{"as_of":"2026-08-13T02:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:93c04e4b261c8803a901ceac069c2828b41fa119eff1eb84023e6b205ac04ee2","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":19,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":19,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":19,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":19,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T11:45:04.601317Z","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":"2026-07-04T18:40:03.502214Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-08-07T13:43:20.009714Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.21191","last_updated":"2025-05-27T13:40:28Z","snapshot_observed_at":"2026-08-13T01:34:29.623710Z","submitted_at":"2025-05-27T13:40:28Z","title":"Unveiling Instruction-Specific Neurons & Experts: An Analytical Framework for LLM's Instruction-Following Capabilities","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T13:43:20.009714Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2505.21191"},"observation_digest":"sha256:fd16d5e80f80a2d6990c816871061f3dfef64d10946f3155438f872eb261b363","observation_id":"debfa87b-18b5-4e51-969c-90a69b4d3c5d","resolution":{"observed_at":"2026-08-07T13:43:20.009714Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-08-07T12:32:29.744760Z","title":"Llms for explainable ai: A comprehensive survey","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.24340","last_updated":"2025-05-30T08:32:37Z","snapshot_observed_at":"2026-08-12T04:21:05.862812Z","submitted_at":"2025-05-30T08:32:37Z","title":"GeoVision Labeler: Zero-Shot Geospatial Classification with Vision and Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T12:32:29.744760Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2505.24340"},"observation_digest":"sha256:eb5d5ee55a58a322b03100efdfa8c1dbc832c15cf333d0936a40a4ddf65412cb","observation_id":"1a0f4c1b-f7b7-4d64-ad80-0f0e38b51fae","resolution":{"observed_at":"2026-08-07T12:32:29.744760Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-08-07T11:21:39.242160Z","title":"Llms for explainable ai: A comprehensive survey.arXiv preprint arXiv:2504.00125, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.02726","last_updated":"2025-06-03T10:36:38Z","snapshot_observed_at":"2026-08-10T14:38:31.928986Z","submitted_at":"2025-06-03T10:36:38Z","title":"RACE-Align: Retrieval-Augmented and Chain-of-Thought Enhanced Preference Alignment for Large Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:21:39.242160Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2506.02726"},"observation_digest":"sha256:ec7c85a4cda85f49b5de73df0a9053926c82dd68d1ccc7f0b332df27032260ac","observation_id":"a381681a-455a-4ea2-9fb1-fabb69e82004","resolution":{"observed_at":"2026-08-07T11:21:39.242160Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-08-06T18:47:53.648019Z","title":"& Lin, B","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.07421","last_updated":"2025-07-10T04:31:01Z","snapshot_observed_at":"2026-08-12T13:42:13.096591Z","submitted_at":"2025-07-10T04:31:01Z","title":"SynthEHR-Eviction: Enhancing Eviction SDoH Detection with LLM-Augmented Synthetic EHR Data","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T18:47:53.648019Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2507.07421"},"observation_digest":"sha256:88e93a28dfa49804b44b07bd95f79ce6ff4d6a7bb85ede316543a7b5b2f24be3","observation_id":"7d7b8723-7815-47e8-8823-1a229442f23d","resolution":{"observed_at":"2026-08-06T18:47:53.648019Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-08-06T04:35:18.187953Z","title":"Llms for explainable ai: A comprehensive survey,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.03393","last_updated":"2025-08-05T12:42:46Z","snapshot_observed_at":"2026-08-12T23:33:42.398906Z","submitted_at":"2025-08-05T12:42:46Z","title":"Agentic AI in 6G Software Businesses: A Layered Maturity Model","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T04:35:18.187953Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2508.03393"},"observation_digest":"sha256:3d4d7c5daffce8abd3ca569cf40c7dd2fd6c3ae103276db354828e746a2cc080","observation_id":"797d84bb-14c0-425b-b02f-3babbc036a6b","resolution":{"observed_at":"2026-08-06T04:35:18.187953Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-08-05T18:47:19.914470Z","title":"Llms for explainable ai: A compre- hensive survey,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.14028","last_updated":"2025-08-19T17:39:31Z","snapshot_observed_at":"2026-08-12T18:41:34.024868Z","submitted_at":"2025-08-19T17:39:31Z","title":"Trust and Reputation in Data Sharing: A Survey","version":1},"reference_index":201,"source":"pdf_text","source_observed_at":"2026-08-05T18:47:19.914470Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2508.14028"},"observation_digest":"sha256:37b89b2b0032aca6e9d5d0b494f10e962a5b1d100d86f4c44b9cfe1c12b2d055","observation_id":"1af23ab8-dc62-41ea-ad69-9a6adb3fb2dc","resolution":{"observed_at":"2026-08-05T18:47:19.914470Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":"2504.00125","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-07-04T18:40:03.502214Z","title":"Llms for explainable ai: A comprehensive survey","venue":null,"work_id":"e459a607-d0da-43de-9738-9ef740a3bbe5","year":2025},"citing_paper":{"arxiv_id":"2602.04003","last_updated":"2026-05-15T16:48:29Z","snapshot_observed_at":"2026-07-06T22:44:23.981940Z","submitted_at":"2026-02-03T20:42:44Z","title":"When AI Persuades: Adversarial Explanation Attacks on Human Trust in AI-Assisted Decision Making","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-21T13:21:45.525765Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2602.04003"},"observation_digest":"sha256:2148439d5be37fd72f66fc7fc3bd0b70b4337a0e33e561ef35fd8f367aeec8c9","observation_id":"5c416be9-184b-4245-bc26-ea4b430ffcb8","resolution":{"observed_at":"2026-05-21T13:24:11.344767Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":"2504.00125","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-07-04T18:40:03.502214Z","title":"Llms for explainable ai: A comprehensive survey","venue":null,"work_id":"e459a607-d0da-43de-9738-9ef740a3bbe5","year":2025},"citing_paper":{"arxiv_id":"2604.03976","last_updated":"2026-05-04T20:58:24Z","snapshot_observed_at":"2026-07-06T22:53:01.835843Z","submitted_at":"2026-04-05T05:42:20Z","title":"Quantifying Trust: Financial Risk Management for Trustworthy AI Agents","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-13T17:16:17.464937Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2604.03976"},"observation_digest":"sha256:4d2fd8d0bc47829972c55c79e824021ffe84f2558c88c6937cfedf7fdadd6207","observation_id":"bd95f519-8a43-4831-b931-304f19995d76","resolution":{"observed_at":"2026-05-13T17:16:37.282731Z","resolver_source":"orphan_title_repair","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-07-13T09:28:30.950169Z","title":"Llms for explain- able ai: A comprehensive survey,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2604.06265","last_updated":"2026-06-18T07:01:21Z","snapshot_observed_at":"2026-07-13T09:28:30.620949Z","submitted_at":"2026-04-07T02:37:45Z","title":"SMT-AD: a scalable quantum-inspired anomaly detection approach","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-13T09:28:30.950169Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2604.06265"},"observation_digest":"sha256:7e144eb9f3b0a209cfe2eb127a476e869998449dd61e5b8019f21bee0e79aef1","observation_id":"0c667ec8-2bdc-4f0b-8141-9886f7248b38","resolution":{"observed_at":"2026-07-13T09:28:30.950169Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":"2504.00125","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-07-04T18:40:03.502214Z","title":"Llms for explainable ai: A comprehensive survey","venue":null,"work_id":"e459a607-d0da-43de-9738-9ef740a3bbe5","year":2025},"citing_paper":{"arxiv_id":"2604.06266","last_updated":"2026-04-07T03:21:14Z","snapshot_observed_at":"2026-07-06T22:54:48.916799Z","submitted_at":"2026-04-07T03:21:14Z","title":"Attribution-Driven Explainable Intrusion Detection with Encoder-Based Large Language Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-10T20:06:01.233352Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2604.06266"},"observation_digest":"sha256:5fe9d10dea75805b28fb8e145b8604c360a9fd32d019303bb3f36bfa9bd81207","observation_id":"251e6d23-fbb7-4e28-8f39-af62039e6f57","resolution":{"observed_at":"2026-05-10T22:15:48.796336Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":"2504.00125","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-07-04T18:40:03.502214Z","title":"Llms for explainable ai: A comprehensive survey","venue":null,"work_id":"e459a607-d0da-43de-9738-9ef740a3bbe5","year":2025},"citing_paper":{"arxiv_id":"2604.14687","last_updated":"2026-04-16T06:46:32Z","snapshot_observed_at":"2026-07-06T23:02:22.790426Z","submitted_at":"2026-04-16T06:46:32Z","title":"M2-PALE: A Framework for Explaining Multi-Agent MCTS--Minimax Hybrids via Process Mining and LLMs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T11:42:03.298417Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2604.14687"},"observation_digest":"sha256:b975384e6623645b81bd24097c8ebc02c47e53498b9c49dd79bc6b9d260685b7","observation_id":"1ddc1d91-b04f-4eee-a9bc-6a98ca8c4a5a","resolution":{"observed_at":"2026-05-10T11:50:20.782841Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":"2504.00125","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-07-04T18:40:03.502214Z","title":"Llms for explainable ai: A comprehensive survey","venue":null,"work_id":"e459a607-d0da-43de-9738-9ef740a3bbe5","year":2025},"citing_paper":{"arxiv_id":"2604.18052","last_updated":"2026-04-20T10:19:57Z","snapshot_observed_at":"2026-08-04T19:55:29.062851Z","submitted_at":"2026-04-20T10:19:57Z","title":"ExAI5G: A Logic-Based Explainable AI Framework for Intrusion Detection in 5G Networks","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T04:35:13.736217Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2604.18052"},"observation_digest":"sha256:441c648d95dca0d6bee8fff3e6f161d1fbbc9708753a11cfa8e225c5653a36de","observation_id":"e3bca10a-ff20-4dbc-97ca-0c7c440b5c47","resolution":{"observed_at":"2026-05-10T12:15:22.980498Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":"2504.00125","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-07-04T18:40:03.502214Z","title":"Llms for explainable ai: A comprehensive survey","venue":null,"work_id":"e459a607-d0da-43de-9738-9ef740a3bbe5","year":2025},"citing_paper":{"arxiv_id":"2604.21092","last_updated":"2026-04-22T21:22:21Z","snapshot_observed_at":"2026-08-11T20:48:37.464785Z","submitted_at":"2026-04-22T21:22:21Z","title":"Mind the Prompt: Self-adaptive Generation of Task Plan Explanations via LLMs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-09T23:56:41.219465Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2604.21092"},"observation_digest":"sha256:fd6eaec685f87772c8f2b5b14f0a411e975b38922f3bbfee17655d1799696474","observation_id":"ee26b792-0d54-4109-8351-ea5813f2d63e","resolution":{"observed_at":"2026-05-11T13:51:04.740092Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":"2504.00125","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-07-04T18:40:03.502214Z","title":"Llms for explainable ai: A comprehensive survey","venue":null,"work_id":"e459a607-d0da-43de-9738-9ef740a3bbe5","year":2025},"citing_paper":{"arxiv_id":"2604.24623","last_updated":"2026-04-27T15:52:20Z","snapshot_observed_at":"2026-08-11T12:19:56.185305Z","submitted_at":"2026-04-27T15:52:20Z","title":"XGRAG: A Graph-Native Framework for Explaining KG-based Retrieval-Augmented Generation","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-05-08T03:26:18.733886Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2604.24623"},"observation_digest":"sha256:1a7a06dcd4a61d4831f5839b59836c49880cd463d1a966f827ef884c2f6b9f38","observation_id":"ea181e00-220f-4bd5-bb08-4d18ef779146","resolution":{"observed_at":"2026-05-11T22:06:18.135951Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":"2504.00125","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-07-04T18:40:03.502214Z","title":"Llms for explainable ai: A comprehensive survey","venue":null,"work_id":"e459a607-d0da-43de-9738-9ef740a3bbe5","year":2025},"citing_paper":{"arxiv_id":"2606.24424","last_updated":"2026-06-23T11:01:28Z","snapshot_observed_at":"2026-07-06T23:58:58.854077Z","submitted_at":"2026-06-23T11:01:28Z","title":"Explainable AI for Next-Generation Wireless Physical Layer: Basics, State-of-the-Art, and Open Challenges","version":1},"reference_index":275,"source":"pdf_text","source_observed_at":"2026-06-25T22:34:33.698421Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2606.24424"},"observation_digest":"sha256:58dafccfbb25da427835d20a2c497664f9d26d9ad4fd8d0f813e435664c0a2c5","observation_id":"67d18bbf-b2dd-492d-9926-2899c53ba82d","resolution":{"observed_at":"2026-07-04T18:40:03.503589Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":"2504.00125","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-07-04T18:40:03.502214Z","title":"Llms for explainable ai: A comprehensive survey","venue":null,"work_id":"e459a607-d0da-43de-9738-9ef740a3bbe5","year":2025},"citing_paper":{"arxiv_id":"2606.28708","last_updated":"2026-06-27T03:29:49Z","snapshot_observed_at":"2026-08-11T21:06:42.454009Z","submitted_at":"2026-06-27T03:29:49Z","title":"AnTenA: Actionable and Explainable Tensor Analysis System with Large Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-30T10:16:50.346876Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2606.28708"},"observation_digest":"sha256:24c6cd99d9c9462b79d379540e712b8a97f9b5679177ed62ab646f9656eb5102","observation_id":"57679cc4-e155-4bf4-ac1a-f82c033a9c2d","resolution":{"observed_at":"2026-06-30T12:44:39.654122Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":"2504.00125","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-07-04T18:40:03.502214Z","title":"Llms for explainable ai: A comprehensive survey","venue":null,"work_id":"e459a607-d0da-43de-9738-9ef740a3bbe5","year":2025},"citing_paper":{"arxiv_id":"2607.00972","last_updated":"2026-07-01T14:08:58Z","snapshot_observed_at":"2026-08-09T03:19:55.185156Z","submitted_at":"2026-07-01T14:08:58Z","title":"Bayesian Uncertainty Propagation for Agentic RAG Pipelines: A Proof-of-Concept Study on Multi-Hop Question Answering","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-02T12:24:32.832030Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2607.00972"},"observation_digest":"sha256:06b872c4892fb2df89410caf8408ea18d93db12dc7795ec2851e855b1c792374","observation_id":"1a424bf3-a190-4835-9a20-8945e2b0bd15","resolution":{"observed_at":"2026-07-02T12:26:56.060208Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-08-02T07:06:20.676202Z","title":"LLMs for explainable AI: A comprehensive survey, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.13078","last_updated":"2026-07-12T22:34:02Z","snapshot_observed_at":"2026-08-09T02:07:52.896888Z","submitted_at":"2026-07-12T22:34:02Z","title":"Operational Evidence Gaps for LLMs in Fraud Detection and Trust-and-Safety Workflows","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-02T07:06:20.676202Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2607.13078"},"observation_digest":"sha256:ae25199e4ab78fdbb524014a62c2a2d24545346c2dffc829970f52205e80e4ec","observation_id":"65481bcf-9fc8-41cf-969c-eabe7213b6f8","resolution":{"observed_at":"2026-08-02T07:06:20.676202Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.00125","snapshot_observed_at":"2026-08-12T11:45:04.601317Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.11033","last_updated":"2026-08-11T15:10:34Z","snapshot_observed_at":"2026-08-13T02:20:53.332021Z","submitted_at":"2026-08-11T15:10:34Z","title":"Who Are You Explaining To? A Multi-Agent System for Audience-Aware XAI Narratives","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T11:45:04.601317Z"},"links":{"cited_paper":"/paper/2504.00125","citing_paper":"/paper/2608.11033"},"observation_digest":"sha256:f8469dd2c79b162b9fc247430095213774c4a64c076add313513d958038efd04","observation_id":"165a94b5-ed3e-45f6-a774-017de00538e9","resolution":{"observed_at":"2026-08-12T11:45:04.601317Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2504.00125/citation-record","integrity":"/paper/2504.00125/integrity","json":"/paper/2504.00125/citation-record.json","paper":"/paper/2504.00125"},"outbound":[],"paper":{"arxiv_id":"2504.00125","last_updated":"2025-03-31T18:19:41Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-09T01:11:09.941267Z","submitted_at":"2025-03-31T18:19:41Z","title":"LLMs for Explainable AI: A Comprehensive Survey"},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2504.00125."}