{"as_of":"2026-08-11T05:45:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:84f9915fbd8d7196177a0625b4672dba858266bf34969178707acf25f5e0aed7","coverage":[{"denominator":60,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":60,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T22:22:43.480187Z","state":"measured"},{"denominator":60,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":60,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2608.04548/citation-record","integrity":"/paper/2608.04548/integrity","json":"/paper/2608.04548/citation-record.json","paper":"/paper/2608.04548"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:38.642266Z","title":"Communication, Simulation, and Intelligent Agents: Implications of Personal Intelligent Machines for Medical Education","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:38.642266Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:628497a89933f7657e33ec09073d0eca6d3b921cd3aa0294ebd36ebbb7b43941","observation_id":"59408797-55d0-4679-ac45-5a56fe79be39","resolution":{"observed_at":"2026-08-06T22:22:38.642266Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:38.733806Z","title":"Classification Problem Solving","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:38.733806Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:89213611c16d818c3c1afaf1123f137a0d9a813afd945c1924a758348f73f381","observation_id":"01881f18-33e4-4a8b-af9a-908d6af436a8","resolution":{"observed_at":"2026-08-06T22:22:38.733806Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:38.832256Z","title":", title =","venue":null,"work_id":null,"year":1980},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:38.832256Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:e3aca6794881a428b523a2f12a11d47df532c8fc83d92e170794fa2a6824491e","observation_id":"f4a65a2f-55d0-4ca0-94c5-ea0ab8aab3fb","resolution":{"observed_at":"2026-08-06T22:22:38.832256Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:38.931660Z","title":"New Ways to Make Microcircuits Smaller---Duplicate Entry","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:38.931660Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:bef7a29e6e939d37ddb8f281712f169aeb1cb12f9fdf4f2b4c0e9c3991c8dd3e","observation_id":"402979e9-b0be-4194-8515-225dd548b5a8","resolution":{"observed_at":"2026-08-06T22:22:38.931660Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:39.010905Z","title":"Clancey and Glenn Rennels , abstract =","venue":null,"work_id":null,"year":1984},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:39.010905Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:e91d49b1582470debe03b188198e469fb129aef90bac38c098a8c3a0d2be772d","observation_id":"e7c0c348-b169-48cb-8abd-1eeb27067c82","resolution":{"observed_at":"2026-08-06T22:22:39.010905Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:39.092648Z","title":"and Rennels, Glenn R","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:39.092648Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:3bcfbaf113f635ffe957e8c5891402eeb4a59cbfd21da360d655a413ad34f5ca","observation_id":"4ca12056-b6fc-49bb-983f-7994300b9b27","resolution":{"observed_at":"2026-08-06T22:22:39.092648Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:39.157281Z","title":"Poligon: A System for Parallel Problem Solving","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:39.157281Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:7ed09c80a172177f695ad0ddbeb6bfe2c07aaaf7a700fc4aa23103c7b9a2bb35","observation_id":"60e631ff-a82c-40ac-acab-045f4cd5b172","resolution":{"observed_at":"2026-08-06T22:22:39.157281Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:39.243477Z","title":"Transfer of Rule-Based Expertise through a Tutorial Dialogue","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:39.243477Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:bfef0de1783c0a04c428bc8d9ee977a0265c99535cb69d7bc611c94c3d469a1d","observation_id":"cb6083fe-9eb7-4210-9985-a8b0efd35de3","resolution":{"observed_at":"2026-08-06T22:22:39.243477Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:39.329830Z","title":"The Engineering of Qualitative Models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:39.329830Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:7ad2f4ac4f5e40597135d3e1ab69996a1851df5b7aeee75a39b225644aefda22","observation_id":"de4e6850-9f32-4a7a-b117-51c1fb94ceeb","resolution":{"observed_at":"2026-08-06T22:22:39.329830Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:39.453676Z","title":"2023 , eprint=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:39.453676Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:d26727cbd744e059d819f955f623741707b7c84a39a0c16978df103e48d1cfab","observation_id":"68bfc449-d12e-4c7a-a61e-d88f2549dba2","resolution":{"observed_at":"2026-08-06T22:22:39.453676Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:39.549229Z","title":"Pluto: The 'Other' Red Planet","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:39.549229Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:d5fa1280b07b15d82028481cad5b556fc55f00e86c2bb200927902744b1e0ca8","observation_id":"345777e8-1b33-4c24-a0f7-6516c52fd14b","resolution":{"observed_at":"2026-08-06T22:22:39.549229Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:23:06.508521Z","title":"Intersoft Consulting, Accessed in October , volume=","venue":null,"work_id":"33925480-844f-4a61-a3a2-9b47e8be6242","year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:39.616157Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:6251cbb394a1d44bb10c0d76af68fae91b281e2548e900eab28e71a2cfd88705","observation_id":"d355099b-3609-4a73-8e85-c5fe31c895a4","resolution":{"observed_at":"2026-08-06T22:23:06.533659Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:39.718384Z","title":"Santa Clara Univ","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:39.718384Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:1546bd519ffed9176cf270b90160c47558da43f926216fa1805483c789498723","observation_id":"c18f1a42-e9c0-450b-8a10-16a001d07bbb","resolution":{"observed_at":"2026-08-06T22:22:39.718384Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:39.808845Z","title":"Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:39.808845Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:eaa6355a55cba1275a64e872ea53d3e0e758cc71064e428f9cadb75edb9f0474","observation_id":"5d2d2d30-5ced-4787-aee2-2b9fe87b0d45","resolution":{"observed_at":"2026-08-06T22:22:39.808845Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.00676","last_updated":"2024-01-01T06:04:52Z","snapshot_observed_at":"2026-08-07T08:44:59.348063Z","submitted_at":"2024-01-01T06:04:52Z","title":"Digger: Detecting Copyright Content Mis-usage in Large Language Model Training","version":1},"cited_work":{"arxiv_id":"2401.00676","doi":null,"metadata_source":"pith","pith_arxiv_id":"2401.00676","snapshot_observed_at":"2026-08-06T22:22:43.900505Z","title":"Digger: Detecting Copyright Content Mis-usage in Large Language Model Training","venue":"cs.CR","work_id":"684d7eb2-6a5e-41cf-b5f5-ca39274eae3b","year":2024},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:39.897261Z"},"links":{"cited_paper":"/paper/2401.00676","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:9d18267c6b218bb39cb1303942b438c058d0a98d6d566c20ed9fb2baeebeb384","observation_id":"c999ec79-63c1-4ae2-bb4f-434e6acaa334","resolution":{"observed_at":"2026-08-06T22:22:44.031107Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:23:06.391949Z","title":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=","venue":null,"work_id":"b23e6472-26a3-448a-bcdb-36e13f5b13bc","year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:39.988107Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:74b932b7c12888099fdf8c53e75b2bd218c89bb8fd279ce87db018f366bc12b2","observation_id":"215c4465-b58d-4aaf-ac55-9a422480e20d","resolution":{"observed_at":"2026-08-06T22:23:06.437399Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:23:06.283758Z","title":"Annual International Conference on the Theory and Applications of Cryptographic Techniques , pages=","venue":null,"work_id":"28b73359-2be6-409b-9df6-c68d5dd762d4","year":2020},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:40.079025Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:184be08820c8d63c6eef4e4252e4872d67fde5e80a6ab8d84c0ef9c200b48ed1","observation_id":"fc83ea87-60ba-4027-9609-957c2760676e","resolution":{"observed_at":"2026-08-06T22:23:06.341461Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:40.162604Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:40.162604Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:4f41366f7fff2d087d7fcef449b0bfb935f997540151c4b1f93c56330e318154","observation_id":"4d023110-571b-41c8-aba5-878a087453ad","resolution":{"observed_at":"2026-08-06T22:22:40.162604Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:40.259301Z","title":"2015 IEEE symposium on security and privacy , pages=","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:40.259301Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:1b097dacca7aad1fd284b733f4151f3a8332d187b4fa9af7af052498d3c50237","observation_id":"e16d4ff8-09e0-4581-bffe-9a071dba1863","resolution":{"observed_at":"2026-08-06T22:22:40.259301Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:40.350329Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:40.350329Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:559b64efaa6219f06a01418b2856c67c3f1f2a0d39e57c0b83a1b4cbc5188034","observation_id":"e99aaa55-8642-432e-affc-c9de144736e2","resolution":{"observed_at":"2026-08-06T22:22:40.350329Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:40.441414Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:40.441414Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:defa91d80c254eb9979297a5bb1aa1a96056693e83e3cc9545d17ebb442c32f0","observation_id":"d45db407-f35a-4ec4-b8ca-46002817d4a9","resolution":{"observed_at":"2026-08-06T22:22:40.441414Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:23:06.090714Z","title":"International conference on machine learning , pages=","venue":null,"work_id":"cca834b7-833e-4afe-b8b7-3c9c19358115","year":2021},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:40.525889Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:ac29e795aa49b0a077b74116e11575eb14e302c35a9cbd112b50e11418f5011a","observation_id":"cdb33bb6-ea28-49ef-94d3-77c00c2d5ee6","resolution":{"observed_at":"2026-08-06T22:23:06.189524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2606.12809","last_updated":"2026-06-11T02:09:26Z","snapshot_observed_at":"2026-08-06T20:44:08.729737Z","submitted_at":"2026-06-11T02:09:26Z","title":"MLUBench: A Benchmark for Lifelong Unlearning Evaluation in MLLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2606.12809","snapshot_observed_at":"2026-08-06T22:22:40.595179Z","title":"arXiv preprint arXiv:2606.12809 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:40.595179Z"},"links":{"cited_paper":"/paper/2606.12809","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:726a13592da437d771284be97a70ee2e49aa9ef960ee8019b22fb5d694e1046a","observation_id":"db1f4b70-8b39-47df-85e8-6c5d711c87ef","resolution":{"observed_at":"2026-08-06T22:22:40.595179Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.05938","last_updated":"2026-08-03T04:01:00Z","snapshot_observed_at":"2026-08-06T23:31:04.390937Z","submitted_at":"2026-05-07T09:46:33Z","title":"ICU-Bench:Benchmarking Continual Unlearning in Multimodal Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.05938","snapshot_observed_at":"2026-08-06T22:22:40.672171Z","title":"arXiv preprint arXiv:2605.05938 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:40.672171Z"},"links":{"cited_paper":"/paper/2605.05938","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:5e5dfa72545f734b7cc89ccac60ada59913cc85384346b38a009831ae51522be","observation_id":"5c3cf23b-ee8d-4593-9ffc-0bef56c43b7f","resolution":{"observed_at":"2026-08-06T22:22:40.672171Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:23:05.705822Z","title":"International Conference on Learning Representations , volume=","venue":null,"work_id":"7a3d901b-5bed-4b0b-bf42-a85d6fa61a70","year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:40.753043Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:9f79f8a1d48215d791e137ce82443592987330839cc0782108615e796f7706d6","observation_id":"5efff4f1-c6bd-4ba5-b6d6-770b5ca3b643","resolution":{"observed_at":"2026-08-06T22:23:05.997031Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:23:04.879247Z","title":"International Conference on Learning Representations , volume=","venue":null,"work_id":"d5213c55-1357-4684-8539-b60cbf948d41","year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:40.842359Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:f046e4a8e9cf5d93f9e0cebf7c653e655e0d27317da992491357aea204470713","observation_id":"2ce3001e-bdff-4a3b-b012-4693ccb162ca","resolution":{"observed_at":"2026-08-06T22:23:05.585519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:40.955184Z","title":"arXiv preprint arXiv:2507.01271 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:40.955184Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:fdc7da0055ee2bf6e869b7b2b83d8dab00230489d37a3c281ab032462dc9b34d","observation_id":"139cad28-3691-4977-b30d-cfeade2f89fb","resolution":{"observed_at":"2026-08-06T22:22:40.955184Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:41.056249Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.056249Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:1bb63699255cdb7596454613208f20fb94716ae500c3f3d7888bf1e67b9e65ca","observation_id":"8736480d-19ae-4648-b77f-a4249b70f9bb","resolution":{"observed_at":"2026-08-06T22:22:41.056249Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:23:03.605098Z","title":"Proceedings of the AAAI Conference on Artificial Intelligence , volume=","venue":null,"work_id":"c60715f3-5403-4e60-9b34-8fc7b9dce7c4","year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.103320Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:745d66250a2f14bf4e0447e20173b730663fd850c97dfb43ba8ba4a75474bb78","observation_id":"0fb7f6c4-1acd-4c17-bb39-d5c16e1bddd2","resolution":{"observed_at":"2026-08-06T22:23:03.827049Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:41.156734Z","title":"2022 IEEE 7th European Symposium on Security and Privacy (EuroS&P) , pages=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.156734Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:88ba54da2855bfbb2fcb94aa55cf49a048a350fa4105151fa6671e4f575993c7","observation_id":"03764f81-d880-413f-bb9e-fdf20b881e66","resolution":{"observed_at":"2026-08-06T22:22:41.156734Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:41.211088Z","title":"Conference on Lifelong Learning Agents , pages=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.211088Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:23f5218df8f4c5e003ab3fd77949628b5c57fac7721068739ff4859d85a57543","observation_id":"d17faa42-2c76-4022-be6c-dfe0c06e5674","resolution":{"observed_at":"2026-08-06T22:22:41.211088Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_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},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.06121","snapshot_observed_at":"2026-08-06T22:22:41.268384Z","title":"arXiv preprint arXiv:2401.06121 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.268384Z"},"links":{"cited_paper":"/paper/2401.06121","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:696a48e9ceef4328730732bef1b9f52a7847e5c29cfa6d0112c4a6a2d8466101","observation_id":"356d9e68-e405-4616-9892-27a0709622da","resolution":{"observed_at":"2026-08-06T22:22:41.268384Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:41.322293Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.322293Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:9b66c596ca45291a4523d42e0af4a36b00d0fc8975907378a4efd06f3948f313","observation_id":"0c92b294-61b3-45b3-8329-3f6e99594ef8","resolution":{"observed_at":"2026-08-06T22:22:41.322293Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_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},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.05868","snapshot_observed_at":"2026-08-06T22:22:41.375533Z","title":"arXiv preprint arXiv:2404.05868 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.375533Z"},"links":{"cited_paper":"/paper/2404.05868","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:e95784b315595bd790c1dd3fedfed497c6faeb0470a4637a34ab184db29b8c21","observation_id":"779fba65-6ec7-4f16-98f5-04222c900329","resolution":{"observed_at":"2026-08-06T22:22:41.375533Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.19894","last_updated":"2025-07-26T09:49:57Z","snapshot_observed_at":"2026-08-07T11:18:12.932540Z","submitted_at":"2025-07-26T09:49:57Z","title":"A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.19894","snapshot_observed_at":"2026-08-06T22:22:41.435478Z","title":"arXiv preprint arXiv:2507.19894 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.435478Z"},"links":{"cited_paper":"/paper/2507.19894","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:a59ba044f0313f3c709935491612616214d24de6ad9c3b2e94d96edcae642e19","observation_id":"d97627bc-e239-441a-96e7-1cfd4e584851","resolution":{"observed_at":"2026-08-06T22:22:41.435478Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.18879","last_updated":"2026-06-03T04:33:30Z","snapshot_observed_at":"2026-07-06T23:29:42.583875Z","submitted_at":"2026-05-16T03:10:36Z","title":"ZeroUnlearn: Few-Shot Knowledge Unlearning in Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.18879","snapshot_observed_at":"2026-08-06T22:22:41.495413Z","title":"arXiv preprint arXiv:2605.18879 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.495413Z"},"links":{"cited_paper":"/paper/2605.18879","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:8607cc819e4eb3006600a5b27b718a735970f32c16f728bd0f43d639d91d1f58","observation_id":"31ea6f29-9732-4e71-a275-ef7b5636aba3","resolution":{"observed_at":"2026-08-06T22:22:41.495413Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:23:03.443117Z","title":"Findings of the Association for Computational Linguistics: ACL 2025 , pages=","venue":null,"work_id":"3896c364-247b-4a3a-bba6-92251a96faf2","year":2025},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.558914Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:864e6c9ea15ce1459aef7c70d79cb1375a21744373ca013e87c6d419755787d3","observation_id":"7fd09a3e-4dd8-4eb3-bb03-878e0ba91eaa","resolution":{"observed_at":"2026-08-06T22:23:03.533745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:23:03.275538Z","title":"Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=","venue":null,"work_id":"9b5c703a-9834-4564-b202-cafaf174f3dc","year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.615054Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:9d52769078c4f5577819811dfea0e236a554e0f27176c0db7c5e21c92e3b90ed","observation_id":"c4379c58-41d2-42ed-b6f9-541596df7618","resolution":{"observed_at":"2026-08-06T22:23:03.321645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:41.681883Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.681883Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:083c90e6ac92743d0565e54f7a3ed8fc0da35a0b237a11d6f5df40dffcf8909e","observation_id":"cc7f998b-9dd5-4a53-9f15-90ba59344933","resolution":{"observed_at":"2026-08-06T22:22:41.681883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:41.741067Z","title":"arXiv preprint arXiv:2512.11325 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.741067Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:23e4a270259902f9cbe7a6cb0d55d973de3642519fa2aa61aa79e3f54730a99f","observation_id":"4e16c272-8827-482e-bd51-eeff1e6b8a6b","resolution":{"observed_at":"2026-08-06T22:22:41.741067Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.05909","last_updated":"2026-05-07T09:18:58Z","snapshot_observed_at":"2026-08-11T05:06:53.014877Z","submitted_at":"2026-05-07T09:18:58Z","title":"Null Space Constrained Contrastive Visual Forgetting for MLLM Unlearning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.05909","snapshot_observed_at":"2026-08-06T22:22:41.800399Z","title":"arXiv preprint arXiv:2605.05909 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.800399Z"},"links":{"cited_paper":"/paper/2605.05909","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:325e374a343443ccde84f3c8c37c139e4e1221fead05a3eaa9f481f524c01f82","observation_id":"45159019-cded-4c9b-b158-f66c1ee80ebd","resolution":{"observed_at":"2026-08-06T22:22:41.800399Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14796","last_updated":"2024-12-22T23:47:58Z","snapshot_observed_at":"2026-08-06T14:42:25.772659Z","submitted_at":"2024-06-21T00:13:17Z","title":"MU-Bench: A Multitask Multimodal Benchmark for Machine Unlearning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14796","snapshot_observed_at":"2026-08-06T22:22:41.858745Z","title":"arXiv preprint arXiv:2406.14796 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.858745Z"},"links":{"cited_paper":"/paper/2406.14796","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:7a1c44810eefd89e75c829725fdfc61b37b9d1eb1e710f1257e8386606115bf5","observation_id":"f0989817-216d-49e4-802c-c8caf0c820e6","resolution":{"observed_at":"2026-08-06T22:22:41.858745Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.12545","last_updated":"2025-07-22T08:49:12Z","snapshot_observed_at":"2026-08-07T17:00:28.562414Z","submitted_at":"2025-03-16T15:26:20Z","title":"PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.12545","snapshot_observed_at":"2026-08-06T22:22:41.943816Z","title":"arXiv preprint arXiv:2503.12545 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:41.943816Z"},"links":{"cited_paper":"/paper/2503.12545","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:499cb85efb3a7654eb4b7d5418ccd6c2ad45b995d8df7c5acd187eee2de0481d","observation_id":"2fc58711-bae9-4a9f-b151-eadb1437edab","resolution":{"observed_at":"2026-08-06T22:22:41.943816Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:42.031798Z","title":"Findings of the Association for Computational Linguistics: ACL 2025 , pages=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.031798Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:b76041fc2421d28013acedab53918a6d4ce806a6f9b75bc94984c7e4ce0ceef9","observation_id":"e895f0a0-3646-4490-a3d6-7eeaea91affd","resolution":{"observed_at":"2026-08-06T22:22:42.031798Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:42.086297Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.086297Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:db9fa5eb4e12f9ea57363cef31e43242fe19eb9b864a6f938420ee2dd73b2248","observation_id":"8c307f32-babe-4eb4-87d8-e00b81cc209b","resolution":{"observed_at":"2026-08-06T22:22:42.086297Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:45.094129Z","title":"Engineering Applications of Artificial Intelligence , volume=","venue":null,"work_id":"9f051b89-9c66-46ff-af07-655352b99bb8","year":2025},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.135422Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:6b534dd3beb989542cb99f61e2b1fd0f0c44ad4ee93f03b3fea8c5d7b613a0ef","observation_id":"b21c47fb-9245-40e0-945b-391694c79704","resolution":{"observed_at":"2026-08-06T22:22:45.628532Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:42.188451Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.188451Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:e8d0d9fa0ce3ace8db2383397385cc626e944cb0d72a7b2d685c36c333f9eda4","observation_id":"2e0bc165-b256-4b2f-8bcb-fbf8d3dda1cf","resolution":{"observed_at":"2026-08-06T22:22:42.188451Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:42.257723Z","title":"International conference on machine learning , pages=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.257723Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:789a7caa4c50df1a10e9505df00646dd07afc9412e2e133f43ed222913d03d7f","observation_id":"4d8b72b4-af68-4b0a-bb9b-788b8d3cca02","resolution":{"observed_at":"2026-08-06T22:22:42.257723Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.04089","last_updated":"2023-03-31T15:27:01Z","snapshot_observed_at":"2026-08-03T22:12:27.993418Z","submitted_at":"2022-12-08T05:50:53Z","title":"Editing Models with Task Arithmetic","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.04089","snapshot_observed_at":"2026-08-06T22:22:42.310741Z","title":"arXiv preprint arXiv:2212.04089 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.310741Z"},"links":{"cited_paper":"/paper/2212.04089","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:8dc1ff56ee2b9f7a72c9a6ccdaf03e16d5c4d9dbac75e899e0ef0d123eb3d2f9","observation_id":"20c7078f-68b2-47a3-9d47-072c7e8c7063","resolution":{"observed_at":"2026-08-06T22:22:42.310741Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:44.700816Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":"758e2f1b-eb5b-4ea0-9db8-f32e8e8e63d2","year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.369656Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:5d589fa310ef5c585dfc47eaa17a2b4520bb5bb165496a56aba5927cd369dcf1","observation_id":"e16ed26c-1157-4bdd-9540-85481c4bdced","resolution":{"observed_at":"2026-08-06T22:22:44.844660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:42.423805Z","title":"Forty-first International Conference on Machine Learning , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.423805Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:8597984a0c981e239d3dda422dadce39da30c7a7d1c94163ca2140f8f8de217e","observation_id":"6e83493f-e8c4-4768-834e-140ba2ed7a89","resolution":{"observed_at":"2026-08-06T22:22:42.423805Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.03617","last_updated":"2024-10-04T17:17:19Z","snapshot_observed_at":"2026-07-06T19:27:52.298292Z","submitted_at":"2024-10-04T17:17:19Z","title":"What Matters for Model Merging at Scale?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.03617","snapshot_observed_at":"2026-08-06T22:22:42.551293Z","title":"arXiv preprint arXiv:2410.03617 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.551293Z"},"links":{"cited_paper":"/paper/2410.03617","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:a80ef416629e57d8eb1668146613b8ad0e393cf2652866905105a63ca697a7b4","observation_id":"7f1d5559-9eeb-468a-a5b6-8d723c374db0","resolution":{"observed_at":"2026-08-06T22:22:42.551293Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:44.462693Z","title":null,"venue":null,"work_id":"48473375-fdd6-409f-aac1-da840322d0f2","year":2025},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.614299Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:80fb0d98fd8bdcf7795a33f3abf0dc8787dd073a2ddd0c3552d2d374cae6e543","observation_id":"9a4ca23b-6743-46ba-88c6-275abac36fd4","resolution":{"observed_at":"2026-08-06T22:22:44.580466Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:44.169123Z","title":"Advances in Neural Information Processing Systems , volume=","venue":null,"work_id":"aa9a5bcd-a2a3-4ab9-bad6-57acd7cf88d0","year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.690166Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:eb3bf1777ee3083793dd8aa2b4b85c2f000f8260a5c1b245805188beade16136","observation_id":"9130dbf5-8ca8-4297-ae34-c3599661666e","resolution":{"observed_at":"2026-08-06T22:22:44.307066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:42.783330Z","title":"Proceedings of the Computer Vision and Pattern Recognition Conference , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.783330Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:b374118ededcb81deb837698263e966a98499144459d219f5cfba9788e9bc82e","observation_id":"4c3ed814-6f86-4244-bedf-48ef489e57b5","resolution":{"observed_at":"2026-08-06T22:22:42.783330Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:42.943254Z","title":", author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:42.943254Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:6661c204aa99080867aa099e497bd7bd62253577287905996b0f15344d791edd","observation_id":"066b7776-0a32-4a52-9342-b9b1c3570782","resolution":{"observed_at":"2026-08-06T22:22:42.943254Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:43.038190Z","title":"Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:43.038190Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:644e5ff358b9d3682f9936b3c07325bf13c776a3151d5caf304727b66268525c","observation_id":"1eb0f636-44b5-415e-9178-ad9bfa0a3133","resolution":{"observed_at":"2026-08-06T22:22:43.038190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.12191","last_updated":"2024-10-03T15:54:49Z","snapshot_observed_at":"2026-08-06T05:35:29.109022Z","submitted_at":"2024-09-18T17:59:32Z","title":"Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.12191","snapshot_observed_at":"2026-08-06T22:22:43.162580Z","title":"arXiv preprint arXiv:2409.12191 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:43.162580Z"},"links":{"cited_paper":"/paper/2409.12191","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:663c5af7e5754335029b9f66dbd13d64099321744db44a2aeb923b92eb9738ab","observation_id":"71c34f41-e728-4396-904e-4c79950bf60b","resolution":{"observed_at":"2026-08-06T22:22:43.162580Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.18610","last_updated":"2026-05-18T16:21:41Z","snapshot_observed_at":"2026-07-06T23:29:29.105126Z","submitted_at":"2026-05-18T16:21:41Z","title":"CATA: Continual Machine Unlearning via Conflict-Averse Task Arithmetic","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.18610","snapshot_observed_at":"2026-08-06T22:22:43.309874Z","title":"arXiv preprint arXiv:2605.18610 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:43.309874Z"},"links":{"cited_paper":"/paper/2605.18610","citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:25d904336b1b593d8df0da78e87ce4eb9254c6bfa68bb9d5103ba59a853828c2","observation_id":"6e1d3564-7062-42fd-b345-0f1598ece987","resolution":{"observed_at":"2026-08-06T22:22:43.309874Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:22:43.480187Z","title":"Findings of the Association for Computational Linguistics: NAACL 2025 , pages=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-06T22:22:43.480187Z"},"links":{"citing_paper":"/paper/2608.04548"},"observation_digest":"sha256:b6f5985787f8aae78876c884d07a1c2a16261042326e99313ae39d51a5a8c154","observation_id":"29beede2-0be9-42ae-b944-8f9773eb399e","resolution":{"observed_at":"2026-08-06T22:22:43.480187Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.04548","last_updated":"2026-08-05T07:37:23Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T15:05:36.945582Z","submitted_at":"2026-08-05T07:37:23Z","title":"A Model Merging Approach for Continual MLLM Unlearning"},"reference_resolution":{"displayed":60,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":47,"verified_exact":0,"verified_fuzzy":12},"total_outbound_references":60},"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 11 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2608.04548."}