{"as_of":"2026-08-08T11:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5b01917ea5c3147f3c796d5c96d16af090492b212eb4e1875d35b60848b52050","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:29:23.358235Z","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":"2026-07-03T06:47:43.812886Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2401.13110","last_updated":"2024-01-23T21:47:12Z","snapshot_observed_at":"2026-08-04T22:46:17.607824Z","submitted_at":"2024-01-23T21:47:12Z","title":"XAI for All: Can Large Language Models Simplify Explainable AI?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.13110","snapshot_observed_at":"2026-08-07T11:29:23.358235Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.02262","last_updated":"2025-06-02T21:10:51Z","snapshot_observed_at":"2026-08-07T11:25:01.461990Z","submitted_at":"2025-06-02T21:10:51Z","title":"Composable Building Blocks for Controllable and Transparent Interactive AI Systems","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T11:29:23.358235Z"},"links":{"cited_paper":"/paper/2401.13110","citing_paper":"/paper/2506.02262"},"observation_digest":"sha256:8bc225a7f59135da08ef3686807c013c639bdb7b8e74d50f7f09183c52cc75da","observation_id":"295d5137-95a3-448f-98dc-562f72609a8e","resolution":{"observed_at":"2026-08-07T11:29:23.358235Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.13110","last_updated":"2024-01-23T21:47:12Z","snapshot_observed_at":"2026-08-04T22:46:17.607824Z","submitted_at":"2024-01-23T21:47:12Z","title":"XAI for All: Can Large Language Models Simplify Explainable AI?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.13110","snapshot_observed_at":"2026-08-07T01:02:18.331055Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12240","last_updated":"2025-06-13T21:41:07Z","snapshot_observed_at":"2026-08-07T00:52:47.231030Z","submitted_at":"2025-06-13T21:41:07Z","title":"Mind the XAI Gap: A Human-Centered LLM Framework for Democratizing Explainable AI","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T01:02:18.331055Z"},"links":{"cited_paper":"/paper/2401.13110","citing_paper":"/paper/2506.12240"},"observation_digest":"sha256:c8ae6e69a97cf6360c89496f40306627a2e33ffb7edf7f65e78a937406e48ec5","observation_id":"4da7ee07-944b-4a04-b67e-bbead82c8421","resolution":{"observed_at":"2026-08-07T01:02:18.331055Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.13110","last_updated":"2024-01-23T21:47:12Z","snapshot_observed_at":"2026-08-04T22:46:17.607824Z","submitted_at":"2024-01-23T21:47:12Z","title":"XAI for All: Can Large Language Models Simplify Explainable AI?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.13110","snapshot_observed_at":"2026-08-06T22:22:41.465967Z","title":"and et al","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.21812","last_updated":"2025-06-26T23:25:22Z","snapshot_observed_at":"2026-08-06T22:16:14.734980Z","submitted_at":"2025-06-26T23:25:22Z","title":"Towards Transparent AI: A Survey on Explainable Large Language Models","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T22:22:41.465967Z"},"links":{"cited_paper":"/paper/2401.13110","citing_paper":"/paper/2506.21812"},"observation_digest":"sha256:6e445c5fe17b401fcaef9a9c20bc50393404e8c6e636fcbc5d03497835811aa7","observation_id":"b5487ae0-6855-4938-9a61-0f25bd6072c1","resolution":{"observed_at":"2026-08-06T22:22:41.465967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.13110","last_updated":"2024-01-23T21:47:12Z","snapshot_observed_at":"2026-08-04T22:46:17.607824Z","submitted_at":"2024-01-23T21:47:12Z","title":"XAI for All: Can Large Language Models Simplify Explainable AI?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.13110","snapshot_observed_at":"2026-08-05T05:33:22.987092Z","title":"XAI for all: Can large language models simplify explainable AI?","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.05199","last_updated":"2025-09-05T15:58:49Z","snapshot_observed_at":"2026-08-08T06:11:52.889994Z","submitted_at":"2025-09-05T15:58:49Z","title":"Triadic Fusion of Cognitive, Functional, and Causal Dimensions for Explainable LLMs: The TAXAL Framework","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T05:33:22.987092Z"},"links":{"cited_paper":"/paper/2401.13110","citing_paper":"/paper/2509.05199"},"observation_digest":"sha256:89d57747ee769a0b402a05d1d8156c76b89fdf03e151d721efb2fa06e7912dac","observation_id":"bc9aa147-d8b8-47d3-b4c6-669d4e9e2da9","resolution":{"observed_at":"2026-08-05T05:33:22.987092Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.13110","last_updated":"2024-01-23T21:47:12Z","snapshot_observed_at":"2026-08-04T22:46:17.607824Z","submitted_at":"2024-01-23T21:47:12Z","title":"XAI for All: Can Large Language Models Simplify Explainable AI?","version":1},"cited_work":{"arxiv_id":"2401.13110","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2401.13110","snapshot_observed_at":"2026-07-03T06:47:43.812886Z","title":"XAI for all: Can large language models simplify explainable AI?","venue":null,"work_id":"ff150a21-904b-4c9b-8895-2f5f05041833","year":2024},"citing_paper":{"arxiv_id":"2606.10882","last_updated":"2026-06-09T13:56:31Z","snapshot_observed_at":"2026-08-06T14:55:34.402749Z","submitted_at":"2026-06-09T13:56:31Z","title":"From Quality Properties to Practice: A Guideline and Workflow for Explainability Requirements","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-27T12:25:42.492883Z"},"links":{"cited_paper":"/paper/2401.13110","citing_paper":"/paper/2606.10882"},"observation_digest":"sha256:7a925bcc6f23b23551d6dce90130f3b81fa73b192fd9026be8b769667e7ebbca","observation_id":"f32cba46-10b8-4297-9486-2cdab9b4edc9","resolution":{"observed_at":"2026-07-03T06:47:43.814376Z","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/2401.13110/citation-record","integrity":"/paper/2401.13110/integrity","json":"/paper/2401.13110/citation-record.json","paper":"/paper/2401.13110"},"outbound":[],"paper":{"arxiv_id":"2401.13110","last_updated":"2024-01-23T21:47:12Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-04T22:46:17.607824Z","submitted_at":"2024-01-23T21:47:12Z","title":"XAI for All: Can Large Language Models Simplify Explainable AI?"},"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 5 inbound Pith citation observations for arXiv:2401.13110."}