{"as_of":"2026-08-10T09:06:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2c5fb53a41f191c8c2d7904cb923fa28543728fb2278645bf928515ead98fb53","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":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T05:05:23.168254Z","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":"2026-05-21T12:50:09.318133Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.05602","last_updated":"2024-06-10T09:58:55Z","snapshot_observed_at":"2026-08-07T09:40:05.681390Z","submitted_at":"2024-02-08T12:01:24Z","title":"AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.05602","snapshot_observed_at":"2026-08-09T17:58:33.763604Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.00726","last_updated":"2025-02-02T09:15:27Z","snapshot_observed_at":"2026-08-09T22:10:55.662622Z","submitted_at":"2025-02-02T09:15:27Z","title":"Perspectives for Direct Interpretability in Multi-Agent Deep Reinforcement Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-09T17:58:33.763604Z"},"links":{"cited_paper":"/paper/2402.05602","citing_paper":"/paper/2502.00726"},"observation_digest":"sha256:312f711648b873cb4e0edb04e63ed5859a3e07605dd628a6dc17d1ddcb076811","observation_id":"d558e266-725e-4f94-a38c-89544f374f73","resolution":{"observed_at":"2026-08-09T17:58:33.763604Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05602","last_updated":"2024-06-10T09:58:55Z","snapshot_observed_at":"2026-08-07T09:40:05.681390Z","submitted_at":"2024-02-08T12:01:24Z","title":"AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.05602","snapshot_observed_at":"2026-08-07T23:08:02.183687Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.09674","last_updated":"2025-05-27T08:40:42Z","snapshot_observed_at":"2026-08-09T02:24:15.276351Z","submitted_at":"2025-02-13T06:39:22Z","title":"The Hidden Dimensions of LLM Alignment: A Multi-Dimensional Analysis of Orthogonal Safety Directions","version":4},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-07T23:08:02.183687Z"},"links":{"cited_paper":"/paper/2402.05602","citing_paper":"/paper/2502.09674"},"observation_digest":"sha256:1837c550c9974f06532f1559201cc4f50b5a7ea89d09eb5e80a626e8cf5a1584","observation_id":"e47def67-bff9-4b0b-a1d5-7a51bc53b627","resolution":{"observed_at":"2026-08-07T23:08:02.183687Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05602","last_updated":"2024-06-10T09:58:55Z","snapshot_observed_at":"2026-08-07T09:40:05.681390Z","submitted_at":"2024-02-08T12:01:24Z","title":"AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.05602","snapshot_observed_at":"2026-08-05T13:18:53.385709Z","title":"Attnlrp: attention-aware layer-wise relevance propagation for transformers","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.00749","last_updated":"2025-08-31T08:52:45Z","snapshot_observed_at":"2026-08-08T05:28:11.214250Z","submitted_at":"2025-08-31T08:52:45Z","title":"Causal Interpretation of Sparse Autoencoder Features in Vision","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-05T13:18:53.385709Z"},"links":{"cited_paper":"/paper/2402.05602","citing_paper":"/paper/2509.00749"},"observation_digest":"sha256:3fc8a2c7262dac7f2c3cfea685d8b9924ea0b8a4435217d1d11ed3f9b3059ccc","observation_id":"c52f3fee-5905-469d-b81a-90ab67540a3e","resolution":{"observed_at":"2026-08-05T13:18:53.385709Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05602","last_updated":"2024-06-10T09:58:55Z","snapshot_observed_at":"2026-08-07T09:40:05.681390Z","submitted_at":"2024-02-08T12:01:24Z","title":"AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers","version":2},"cited_work":{"arxiv_id":"2402.05602","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.05602","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Achtibat, S","venue":null,"work_id":"f1c87757-a69c-45e7-8ffc-bccfda64c0aa","year":2024},"citing_paper":{"arxiv_id":"2602.16608","last_updated":"2026-05-19T23:05:11Z","snapshot_observed_at":"2026-08-08T15:26:08.027438Z","submitted_at":"2026-02-18T17:03:10Z","title":"Explainable AI: Context-Aware Layer-Wise Integrated Gradients for Explaining Transformer Models","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-21T12:46:59.419162Z"},"links":{"cited_paper":"/paper/2402.05602","citing_paper":"/paper/2602.16608"},"observation_digest":"sha256:a168edd67507bd47511788e5d580e12ccabaa111a57f2becf4b0eae8a6d7610f","observation_id":"67e1de56-e598-4c84-8873-54c7f847180e","resolution":{"observed_at":"2026-05-21T12:50:09.320641Z","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":"2402.05602","last_updated":"2024-06-10T09:58:55Z","snapshot_observed_at":"2026-08-07T09:40:05.681390Z","submitted_at":"2024-02-08T12:01:24Z","title":"AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers","version":2},"cited_work":{"arxiv_id":"2402.05602","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.05602","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Achtibat, S","venue":null,"work_id":"f1c87757-a69c-45e7-8ffc-bccfda64c0aa","year":2024},"citing_paper":{"arxiv_id":"2604.04500","last_updated":"2026-04-06T07:51:59Z","snapshot_observed_at":"2026-07-30T06:32:02.248567Z","submitted_at":"2026-04-06T07:51:59Z","title":"Saliency-R1: Enforcing Interpretable and Faithful Vision-language Reasoning via Saliency-map Alignment Reward","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-10T19:59:19.379119Z"},"links":{"cited_paper":"/paper/2402.05602","citing_paper":"/paper/2604.04500"},"observation_digest":"sha256:ff47d181e9466c57b822a019f2b0830170a3ce16b163c09c0a8f98dd2a87975c","observation_id":"ebdcc51d-5cdd-4c5e-a1ea-d3e971bd3311","resolution":{"observed_at":"2026-05-10T22:20:47.657759Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05602","last_updated":"2024-06-10T09:58:55Z","snapshot_observed_at":"2026-08-07T09:40:05.681390Z","submitted_at":"2024-02-08T12:01:24Z","title":"AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers","version":2},"cited_work":{"arxiv_id":"2402.05602","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.05602","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Achtibat, S","venue":null,"work_id":"f1c87757-a69c-45e7-8ffc-bccfda64c0aa","year":2024},"citing_paper":{"arxiv_id":"2604.14325","last_updated":"2026-04-15T18:32:32Z","snapshot_observed_at":"2026-07-06T23:02:09.426599Z","submitted_at":"2026-04-15T18:32:32Z","title":"Faithfulness Serum: Mitigating the Faithfulness Gap in Textual Explanations of LLM Decisions via Attribution Guidance","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-10T13:45:51.417645Z"},"links":{"cited_paper":"/paper/2402.05602","citing_paper":"/paper/2604.14325"},"observation_digest":"sha256:abb927372353b81803a99805be6d5aeec3e43b76504a195ce59f294aa8fb6ce7","observation_id":"a01d256c-bd77-4ce1-8186-165fda20ec8c","resolution":{"observed_at":"2026-05-11T11:36:02.808916Z","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":"2402.05602","last_updated":"2024-06-10T09:58:55Z","snapshot_observed_at":"2026-08-07T09:40:05.681390Z","submitted_at":"2024-02-08T12:01:24Z","title":"AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers","version":2},"cited_work":{"arxiv_id":"2402.05602","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.05602","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Achtibat, S","venue":null,"work_id":"f1c87757-a69c-45e7-8ffc-bccfda64c0aa","year":2024},"citing_paper":{"arxiv_id":"2605.05285","last_updated":"2026-07-13T13:01:55Z","snapshot_observed_at":"2026-08-07T19:39:52.311778Z","submitted_at":"2026-05-06T17:38:13Z","title":"Attribution-Guided Continual Learning for Large Language Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-08T16:31:15.098964Z"},"links":{"cited_paper":"/paper/2402.05602","citing_paper":"/paper/2605.05285"},"observation_digest":"sha256:801a9afc9974a9b4256e1b9560ee47dfb8b5f3bfe18c379f6e46cc36caf4b08a","observation_id":"1b58a8ac-98ea-4f97-9e18-0f2ccbf28b39","resolution":{"observed_at":"2026-05-11T18:11:05.482285Z","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"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05602","last_updated":"2024-06-10T09:58:55Z","snapshot_observed_at":"2026-08-07T09:40:05.681390Z","submitted_at":"2024-02-08T12:01:24Z","title":"AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.05602","snapshot_observed_at":"2026-07-14T19:12:02.449224Z","title":"Attnlrp: attention-aware layer-wise relevance propagation for transformers.arXiv preprint arXiv:2402.05602, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2605.05285","last_updated":"2026-07-13T13:01:55Z","snapshot_observed_at":"2026-08-07T19:39:52.311778Z","submitted_at":"2026-05-06T17:38:13Z","title":"Attribution-Guided Continual Learning for Large Language Models","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-14T19:12:02.449224Z"},"links":{"cited_paper":"/paper/2402.05602","citing_paper":"/paper/2605.05285"},"observation_digest":"sha256:6b9068bb3dc149d8e956578ca4c77686e1f1765e10440eed032f26095891c7b4","observation_id":"5221c3a1-69e3-4254-83f9-72d183ce8785","resolution":{"observed_at":"2026-07-14T19:12:02.449224Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05602","last_updated":"2024-06-10T09:58:55Z","snapshot_observed_at":"2026-08-07T09:40:05.681390Z","submitted_at":"2024-02-08T12:01:24Z","title":"AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.05602","snapshot_observed_at":"2026-07-12T00:06:20.034032Z","title":"arXiv preprint arXiv:2402.05602 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.07716","last_updated":"2026-07-04T08:35:07Z","snapshot_observed_at":"2026-08-09T05:17:37.916333Z","submitted_at":"2026-07-04T08:35:07Z","title":"Towards the Explainability of Temporal Graph Networks via Memory Backtracking and Topological Attribution","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-07-12T00:06:20.034032Z"},"links":{"cited_paper":"/paper/2402.05602","citing_paper":"/paper/2607.07716"},"observation_digest":"sha256:9221c3c7fb4389ee1542472bb2e03ae71e0783cba3b101cc1811410193dc608e","observation_id":"b7f77650-6514-49d1-804b-958412c068be","resolution":{"observed_at":"2026-07-12T00:06:20.034032Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.05602","last_updated":"2024-06-10T09:58:55Z","snapshot_observed_at":"2026-08-07T09:40:05.681390Z","submitted_at":"2024-02-08T12:01:24Z","title":"AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.05602","snapshot_observed_at":"2026-08-10T05:05:23.168254Z","title":"Waheed, M","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.07406","last_updated":"2026-08-07T16:54:09Z","snapshot_observed_at":"2026-08-10T08:12:01.339930Z","submitted_at":"2026-08-07T16:54:09Z","title":"Evaluating Explainable AI Methods for Geoscientific Regression: Insights from Applications and the Lorenz-63 System","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T05:05:23.168254Z"},"links":{"cited_paper":"/paper/2402.05602","citing_paper":"/paper/2608.07406"},"observation_digest":"sha256:a5efb78ab87d2cfffacd334a53477e136a0c9a2c3263b7701214c55d0e016440","observation_id":"86850867-02fc-44a8-84c7-4a7724d62b56","resolution":{"observed_at":"2026-08-10T05:05:23.168254Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2402.05602/citation-record","integrity":"/paper/2402.05602/integrity","json":"/paper/2402.05602/citation-record.json","paper":"/paper/2402.05602"},"outbound":[],"paper":{"arxiv_id":"2402.05602","last_updated":"2024-06-10T09:58:55Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T09:40:05.681390Z","submitted_at":"2024-02-08T12:01:24Z","title":"AttnLRP: Attention-Aware Layer-Wise Relevance Propagation for Transformers"},"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 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2402.05602."}