305.14791/citation-record","integrity":"/paper/2305.14791/integrity","json":"/paper/2305.14791/citation-record.json","paper":"/paper/2305.14791"},"outbound":[],"paper":{"arxiv_id":"2305.14791","last_updated":"2024-02-23T07:02:09Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-04T21:05:00.813515Z","submitted_at":"2023-05-24T06:44:32Z","title":"Prompting Large Language Models for Counterfactual Generation: An Empirical Study"},"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":"2026-08-08T06:32:00.761636+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 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2305.14791."}