{"as_of":"2026-08-10T04:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ec0dc6f035ea2df719a1ddf2829676ba692cba817eacc1edd868e3fe39cbb502","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":4,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":4,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:35:52.151902Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-07T15:43:53.904961Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2408.12568","last_updated":"2024-10-23T17:53:24Z","snapshot_observed_at":"2026-07-06T19:04:43.716629Z","submitted_at":"2024-08-22T17:35:18Z","title":"Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.12568","snapshot_observed_at":"2026-08-07T13:35:52.151902Z","title":"Pruning by explaining revisited: Optimizing attribution methods to prune cnns and transformers.CoRR, abs/2408.12568, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.21595","last_updated":"2025-05-27T16:52:29Z","snapshot_observed_at":"2026-08-10T01:35:16.918746Z","submitted_at":"2025-05-27T16:52:29Z","title":"Relevance-driven Input Dropout: an Explanation-guided Regularization Technique","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T13:35:52.151902Z"},"links":{"cited_paper":"/paper/2408.12568","citing_paper":"/paper/2505.21595"},"observation_digest":"sha256:227f85ff6eb30fb5c2b050815d50a7d16a5bfa2faa6f6f15c15f2ed1bfbb4e92","observation_id":"6cc60dc8-51f9-4dd0-9ab5-608eb75ba791","resolution":{"observed_at":"2026-08-07T13:35:52.151902Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.12568","last_updated":"2024-10-23T17:53:24Z","snapshot_observed_at":"2026-07-06T19:04:43.716629Z","submitted_at":"2024-08-22T17:35:18Z","title":"Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers","version":2},"cited_work":{"arxiv_id":"2408.12568","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.12568","snapshot_observed_at":"2026-07-07T15:43:53.904961Z","title":"Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers","venue":"cs.AI","work_id":"0abc704f-fc30-408f-92d2-e54d3958f5fc","year":2024},"citing_paper":{"arxiv_id":"2506.13727","last_updated":"2026-05-07T16:37:45Z","snapshot_observed_at":"2026-07-06T21:43:03.415527Z","submitted_at":"2025-06-16T17:38:36Z","title":"Attribution-Guided Pruning for Insight and Control: Circuit Discovery and Targeted Correction in Small-scale LLMs","version":3},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-19T08:52:45.818050Z"},"links":{"cited_paper":"/paper/2408.12568","citing_paper":"/paper/2506.13727"},"observation_digest":"sha256:de34948e5ae35fe5f6b5bf9771ae4960c1072d50dcebf67e8d1f381181aaacbe","observation_id":"07809702-e91e-42e7-9905-b68c662ecc8a","resolution":{"observed_at":"2026-05-19T08:53:04.131512Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.12568","last_updated":"2024-10-23T17:53:24Z","snapshot_observed_at":"2026-07-06T19:04:43.716629Z","submitted_at":"2024-08-22T17:35:18Z","title":"Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers","version":2},"cited_work":{"arxiv_id":"2408.12568","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.12568","snapshot_observed_at":"2026-07-07T15:43:53.904961Z","title":"Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers","venue":"cs.AI","work_id":"0abc704f-fc30-408f-92d2-e54d3958f5fc","year":2024},"citing_paper":{"arxiv_id":"2606.19993","last_updated":"2026-06-18T09:31:31Z","snapshot_observed_at":"2026-08-07T06:04:20.969024Z","submitted_at":"2026-06-18T09:31:31Z","title":"Activation- and Influence-Aware Ranks (AIR): Function-Preserving SVD Compression for LLMs","version":1},"reference_index":179,"source":"arxiv_source","source_observed_at":"2026-06-26T18:09:17.414031Z"},"links":{"cited_paper":"/paper/2408.12568","citing_paper":"/paper/2606.19993"},"observation_digest":"sha256:070b2d4158c4f7620449f11589321c7f31283ab1898a98c6d14ebdbd63360d65","observation_id":"f23511de-ae2b-4606-bede-aa576824e673","resolution":{"observed_at":"2026-07-04T03:19:31.519208Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.12568","last_updated":"2024-10-23T17:53:24Z","snapshot_observed_at":"2026-07-06T19:04:43.716629Z","submitted_at":"2024-08-22T17:35:18Z","title":"Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers","version":2},"cited_work":{"arxiv_id":"2408.12568","doi":null,"metadata_source":"pith","pith_arxiv_id":"2408.12568","snapshot_observed_at":"2026-07-07T15:43:53.904961Z","title":"Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and Transformers","venue":"cs.AI","work_id":"0abc704f-fc30-408f-92d2-e54d3958f5fc","year":2024},"citing_paper":{"arxiv_id":"2607.05355","last_updated":"2026-07-06T17:33:36Z","snapshot_observed_at":"2026-07-09T23:18:25.416188Z","submitted_at":"2026-07-06T17:33:36Z","title":"Faithfulness to Refusal: A Causal Audit of Neuron Selectors","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-07T15:35:54.665268Z"},"links":{"cited_paper":"/paper/2408.12568","citing_paper":"/paper/2607.05355"},"observation_digest":"sha256:fb930b1a8312bd5464ba3b2086fb7990619ce0c2c30f93204a471fa1d3e863cf","observation_id":"c5aedfff-eb26-4c7e-aadc-5b0068e53646","resolution":{"observed_at":"2026-07-07T15:43:53.906269Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2408.12568/citation-record","integrity":"/paper/2408.12568/integrity","json":"/paper/2408.12568/citation-record.json","paper":"/paper/2408.12568"},"outbound":[],"paper":{"arxiv_id":"2408.12568","last_updated":"2024-10-23T17:53:24Z","latest_version":2,"primary_category":"cs.AI","snapshot_observed_at":"2026-07-06T19:04:43.716629Z","submitted_at":"2024-08-22T17:35:18Z","title":"Pruning By Explaining Revisited: Optimizing Attribution Methods to Prune CNNs and 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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2408.12568."}