{"as_of":"2026-08-10T23:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:487527aba391c02856719e44bc4f5ecb060cb18bb284afd340b7eeaf7e190aff","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":56,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":56,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":56,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":56,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T20:42:25.294695Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":643,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-10T20:42:25.294695Z","title":"Captum: A unified and generic model interpretability library for pytorch.arXiv preprint arXiv:2009.07896, 2020","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2501.07737","last_updated":"2025-01-13T23:00:40Z","snapshot_observed_at":"2026-08-10T20:34:24.285365Z","submitted_at":"2025-01-13T23:00:40Z","title":"Multi-megabase scale genome interpretation with genetic language models","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-10T20:42:25.294695Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2501.07737"},"observation_digest":"sha256:c2370575c71c034b792b9fe55e0e9749a1a39495f45b3be583fb9014f1a6b6f2","observation_id":"60f0848c-972d-4d11-83dd-a2afa8aba124","resolution":{"observed_at":"2026-08-10T20:42:25.294695Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-10T15:27:09.432427Z","title":"Captum: A unified and generic model interpretability library for pytorch,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2501.14136","last_updated":"2025-01-23T23:26:27Z","snapshot_observed_at":"2026-08-10T18:17:55.607112Z","submitted_at":"2025-01-23T23:26:27Z","title":"Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-10T15:27:09.432427Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2501.14136"},"observation_digest":"sha256:177e29ddf1a08f941d08900b6b2936760b8ca209e39489a78e84d39f011c4378","observation_id":"394d3a8c-9c1d-40ad-b289-c0cb643e548c","resolution":{"observed_at":"2026-08-10T15:27:09.432427Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-09T10:15:24.480669Z","title":"Captum: A unified and generic model interpretability library for pytorch, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.03014","last_updated":"2025-02-05T09:17:48Z","snapshot_observed_at":"2026-08-09T10:09:52.717971Z","submitted_at":"2025-02-05T09:17:48Z","title":"xai_evals : A Framework for Evaluating Post-Hoc Local Explanation Methods","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-09T10:15:24.480669Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2502.03014"},"observation_digest":"sha256:b103f0a28d34d3be6d6071b1c8d37dd7d878d05200a2bdf7ac850dbd37ed2df8","observation_id":"be8a1a2b-da51-4155-91c0-cc3bb18b8c02","resolution":{"observed_at":"2026-08-09T10:15:24.480669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-07T20:33:18.549117Z","title":"Captum: A unified and generic model interpretability library for pytorch,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2502.09788","last_updated":"2025-02-13T21:46:34Z","snapshot_observed_at":"2026-08-09T02:40:51.045239Z","submitted_at":"2025-02-13T21:46:34Z","title":"MANTIS: Detection of Zero-Day Malicious Domains Leveraging Low Reputed Hosting Infrastructure","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T20:33:18.549117Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2502.09788"},"observation_digest":"sha256:fcee10dec4a61e690f85036cdeee71e6cb5cb54554ebe788dc14d1d995ad3cb3","observation_id":"449e9497-2c01-431f-92a5-e161251161a2","resolution":{"observed_at":"2026-08-07T20:33:18.549117Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-10T17:37:46.123862Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.15710","last_updated":"2025-01-21T11:32:39Z","snapshot_observed_at":"2026-08-10T23:33:10.747694Z","submitted_at":"2025-01-21T11:32:39Z","title":"The Process of Categorical Clipping at the Core of the Genesis of Concepts in Synthetic Neural Cognition","version":1},"reference_index":142,"source":"pdf_text","source_observed_at":"2026-08-10T17:37:46.123862Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2502.15710"},"observation_digest":"sha256:4d498f948e30a57e524240631a58a6243f238a79deb6d7a20cf9e28fed815664","observation_id":"7d32ac0f-906c-4aef-a2e4-20a09f087c9c","resolution":{"observed_at":"2026-08-10T17:37:46.123862Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-07T11:15:13.833344Z","title":"Cap- tum: A unified and generic model interpretability library for pytorch,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2506.03267","last_updated":"2025-06-03T18:00:28Z","snapshot_observed_at":"2026-08-10T06:44:06.515755Z","submitted_at":"2025-06-03T18:00:28Z","title":"On the Necessity of Multi-Domain Explanation: An Uncertainty Principle Approach for Deep Time Series Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T11:15:13.833344Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2506.03267"},"observation_digest":"sha256:233ec0460a96172e9a0ce13484368fbdeb4f61126469f4c19379f8d07d4d2a31","observation_id":"0cc1cb44-ca50-47e3-aeba-74542ddc3d0a","resolution":{"observed_at":"2026-08-07T11:15:13.833344Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-07T12:09:59.603146Z","title":"& Reblitz-Richardson, O","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.06330","last_updated":"2025-05-31T01:12:23Z","snapshot_observed_at":"2026-08-09T21:03:12.719569Z","submitted_at":"2025-05-31T01:12:23Z","title":"ExplainBench: A Benchmark Framework for Local Model Explanations in Fairness-Critical Applications","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-07T12:09:59.603146Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2506.06330"},"observation_digest":"sha256:c961b0fa1b1e7c68f98669dbbb2ed9c5e6d27d438fbaa536b4ebad18f5c3445d","observation_id":"b23eb441-ecc0-431a-8836-90bf353fdcec","resolution":{"observed_at":"2026-08-07T12:09:59.603146Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-06T23:12:13.432211Z","title":"Captum: A unified and generic model interpretability library for pytorch","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2506.19630","last_updated":"2025-06-24T13:54:12Z","snapshot_observed_at":"2026-08-10T21:14:01.681881Z","submitted_at":"2025-06-24T13:54:12Z","title":"Why Uncertainty Calibration Matters for Reliable Perturbation-based Explanations","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T23:12:13.432211Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2506.19630"},"observation_digest":"sha256:936db82be7840891f8da964c4812a24976726d4f699de12cb1001ab613c76cf5","observation_id":"ff6668a4-5ad6-4df9-8b84-19ad188b4c25","resolution":{"observed_at":"2026-08-06T23:12:13.432211Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-06T23:52:02.234785Z","title":"Captum: A unified and generic model interpretability library for pytorch, 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.00037","last_updated":"2026-05-28T11:41:22Z","snapshot_observed_at":"2026-08-06T23:42:18.711932Z","submitted_at":"2025-06-18T23:31:05Z","title":"Model Fusion via Retrofitting","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T23:52:02.234785Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2507.00037"},"observation_digest":"sha256:d3eff4251c1f513658ccb0e2feb691bf8ea4d236c8e4d23fcf5e0c7b3a7692fd","observation_id":"4ee5c366-5f06-4853-a83e-5912c687fb29","resolution":{"observed_at":"2026-08-06T23:52:02.234785Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-06T20:53:11.266236Z","title":"Captum: A uniﬁed and generic model interpretability library for pytorch","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.01532","last_updated":"2025-07-02T09:36:26Z","snapshot_observed_at":"2026-08-06T20:46:37.017336Z","submitted_at":"2025-07-02T09:36:26Z","title":"Exploring Pose-based Sign Language Translation: Ablation Studies and Attention Insights","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T20:53:11.266236Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2507.01532"},"observation_digest":"sha256:bd12477a03d6748393184867e0adeb561416d46ce6d9b9880fe450beca65d860","observation_id":"56d7bae6-8bff-4f3a-b1a3-31283c101097","resolution":{"observed_at":"2026-08-06T20:53:11.266236Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-06T20:38:17.355402Z","title":"Captum: A unified and generic model interpretability library for pytorch","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.02342","last_updated":"2025-07-12T07:51:21Z","snapshot_observed_at":"2026-08-09T15:21:49.943484Z","submitted_at":"2025-07-03T06:08:07Z","title":"DeltaSHAP: Explaining Prediction Evolutions in Online Patient Monitoring with Shapley Values","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T20:38:17.355402Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2507.02342"},"observation_digest":"sha256:cb284dae6eac9478f6f94acefe6e9020aabec895b7bb00075a68ba862d9f6628","observation_id":"a466ba9d-d454-449e-a776-d84a0aee5712","resolution":{"observed_at":"2026-08-06T20:38:17.355402Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-06T20:07:55.784952Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.03668","last_updated":"2025-07-04T15:42:51Z","snapshot_observed_at":"2026-08-10T14:11:58.816331Z","submitted_at":"2025-07-04T15:42:51Z","title":"TRACE: Training and Inference-Time Interpretability Analysis for Language Models","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T20:07:55.784952Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2507.03668"},"observation_digest":"sha256:2413596b8634b37732fdfae3037cf1a2c638032c20c65cd0f42fedb4fef26db3","observation_id":"d53c1976-c78f-48f8-aa54-701a67170368","resolution":{"observed_at":"2026-08-06T20:07:55.784952Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-06T15:03:07.539446Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.16991","last_updated":"2025-07-27T18:32:07Z","snapshot_observed_at":"2026-08-08T01:47:27.559238Z","submitted_at":"2025-07-22T19:55:09Z","title":"PyG 2.0: Scalable Learning on Real World Graphs","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T15:03:07.539446Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2507.16991"},"observation_digest":"sha256:1ce77330335a917a55ce0db318bef280acadea1b216c403dedd25246b1066ef4","observation_id":"94634029-be39-4215-9f86-7f3316e02ccf","resolution":{"observed_at":"2026-08-06T15:03:07.539446Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-06T12:04:44.906255Z","title":"Cap- tum: A unified and generic model interpretability library for pytorch,","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2507.22177","last_updated":"2025-07-29T19:15:54Z","snapshot_observed_at":"2026-08-09T20:15:39.918702Z","submitted_at":"2025-07-29T19:15:54Z","title":"POLARIS: Explainable Artificial Intelligence for Mitigating Power Side-Channel Leakage","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T12:04:44.906255Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2507.22177"},"observation_digest":"sha256:570925b1191d725c7d51d48eec8313bee3992bf96097caf1ee97c2f1e7490ccb","observation_id":"5a87f90d-3930-432f-aceb-a0d3943b2112","resolution":{"observed_at":"2026-08-06T12:04:44.906255Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-06T04:23:30.405600Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.03586","last_updated":"2025-08-05T15:53:05Z","snapshot_observed_at":"2026-08-10T06:44:17.030542Z","submitted_at":"2025-08-05T15:53:05Z","title":"DeepFaith: A Domain-Free and Model-Agnostic Unified Framework for Highly Faithful Explanations","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T04:23:30.405600Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2508.03586"},"observation_digest":"sha256:baa140269194f3705dcabf6336e86f9b618242657d224f4be91ce2c95eda824f","observation_id":"7de2baca-6426-449b-82a3-0dd558f66627","resolution":{"observed_at":"2026-08-06T04:23:30.405600Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-06T10:23:12.703222Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.10911","last_updated":"2025-07-31T21:09:36Z","snapshot_observed_at":"2026-08-10T09:40:52.276454Z","submitted_at":"2025-07-31T21:09:36Z","title":"Uncovering Latent Connections in Indigenous Heritage: Semantic Pipelines for Cultural Preservation in Brazil","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T10:23:12.703222Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2508.10911"},"observation_digest":"sha256:eed73e03a5d686fc2c73301cdcbca5037a25aafb6c3afbc8bb316fdf422a7317","observation_id":"fec56d22-86e1-44ca-9907-bfcaf4bcf414","resolution":{"observed_at":"2026-08-06T10:23:12.703222Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T14:21:47.334755Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2508.21512","last_updated":"2025-08-29T10:51:41Z","snapshot_observed_at":"2026-08-08T23:50:08.737946Z","submitted_at":"2025-08-29T10:51:41Z","title":"Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-05T14:21:47.334755Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2508.21512"},"observation_digest":"sha256:9e64bbcbc95708544924570a3078fd0b74e6b51a80203a9445f68ced7cbaee5f","observation_id":"871338d7-f0db-495b-9b11-5da98b5fe558","resolution":{"observed_at":"2026-08-05T14:21:47.334755Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T16:06:48.857320Z","title":"Captum: A unified and generic model interpretabil- ity library for pytorch","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2509.00069","last_updated":"2025-08-26T12:45:13Z","snapshot_observed_at":"2026-08-07T09:02:57.595281Z","submitted_at":"2025-08-26T12:45:13Z","title":"AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T16:06:48.857320Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2509.00069"},"observation_digest":"sha256:7edb8ac8f9c4cb0b6b4f9fc687cc008ef61287a5209ef5e66e2e84081c0d4d48","observation_id":"ab252a9a-7cf1-4b8f-a554-b7b0f9bc8ce6","resolution":{"observed_at":"2026-08-05T16:06:48.857320Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T11:09:48.069017Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.03169","last_updated":"2025-09-03T09:36:18Z","snapshot_observed_at":"2026-08-10T19:15:11.427284Z","submitted_at":"2025-09-03T09:36:18Z","title":"Rashomon in the Streets: Explanation Ambiguity in Scene Understanding","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-05T11:09:48.069017Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2509.03169"},"observation_digest":"sha256:236f7240dc9440a8704c6041f97119a0725f03ae3bb5a813fd37f87971a13633","observation_id":"232a8608-dab6-4b60-9a49-fea26c25b462","resolution":{"observed_at":"2026-08-05T11:09:48.069017Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T10:49:55.811697Z","title":"arXiv preprint arXiv:2009.07896 (2020)","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2509.03649","last_updated":"2025-09-03T18:55:23Z","snapshot_observed_at":"2026-08-10T16:16:13.505201Z","submitted_at":"2025-09-03T18:55:23Z","title":"An Empirical Evaluation of Factors Affecting SHAP Explanation of Time Series Classification","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T10:49:55.811697Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2509.03649"},"observation_digest":"sha256:9e5fb6951aa634e2664396cddcf09ead312f44f08503b7c337d2b039d86f5c66","observation_id":"a9d08b1c-c0a6-4fca-bc8e-e54d23dcc02b","resolution":{"observed_at":"2026-08-05T10:49:55.811697Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-04T18:48:59.399215Z","title":"URL http://arxiv.org/abs/2009.07896","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2509.09619","last_updated":"2025-09-11T17:01:31Z","snapshot_observed_at":"2026-08-10T14:15:14.261267Z","submitted_at":"2025-09-11T17:01:31Z","title":"Functional Groups are All you Need for Chemically Interpretable Molecular Property Prediction","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-04T18:48:59.399215Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2509.09619"},"observation_digest":"sha256:4cebd1b1c47d3e1b659eb6e4f8ebceffec82f70e713073c5a48186606a7ab1f1","observation_id":"2ae08232-5c33-4cca-9edf-d10e70f77e1c","resolution":{"observed_at":"2026-08-04T18:48:59.399215Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2511.23036","last_updated":"2026-04-25T04:06:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-11-28T09:57:44Z","title":"Delta-XAI: A Unified Framework for Explaining Prediction Changes in Online Time Series Monitoring","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-17T04:09:30.442579Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2511.23036"},"observation_digest":"sha256:b6aa42704b44e5495bdac90401a5e4701804a1feac1575045a065e1035db8338","observation_id":"a8ac3910-9732-4e89-839c-dab4077b65e1","resolution":{"observed_at":"2026-05-17T04:11:30.730038Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-03T17:25:00.641433Z","title":"InProceedings of the International Confer- ence on Machine Learning (ICML)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.09730","last_updated":"2026-06-01T14:31:08Z","snapshot_observed_at":"2026-08-03T17:24:59.235521Z","submitted_at":"2025-12-10T15:12:09Z","title":"Interpreto: An Explainability Library for Transformers","version":3},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-03T17:25:00.641433Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2512.09730"},"observation_digest":"sha256:09758f95a7242f9edfc0f12901bb8e7aa3cb444fc503025769aa68519fce9206","observation_id":"3c7f807e-f4dd-4307-8dc0-e3ecdc0bf1be","resolution":{"observed_at":"2026-08-03T17:25:00.641433Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2602.12748","last_updated":"2026-04-13T13:42:26Z","snapshot_observed_at":"2026-07-06T22:45:44.135338Z","submitted_at":"2026-02-13T09:24:03Z","title":"X-SYS: A Reference Architecture for Interactive Explanation Systems","version":3},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-15T22:44:44.720768Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2602.12748"},"observation_digest":"sha256:3e77329be48b1ef43b1b327804de15046fecd5d83fdcc803880cccb01ed1b0cd","observation_id":"f39c2e4a-6438-4640-a935-de63d47c65fb","resolution":{"observed_at":"2026-05-15T22:46:46.037718Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2603.01944","last_updated":"2026-03-02T14:57:52Z","snapshot_observed_at":"2026-08-02T23:45:35.889904Z","submitted_at":"2026-03-02T14:57:52Z","title":"MobileMold: A Smartphone-Based Microscopy Dataset for Food Mold Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-15T18:06:09.012289Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2603.01944"},"observation_digest":"sha256:de017dc57ed9b8142747b744a092b89893d9bebd08a86a0351680932f608bf02","observation_id":"fc210c33-526e-44a7-8b8e-7693bb03efad","resolution":{"observed_at":"2026-05-15T18:06:25.224433Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-07-15T00:00:46.717506Z","title":"Captum: A unified and generic model interpretability library for PyTorch","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2603.09787","last_updated":"2026-05-29T11:55:04Z","snapshot_observed_at":"2026-08-06T09:51:54.438986Z","submitted_at":"2026-03-10T15:21:52Z","title":"What is Missing? Explaining Neurons Activated by Absent Concepts","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-15T00:00:46.717506Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2603.09787"},"observation_digest":"sha256:12e7c9478f868047945d47b39f493eb3d4b5ffe766e0670379a8d298e6bcbfe7","observation_id":"0d5dc86e-b348-493e-8166-5bc0637d6939","resolution":{"observed_at":"2026-07-15T00:00:46.717506Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2604.02532","last_updated":"2026-04-02T21:32:54Z","snapshot_observed_at":"2026-07-06T22:51:53.458444Z","submitted_at":"2026-04-02T21:32:54Z","title":"Feature Attribution Stability Suite: How Stable Are Post-Hoc Attributions?","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-13T21:29:35.075916Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2604.02532"},"observation_digest":"sha256:064348bb033f53c54e74d926585a523f1818249a818a32d1fd28a43cdf6a6816","observation_id":"72a83a12-8877-4008-8da4-fbfe50365e53","resolution":{"observed_at":"2026-05-13T21:33:18.506723Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2604.21184","last_updated":"2026-04-23T01:00:58Z","snapshot_observed_at":"2026-08-02T17:36:07.753451Z","submitted_at":"2026-04-23T01:00:58Z","title":"Predicting the thermodynamics in the chromosphere from the translation of SDO data into the IRIS$^{2}$ inversion results using a visual transformer model","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-05-09T21:17:24.132264Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2604.21184"},"observation_digest":"sha256:16f8559583dc8f004409017b157cb4cb80452aa2f6251471c970481625881e78","observation_id":"301160ec-3afc-4870-87e3-7a7f860bc7a5","resolution":{"observed_at":"2026-05-09T21:18:24.839333Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2605.00764","last_updated":"2026-05-01T16:25:13Z","snapshot_observed_at":"2026-07-06T23:14:06.327027Z","submitted_at":"2026-05-01T16:25:13Z","title":"Modeling Subjective Urban Perception with Human Gaze","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-09T19:12:54.038217Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2605.00764"},"observation_digest":"sha256:279d334bb13fa070e289f48c840c59bd64f15c832ab184cd7b52fff8d128ef99","observation_id":"2d8c27f5-92bf-4063-a91a-431ae92c97c3","resolution":{"observed_at":"2026-05-11T15:47:16.267281Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2605.05026","last_updated":"2026-05-06T15:22:52Z","snapshot_observed_at":"2026-07-06T23:17:43.402046Z","submitted_at":"2026-05-06T15:22:52Z","title":"Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-05-08T18:06:16.734687Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2605.05026"},"observation_digest":"sha256:45fbff55ff9f168672f77092800ad3230733c448cb972d8296755e813b749152","observation_id":"0d85d1c6-d496-4a35-9047-780ffee8fb6a","resolution":{"observed_at":"2026-05-09T06:50:39.537591Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2605.10142","last_updated":"2026-05-11T07:51:33Z","snapshot_observed_at":"2026-07-06T23:22:08.560919Z","submitted_at":"2026-05-11T07:51:33Z","title":"Scaling Vision Models Does Not Consistently Improve Localisation-Based Explanation Quality","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-12T04:15:54.437833Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2605.10142"},"observation_digest":"sha256:e688b98c84a6425a2b88736453dc66d9f1691de10520650c02966ab53ca4f596","observation_id":"120959ae-135f-430a-92f0-452f560f28fa","resolution":{"observed_at":"2026-05-12T06:26:26.165770Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2605.11093","last_updated":"2026-05-11T18:01:36Z","snapshot_observed_at":"2026-07-06T23:22:57.012338Z","submitted_at":"2026-05-11T18:01:36Z","title":"Enabling Performant and Flexible Model-Internal Observability for LLM Inference","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-13T07:17:13.823853Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2605.11093"},"observation_digest":"sha256:2f06ac648b53c8cf2513a80b7ce5413ac428688a7f82d7e11de496f465747dfe","observation_id":"0f9fe856-3481-48aa-9f44-c62bf7520956","resolution":{"observed_at":"2026-05-13T07:17:27.974805Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2605.11206","last_updated":"2026-05-13T08:57:14Z","snapshot_observed_at":"2026-08-05T18:10:32.435834Z","submitted_at":"2026-05-11T20:21:04Z","title":"Instructions Shape Production of Language, not Processing","version":1},"reference_index":246,"source":"arxiv_source","source_observed_at":"2026-05-13T03:09:02.902912Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2605.11206"},"observation_digest":"sha256:e33a662bdbfe536f3d24265474113391c80e06678d89b427cd395b416efa6151","observation_id":"a0b53bd3-089a-4ceb-a608-33d73ef37afa","resolution":{"observed_at":"2026-05-13T03:12:09.637783Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2605.11206","last_updated":"2026-05-13T08:57:14Z","snapshot_observed_at":"2026-08-05T18:10:32.435834Z","submitted_at":"2026-05-11T20:21:04Z","title":"Instructions Shape Production of Language, not Processing","version":2},"reference_index":246,"source":"arxiv_source","source_observed_at":"2026-05-14T21:02:02.135970Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2605.11206"},"observation_digest":"sha256:65163ea7a5e59657f29c74b9d12e8479a2d19b155565ac2b3aea6f4a385e4485","observation_id":"7d3e89a3-38e3-42a1-a4c6-05d50c3c828f","resolution":{"observed_at":"2026-05-14T21:02:58.766062Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2605.13511","last_updated":"2026-05-31T14:41:44Z","snapshot_observed_at":"2026-07-06T23:25:07.022065Z","submitted_at":"2026-05-13T13:30:12Z","title":"Many-Shot CoT-ICL: Making In-Context Learning Truly Learn","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-05-14T19:15:44.379686Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2605.13511"},"observation_digest":"sha256:9b46d2d2cc5fba17987a45f9bf7f349a83f911e07071bd118775a0d05940595d","observation_id":"03bb2df3-9733-4949-9ea6-4be144ecdff7","resolution":{"observed_at":"2026-05-14T19:17:50.528605Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2605.14884","last_updated":"2026-05-15T02:04:33Z","snapshot_observed_at":"2026-08-04T00:52:04.092863Z","submitted_at":"2026-05-14T14:28:24Z","title":"AIMing for Standardised Explainability Evaluation in GNNs: A Framework and Case Study on Graph Kernel Networks","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-05-19T17:26:39.809292Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2605.14884"},"observation_digest":"sha256:2f5cba588611316222cd6458071de2fc3612e47805982c34c10e5f8145db6c32","observation_id":"45eebebc-52f1-4905-a48e-e761e2aaf954","resolution":{"observed_at":"2026-05-19T17:27:41.266956Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2605.15172","last_updated":"2026-05-14T17:56:22Z","snapshot_observed_at":"2026-08-06T20:13:00.393114Z","submitted_at":"2026-05-14T17:56:22Z","title":"MetaBackdoor: Exploiting Positional Encoding as a Backdoor Attack Surface in LLMs","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-15T03:04:27.417831Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2605.15172"},"observation_digest":"sha256:75d6542b80e48814d2272aae5f76b9c2b909d6e9c0156fb0d446e950c44d128d","observation_id":"484c9a2b-9cb9-40fc-ac4b-27574fd04dd1","resolution":{"observed_at":"2026-05-15T03:09:44.639687Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2605.19258","last_updated":"2026-05-19T02:10:04Z","snapshot_observed_at":"2026-07-06T23:30:02.207108Z","submitted_at":"2026-05-19T02:10:04Z","title":"ExECG: An Explainable AI Framework for ECG models","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-05-20T07:35:31.869977Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2605.19258"},"observation_digest":"sha256:18fbe13abbbbc4ae9b81a265f2e20db9b8e4fc3b058c3b446674ba9b1faaaf03","observation_id":"c975b2f4-b882-4a8f-8f2e-0934d55ced10","resolution":{"observed_at":"2026-05-20T07:38:09.547472Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2605.24742","last_updated":"2026-05-23T21:33:17Z","snapshot_observed_at":"2026-07-06T23:34:47.734159Z","submitted_at":"2026-05-23T21:33:17Z","title":"Aligning Molecular Graph Explanations with Chemical Identity via InChIfied Invariants","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-06-30T14:12:03.734109Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2605.24742"},"observation_digest":"sha256:41682e933144d52ef8b102c727063d8e41224c73e8615895ecdc5396a9763637","observation_id":"113bfc4d-cd83-45c8-8db8-9a8c052101a4","resolution":{"observed_at":"2026-06-30T14:14:45.436135Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2605.29076","last_updated":"2026-06-02T23:33:43Z","snapshot_observed_at":"2026-08-06T19:53:11.162808Z","submitted_at":"2026-05-27T20:29:41Z","title":"Structured Prompt Optimization Meets Reinforcement Learning for Global and Local Interpretability over Complex Text","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-29T12:25:21.687730Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2605.29076"},"observation_digest":"sha256:a233201e54358d611adcbe26a9b8332c6d1c0a89f459843b0b649c22da3a1cb4","observation_id":"268ac960-6b8a-4e4c-b1fb-9d07a92a17e9","resolution":{"observed_at":"2026-06-29T12:33:24.931605Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2606.07180","last_updated":"2026-06-05T11:44:25Z","snapshot_observed_at":"2026-08-05T22:45:46.712775Z","submitted_at":"2026-06-05T11:44:25Z","title":"OPTIMUS-Prime: Minimal and Sufficient Concept Explanations for Deep Vision Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-27T21:58:41.494980Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2606.07180"},"observation_digest":"sha256:4caeef61569f17e79a0e49d3441dd88a6c063111c30051ff7309941dec0138e4","observation_id":"3c337d23-9e11-4d33-aea5-42f75ae0e1bc","resolution":{"observed_at":"2026-07-02T17:37:14.501224Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2606.08123","last_updated":"2026-06-06T11:57:16Z","snapshot_observed_at":"2026-08-06T19:51:46.557668Z","submitted_at":"2026-06-06T11:57:16Z","title":"Human-Centered Benchmarking of Driver Monitoring Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-06-27T19:59:45.757893Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2606.08123"},"observation_digest":"sha256:9d0afd94a9a16bc45d2c6c18e75cabc50679c0f564f1041f9031abfd0976be39","observation_id":"6bd0fa80-ec06-45b5-bd51-bbc22910fa01","resolution":{"observed_at":"2026-07-02T20:57:23.681709Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2606.09936","last_updated":"2026-06-07T19:27:04Z","snapshot_observed_at":"2026-08-02T13:18:21.055197Z","submitted_at":"2026-06-07T19:27:04Z","title":"One Lens, Many Worlds : A Capability-Typed Interface for World-Model Interpretability","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-27T18:38:48.128635Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2606.09936"},"observation_digest":"sha256:5d607a00236be6e241acddefff2a8777381371cfba5678521c5585f2f08457c1","observation_id":"d3cfa648-8549-4d6c-a335-4ef03fb28a66","resolution":{"observed_at":"2026-07-02T22:47:26.198115Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2606.10900","last_updated":"2026-06-09T14:11:40Z","snapshot_observed_at":"2026-08-08T06:03:34.127351Z","submitted_at":"2026-06-09T14:11:40Z","title":"Personalized Deep Learning for Short-Term Forecasting of Impending Atrial Fibrillation from Continuous Wearable ECG Signals","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-06-27T12:19:23.084167Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2606.10900"},"observation_digest":"sha256:683e5b4c2a017348eba2bc36dee148839dfef1fcf2f1dd8bb57a2c3c9be90ed3","observation_id":"dda53e0d-ee90-4cbf-bf33-c24a755ea2cb","resolution":{"observed_at":"2026-07-03T06:57:43.424113Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2606.29346","last_updated":"2026-06-28T11:29:15Z","snapshot_observed_at":"2026-08-06T15:56:57.654202Z","submitted_at":"2026-06-28T11:29:15Z","title":"Reliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific Models","version":1},"reference_index":144,"source":"arxiv_source","source_observed_at":"2026-06-30T08:20:23.645840Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2606.29346"},"observation_digest":"sha256:8991644cc67ea76df833930c6adf19c2f0f38d220abc0a628af70f0e89c0093e","observation_id":"7d6334e5-e2cc-4f48-8840-89824b116f15","resolution":{"observed_at":"2026-06-30T08:24:26.421005Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":"2009.07896","doi":"10.48550/arxiv.2009.07896","metadata_source":"arxiv_reference","pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":"arXiv (Cornell University)","work_id":"6eefb382-d91c-4d14-8d89-808b103c4973","year":2009},"citing_paper":{"arxiv_id":"2606.32008","last_updated":"2026-06-30T17:43:44Z","snapshot_observed_at":"2026-08-08T09:19:54.150532Z","submitted_at":"2026-06-30T17:43:44Z","title":"Surrogate Fidelity: When Can Open LLMs Explain Closed Ones?","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-07-01T06:15:42.011563Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2606.32008"},"observation_digest":"sha256:98851e52a12a69b31ace30744e8e4fc6eaebd8bd4761fb9ea34cb0fc970319fc","observation_id":"985da47c-c86d-4548-95e0-e9c922b85ad4","resolution":{"observed_at":"2026-07-01T09:45:40.087103Z","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":"2026-07-14T06:21:55.812831+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-14T06:21:55.812831+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-07-12T07:05:03.545756Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.02782","last_updated":"2026-07-02T21:31:09Z","snapshot_observed_at":"2026-08-09T17:08:07.233764Z","submitted_at":"2026-07-02T21:31:09Z","title":"A Preliminary Study on Explaining Risk of Code Changes using LLM-Based Prediction Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-12T07:05:03.545756Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2607.02782"},"observation_digest":"sha256:1dd7c2c3c2ab1c3d446d086c8358b191d1a3470683420924efdb34d09c8f757e","observation_id":"e0be944f-2cb6-45d7-87d9-65a176beb3fc","resolution":{"observed_at":"2026-07-12T07:05:03.545756Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-07-11T18:45:31.095808Z","title":"Captum: A unified and generic model interpretability library for PyTorch.arXiv preprint arXiv:2009.07896,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.04487","last_updated":"2026-07-05T20:19:09Z","snapshot_observed_at":"2026-08-06T23:03:47.079826Z","submitted_at":"2026-07-05T20:19:09Z","title":"Two Black Boxes, One Solver: Encoder Probing and Decoder Attribution for Neural Multi-Attribute VRP under Hard-Mask and Recourse Decoders","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-11T18:45:31.095808Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2607.04487"},"observation_digest":"sha256:f861ec9a998cbdfbf873e7da7db73eec11404b3e91e20781216923f4068783c1","observation_id":"4fd95cc2-1897-4b00-9aeb-fd6094cdf015","resolution":{"observed_at":"2026-07-11T18:45:31.095808Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-07-11T10:50:54.419477Z","title":"arXiv , author=","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2607.04963","last_updated":"2026-07-06T11:50:06Z","snapshot_observed_at":"2026-08-03T04:57:20.508738Z","submitted_at":"2026-07-06T11:50:06Z","title":"STAPO: Selective Trajectory-Aware Policy Optimization for LLM Agent Training","version":1},"reference_index":102,"source":"arxiv_source","source_observed_at":"2026-07-11T10:50:54.419477Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2607.04963"},"observation_digest":"sha256:5e31f057c8a1e12951ec6475680c1e19092e62e28f736482a1f74b9595dff22c","observation_id":"71d2b963-f7e8-4720-94d3-f7698b19bfc4","resolution":{"observed_at":"2026-07-11T10:50:54.419477Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-07-14T04:05:21.655970Z","title":"arXiv (2020)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.11656","last_updated":"2026-07-14T15:16:45Z","snapshot_observed_at":"2026-07-17T23:19:05.845964Z","submitted_at":"2026-07-13T15:05:26Z","title":"Imputation-free transformer learning enables robust Alzheimer's disease prediction and calibrated uncertainty quantification across heterogeneous clinical cohorts","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-14T04:05:21.655970Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2607.11656"},"observation_digest":"sha256:221ac88d83851588b2e623b815b30a25de9356153da22aeebe2740cb87398e72","observation_id":"86c66dee-8041-4387-aa86-6188915599d2","resolution":{"observed_at":"2026-07-14T04:05:21.655970Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-01T22:25:15.014884Z","title":"Kokhlikyan et al","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2607.15774","last_updated":"2026-07-22T11:50:29Z","snapshot_observed_at":"2026-08-01T22:25:12.436224Z","submitted_at":"2026-07-17T09:09:08Z","title":"Scaling Time Series Classification via XAI-Driven Data Reduction","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T22:25:15.014884Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2607.15774"},"observation_digest":"sha256:f52b51e2321a52c9a3826bdde0da2f71885cb225bd502c58c8dac70aaedbe8e2","observation_id":"b93a12a9-cba1-4834-b0d8-11336fde48bb","resolution":{"observed_at":"2026-08-01T22:25:15.014884Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-01T00:54:33.073227Z","title":"Captum: A unified and generic model interpretability library for pytorch.arXiv:2009.07896, 2020","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2607.26014","last_updated":"2026-07-28T17:27:36Z","snapshot_observed_at":"2026-08-10T18:34:10.844685Z","submitted_at":"2026-07-28T17:27:36Z","title":"Automated Solar Radio Burst Detection Using Deep Learning on Augmented e-Callisto Data","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-01T00:54:33.073227Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2607.26014"},"observation_digest":"sha256:22c803d6c5c3ff7ed43d57ab55104817ab5b06abe7b1fbe8e58c9e76b186c240","observation_id":"13eed409-2887-40b5-836e-4f86cb9ab377","resolution":{"observed_at":"2026-08-01T00:54:33.073227Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-03T17:28:10.565466Z","title":"InFindings of the Associa- tion for Computational Linguistics: EMNLP 2025, pages 2239–2259, Suzhou, China","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.28906","last_updated":"2026-07-31T00:05:36Z","snapshot_observed_at":"2026-08-05T23:12:06.546574Z","submitted_at":"2026-07-31T00:05:36Z","title":"Token-Level Diagnosis of Sycophancy in LLMs with Attribution-Guided Steering","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-03T17:28:10.565466Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2607.28906"},"observation_digest":"sha256:4481ec0a2ad7ad33c16f595e89b4e94e0d5bdb2122677f47843f2979737a89a8","observation_id":"31bd79d3-1080-442a-88cb-b4bde562023e","resolution":{"observed_at":"2026-08-03T17:28:10.565466Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T00:44:49.966363Z","title":"arXiv preprint arXiv:2009.07896 , year=","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2608.00566","last_updated":"2026-08-01T10:03:14Z","snapshot_observed_at":"2026-08-06T23:17:27.979846Z","submitted_at":"2026-08-01T10:03:14Z","title":"Crushing the Evidence: A Dual-Penalty Evasion Framework for Fooling White-Box Explainable AI Auditors","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-05T00:44:49.966363Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2608.00566"},"observation_digest":"sha256:c628862716608d8ff2edcf526d331668a3e5817ce6cee24e05415e44f2e2aedc","observation_id":"0d7a3759-df69-4c02-b1cb-eeb58f423233","resolution":{"observed_at":"2026-08-05T00:44:49.966363Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-04T08:06:53.050998Z","title":"Kokhlikyan, V","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2608.02396","last_updated":"2026-08-03T15:39:36Z","snapshot_observed_at":"2026-08-08T19:40:09.713938Z","submitted_at":"2026-08-03T15:39:36Z","title":"Does Explainability Transfer? A Controlled Benchmark of Attribution Methods on Vision Transformers and CNNs","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-04T08:06:53.050998Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2608.02396"},"observation_digest":"sha256:0c12fe2313a534639bdf10a6cf735bdd170a363271958de86117f6994cd0d9a1","observation_id":"84eb791b-6aff-4e31-91d1-56f43f94008f","resolution":{"observed_at":"2026-08-04T08:06:53.050998Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07896","snapshot_observed_at":"2026-08-05T05:39:25.732256Z","title":null,"venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2608.03927","last_updated":"2026-08-04T16:59:30Z","snapshot_observed_at":"2026-08-09T13:59:00.683113Z","submitted_at":"2026-08-04T16:59:30Z","title":"A Physics-Flavored Transformer Network for Parametrizing Contraction Dynamics of Engineered Skeletal Muscle Tissues","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-05T05:39:25.732256Z"},"links":{"cited_paper":"/paper/2009.07896","citing_paper":"/paper/2608.03927"},"observation_digest":"sha256:6964eced880e328116f8643106a2d0880fa2e3ed91a436bad696ae520a9d8c9d","observation_id":"1b3eae41-c358-42b9-ac2f-da8480656b37","resolution":{"observed_at":"2026-08-05T05:39:25.732256Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2009.07896/citation-record","integrity":"/paper/2009.07896/integrity","json":"/paper/2009.07896/citation-record.json","paper":"/paper/2009.07896"},"outbound":[],"paper":{"arxiv_id":"2009.07896","last_updated":"2020-09-16T18:57:57Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T09:56:16.122954Z","submitted_at":"2020-09-16T18:57:57Z","title":"Captum: A unified and generic model interpretability library for PyTorch"},"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 56 inbound Pith citation observations for arXiv:2009.07896."}