{"as_of":"2026-08-09T06:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0170060dc9535ad2d9692116febd1ad632891b0cd532ef58e5be931baf1faaf3","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":9,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":9,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":9,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":9,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:33:33.339776Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-16T22:26:55.093600Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2305.06535","last_updated":"2023-05-11T02:44:29Z","snapshot_observed_at":"2026-08-09T01:14:53.604498Z","submitted_at":"2023-05-11T02:44:29Z","title":"KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment","version":1},"cited_work":{"arxiv_id":"2305.06535","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.06535","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Kga: A general machine unlearning framework based on knowledge gap alignment","venue":null,"work_id":"f516c096-5019-4681-8968-1dd218b0aec1","year":2023},"citing_paper":{"arxiv_id":"2401.06121","last_updated":"2024-01-11T18:57:12Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-01-11T18:57:12Z","title":"TOFU: A Task of Fictitious Unlearning for LLMs","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-05-16T11:07:39.215164Z"},"links":{"cited_paper":"/paper/2305.06535","citing_paper":"/paper/2401.06121"},"observation_digest":"sha256:878f5f450cadfbd8c34efd33f60fe5eef4d00675485391326753237ea4da675a","observation_id":"11b6eb58-33a7-408e-a031-82494fab3c5c","resolution":{"observed_at":"2026-05-16T11:07:39.322764Z","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":"2305.06535","last_updated":"2023-05-11T02:44:29Z","snapshot_observed_at":"2026-08-09T01:14:53.604498Z","submitted_at":"2023-05-11T02:44:29Z","title":"KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment","version":1},"cited_work":{"arxiv_id":"2305.06535","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.06535","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Kga: A general machine unlearning framework based on knowledge gap alignment","venue":null,"work_id":"f516c096-5019-4681-8968-1dd218b0aec1","year":2023},"citing_paper":{"arxiv_id":"2404.05868","last_updated":"2024-10-10T22:00:41Z","snapshot_observed_at":"2026-07-06T17:57:27.510162Z","submitted_at":"2024-04-08T21:05:42Z","title":"Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-16T22:26:55.008143Z"},"links":{"cited_paper":"/paper/2305.06535","citing_paper":"/paper/2404.05868"},"observation_digest":"sha256:cd910e56b6db43f72deacfa3b19512ddf6ed63ca9da01744af44df33fa0faf9a","observation_id":"baf1e9eb-59eb-4bfe-b1f9-e47809871b85","resolution":{"observed_at":"2026-05-16T22:26:55.096149Z","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":"2305.06535","last_updated":"2023-05-11T02:44:29Z","snapshot_observed_at":"2026-08-09T01:14:53.604498Z","submitted_at":"2023-05-11T02:44:29Z","title":"KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.06535","snapshot_observed_at":"2026-08-07T05:33:33.339776Z","title":"Kga: A general machine unlearning framework based on knowledge gap alignment,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.07795","last_updated":"2025-06-09T14:21:25Z","snapshot_observed_at":"2026-08-08T15:28:46.648315Z","submitted_at":"2025-06-09T14:21:25Z","title":"LLM Unlearning Should Be Form-Independent","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:33:33.339776Z"},"links":{"cited_paper":"/paper/2305.06535","citing_paper":"/paper/2506.07795"},"observation_digest":"sha256:9307af93041ef0914ed4c5b26bd9456ff64180b9fefa803c286f289439805d6e","observation_id":"3af76b58-f89e-42d3-a650-ec41e7133e75","resolution":{"observed_at":"2026-08-07T05:33:33.339776Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.06535","last_updated":"2023-05-11T02:44:29Z","snapshot_observed_at":"2026-08-09T01:14:53.604498Z","submitted_at":"2023-05-11T02:44:29Z","title":"KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.06535","snapshot_observed_at":"2026-08-07T04:33:17.015325Z","title":"Kga: A general ma- chine unlearning framework based on knowledge gap alignment","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.10424","last_updated":"2025-06-12T07:23:56Z","snapshot_observed_at":"2026-08-08T16:23:05.158098Z","submitted_at":"2025-06-12T07:23:56Z","title":"SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning against Membership Inference Attacks","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-07T04:33:17.015325Z"},"links":{"cited_paper":"/paper/2305.06535","citing_paper":"/paper/2506.10424"},"observation_digest":"sha256:7e86fe2e6b1fa6526f33de6df9e7a700aa4fe9876cb9baa484477813e89f0f37","observation_id":"f081c439-8270-4fbd-bb41-2cbd5e64565d","resolution":{"observed_at":"2026-08-07T04:33:17.015325Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.06535","last_updated":"2023-05-11T02:44:29Z","snapshot_observed_at":"2026-08-09T01:14:53.604498Z","submitted_at":"2023-05-11T02:44:29Z","title":"KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.06535","snapshot_observed_at":"2026-08-07T04:16:59.140903Z","title":"Kga: A general machine unlearning framework based on knowledge gap alignment.arXiv preprint arXiv:2305.06535,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.11253","last_updated":"2026-05-25T18:27:38Z","snapshot_observed_at":"2026-08-08T18:59:13.519976Z","submitted_at":"2025-06-12T19:51:10Z","title":"Lifting Data-Tracing Machine Unlearning to Knowledge-Tracing for Foundation Models","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T04:16:59.140903Z"},"links":{"cited_paper":"/paper/2305.06535","citing_paper":"/paper/2506.11253"},"observation_digest":"sha256:a200f0fa56a31d669461444ed60106229de1d37d7f2e94dc26a75412dd55dd24","observation_id":"44f2363b-1af1-4026-adb0-4c781af1eced","resolution":{"observed_at":"2026-08-07T04:16:59.140903Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.06535","last_updated":"2023-05-11T02:44:29Z","snapshot_observed_at":"2026-08-09T01:14:53.604498Z","submitted_at":"2023-05-11T02:44:29Z","title":"KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.06535","snapshot_observed_at":"2026-08-07T00:53:52.877255Z","title":"Kga: A general machine unlearning framework based on knowledge gap alignment","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.13048","last_updated":"2025-06-16T02:31:41Z","snapshot_observed_at":"2026-08-08T00:45:51.797303Z","submitted_at":"2025-06-16T02:31:41Z","title":"The Space Complexity of Learning-Unlearning Algorithms","version":1},"reference_index":103,"source":"arxiv_source","source_observed_at":"2026-08-07T00:53:52.877255Z"},"links":{"cited_paper":"/paper/2305.06535","citing_paper":"/paper/2506.13048"},"observation_digest":"sha256:2f5a33614c62498f60853a24cf3391dda1b20705f045b79e80d1fc1ed6b625a5","observation_id":"88b3a212-123a-4b24-bc8b-4abe7f8495a5","resolution":{"observed_at":"2026-08-07T00:53:52.877255Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.06535","last_updated":"2023-05-11T02:44:29Z","snapshot_observed_at":"2026-08-09T01:14:53.604498Z","submitted_at":"2023-05-11T02:44:29Z","title":"KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.06535","snapshot_observed_at":"2026-08-06T19:06:40.121759Z","title":"Kga: A general machine unlearning framework based on knowledge gap alignment","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.07137","last_updated":"2025-07-09T00:51:09Z","snapshot_observed_at":"2026-08-09T04:04:53.987710Z","submitted_at":"2025-07-09T00:51:09Z","title":"Automating Evaluation of Diffusion Model Unlearning with (Vision-) Language Model World Knowledge","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-06T19:06:40.121759Z"},"links":{"cited_paper":"/paper/2305.06535","citing_paper":"/paper/2507.07137"},"observation_digest":"sha256:39ac1b0444ad9e8fb7cf14ecef43e958065e112a77e7ad0e149d5e53be90717b","observation_id":"a9bf22d6-2da8-4362-9248-239444c8f69f","resolution":{"observed_at":"2026-08-06T19:06:40.121759Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.06535","last_updated":"2023-05-11T02:44:29Z","snapshot_observed_at":"2026-08-09T01:14:53.604498Z","submitted_at":"2023-05-11T02:44:29Z","title":"KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.06535","snapshot_observed_at":"2026-08-04T11:27:22.042626Z","title":"Kga: A general machine unlearning framework based on knowledge gap alignment.arXiv preprint arXiv:2305.06535, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2510.04773","last_updated":"2026-06-24T11:41:35Z","snapshot_observed_at":"2026-08-04T11:27:18.543408Z","submitted_at":"2025-10-06T12:49:00Z","title":"Distribution Preference Optimization: A Fine-grained Perspective for LLM Unlearning","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-04T11:27:22.042626Z"},"links":{"cited_paper":"/paper/2305.06535","citing_paper":"/paper/2510.04773"},"observation_digest":"sha256:0047085e8bee62cd05ecdc9b64755df21fbf38f8f93bb4fb62279824b6496c3f","observation_id":"01f61631-3dca-403b-af87-b6b97882fd9d","resolution":{"observed_at":"2026-08-04T11:27:22.042626Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.06535","last_updated":"2023-05-11T02:44:29Z","snapshot_observed_at":"2026-08-09T01:14:53.604498Z","submitted_at":"2023-05-11T02:44:29Z","title":"KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment","version":1},"cited_work":{"arxiv_id":"2305.06535","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2305.06535","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Kga: A general machine unlearning framework based on knowledge gap alignment","venue":null,"work_id":"f516c096-5019-4681-8968-1dd218b0aec1","year":2023},"citing_paper":{"arxiv_id":"2604.17396","last_updated":"2026-04-19T11:59:58Z","snapshot_observed_at":"2026-08-01T18:23:32.699442Z","submitted_at":"2026-04-19T11:59:58Z","title":"Representation-Guided Parameter-Efficient LLM Unlearning","version":1},"reference_index":109,"source":"arxiv_source","source_observed_at":"2026-05-10T06:01:46.885030Z"},"links":{"cited_paper":"/paper/2305.06535","citing_paper":"/paper/2604.17396"},"observation_digest":"sha256:cbb767347315a3d39a4bbbfea8ed70f8194589aea1037eaa4be2a92f2c3538d4","observation_id":"37edfbb1-eaa7-4f1a-bcd5-de577947930e","resolution":{"observed_at":"2026-05-10T06:06:19.321766Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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/2305.06535/citation-record","integrity":"/paper/2305.06535/integrity","json":"/paper/2305.06535/citation-record.json","paper":"/paper/2305.06535"},"outbound":[],"paper":{"arxiv_id":"2305.06535","last_updated":"2023-05-11T02:44:29Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T01:14:53.604498Z","submitted_at":"2023-05-11T02:44:29Z","title":"KGA: A General Machine Unlearning Framework Based on Knowledge Gap Alignment"},"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 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2305.06535."}