{"as_of":"2026-08-09T15:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3842d8b01655ef0932df1eef57b479cb07b9ad503b5aff5967b38980cd297003","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":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":16,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T14:46:42.517303Z","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":"2026-07-04T07:59:40.278596Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-08-07T14:46:42.517303Z","title":"Token pruning in multimodal large language models: Are we solving the right problem?arXiv preprint arXiv:2502.11501, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.17670","last_updated":"2025-07-07T20:01:47Z","snapshot_observed_at":"2026-08-07T22:51:12.206699Z","submitted_at":"2025-05-23T09:36:53Z","title":"Towards General Continuous Memory for Vision-Language Models","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T14:46:42.517303Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2505.17670"},"observation_digest":"sha256:1536c50a95691f0b0a9ce53558c3d0df5bd9259b86546456633b2ad63f76700a","observation_id":"19e41b4e-40f0-450f-bcd8-869d35eab58b","resolution":{"observed_at":"2026-08-07T14:46:42.517303Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-08-07T04:20:32.526592Z","title":"Token pruning in multimodal large language models: Are we solving the right problem? arXiv preprint arXiv:2502.11501, 2025a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.10967","last_updated":"2025-07-01T08:19:08Z","snapshot_observed_at":"2026-08-08T17:11:06.528222Z","submitted_at":"2025-06-12T17:59:09Z","title":"Beyond Attention or Similarity: Maximizing Conditional Diversity for Token Pruning in MLLMs","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T04:20:32.526592Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2506.10967"},"observation_digest":"sha256:4f373fcd265c8e810bc078f83bd6b6be818a63913db4c1e9b97913a2929f3019","observation_id":"e2fd1dc9-808b-4d11-be3a-44643dea61ac","resolution":{"observed_at":"2026-08-07T04:20:32.526592Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-08-07T00:42:53.711824Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.13166","last_updated":"2025-06-16T07:21:11Z","snapshot_observed_at":"2026-08-08T08:38:39.497266Z","submitted_at":"2025-06-16T07:21:11Z","title":"GreedyPrune: Retenting Critical Visual Token Set for Large Vision Language Models","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-07T00:42:53.711824Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2506.13166"},"observation_digest":"sha256:c6ac5ab38826f4c24f3217da51015b4c3a69313186ebdbe1bc2ba627d5ade5d0","observation_id":"76a83887-ed54-4d0b-b283-ee5ffa438ff3","resolution":{"observed_at":"2026-08-07T00:42:53.711824Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-08-06T15:38:44.318646Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.15428","last_updated":"2025-07-21T09:27:45Z","snapshot_observed_at":"2026-08-08T22:42:41.641573Z","submitted_at":"2025-07-21T09:27:45Z","title":"EgoPrune: Efficient Token Pruning for Egomotion Video Reasoning in Embodied Agent","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-06T15:38:44.318646Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2507.15428"},"observation_digest":"sha256:9f228d0b0969f0ec110cf3ccf4c993d09f5959d5b63b80e709bf5f337775615f","observation_id":"47c54d47-f78f-446e-8beb-358f76c9e1b1","resolution":{"observed_at":"2026-08-06T15:38:44.318646Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":"2502.11501","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-07-04T07:59:40.278596Z","title":"arXiv preprint arXiv:2502.11501 , year=","venue":null,"work_id":"e464475a-9870-43b1-8060-a9866dce6505","year":2025},"citing_paper":{"arxiv_id":"2511.22599","last_updated":"2026-04-08T14:04:20Z","snapshot_observed_at":"2026-08-03T23:42:45.825181Z","submitted_at":"2025-11-27T16:27:35Z","title":"DisCEdge: Distributed Context Management for Large Language Models at the Edge","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-17T04:17:31.955480Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2511.22599"},"observation_digest":"sha256:180eefce12074d661a24c55d8a698272b5b783e9f40a7d9b17a934227b7342a3","observation_id":"516ec196-7465-4611-bb3b-b97e1bab1705","resolution":{"observed_at":"2026-05-17T04:19:00.468091Z","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":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":"2502.11501","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-07-04T07:59:40.278596Z","title":"arXiv preprint arXiv:2502.11501 , year=","venue":null,"work_id":"e464475a-9870-43b1-8060-a9866dce6505","year":2025},"citing_paper":{"arxiv_id":"2604.11240","last_updated":"2026-04-13T09:44:52Z","snapshot_observed_at":"2026-08-02T05:19:31.992123Z","submitted_at":"2026-04-13T09:44:52Z","title":"Decoupled Similarity for Task-Aware Token Pruning in Large Vision-Language Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-10T15:15:04.261855Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2604.11240"},"observation_digest":"sha256:2d4d4596f54c4121554f66d731ffe244a6fc3573448b2a9a5b82b3728aae1eb3","observation_id":"e205e0cd-ba2e-4345-9dee-10754d966920","resolution":{"observed_at":"2026-05-11T10:56:05.671079Z","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":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":"2502.11501","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-07-04T07:59:40.278596Z","title":"arXiv preprint arXiv:2502.11501 , year=","venue":null,"work_id":"e464475a-9870-43b1-8060-a9866dce6505","year":2025},"citing_paper":{"arxiv_id":"2604.11627","last_updated":"2026-04-13T15:38:22Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2026-04-13T15:38:22Z","title":"POINTS-Long: Adaptive Dual-Mode Visual Reasoning in MLLMs","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-05-10T15:23:08.671342Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2604.11627"},"observation_digest":"sha256:e208444d41a159ebf80b6127110a2c4914c9ef3732446433f117fc8c7a35df1f","observation_id":"0ddfd256-2beb-4e46-99e7-3ae0b02d2d52","resolution":{"observed_at":"2026-05-11T10:41:04.139640Z","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":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":"2502.11501","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-07-04T07:59:40.278596Z","title":"arXiv preprint arXiv:2502.11501 , year=","venue":null,"work_id":"e464475a-9870-43b1-8060-a9866dce6505","year":2025},"citing_paper":{"arxiv_id":"2604.17087","last_updated":"2026-04-18T17:52:02Z","snapshot_observed_at":"2026-07-06T23:04:14.688737Z","submitted_at":"2026-04-18T17:52:02Z","title":"EvoComp: Learning Visual Token Compression for Multimodal Large Language Models via Semantic-Guided Evolutionary Labeling","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-10T07:00:36.870817Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2604.17087"},"observation_digest":"sha256:ce3b057f9db350c8bd6bf12933233cd139213a80bd5d199f0e19e860fcf8c1d3","observation_id":"1860b541-f2f5-47d7-85f9-0677f2028b8c","resolution":{"observed_at":"2026-05-10T07:01:49.104087Z","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":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":"2502.11501","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-07-04T07:59:40.278596Z","title":"arXiv preprint arXiv:2502.11501 , year=","venue":null,"work_id":"e464475a-9870-43b1-8060-a9866dce6505","year":2025},"citing_paper":{"arxiv_id":"2604.19145","last_updated":"2026-04-21T06:51:08Z","snapshot_observed_at":"2026-07-06T23:05:53.378585Z","submitted_at":"2026-04-21T06:51:08Z","title":"ST-Prune: Training-Free Spatio-Temporal Token Pruning for Vision-Language Models in Autonomous Driving","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-10T03:01:22.470554Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2604.19145"},"observation_digest":"sha256:855a7d5a3ef6875b5feb5caecee7d3863c09ea8f47737c38975e2222923e9031","observation_id":"aa650f97-d347-4b46-90c9-bc6bdeac4abf","resolution":{"observed_at":"2026-05-11T12:46:05.419065Z","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":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":"2502.11501","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-07-04T07:59:40.278596Z","title":"arXiv preprint arXiv:2502.11501 , year=","venue":null,"work_id":"e464475a-9870-43b1-8060-a9866dce6505","year":2025},"citing_paper":{"arxiv_id":"2605.05668","last_updated":"2026-05-07T04:45:52Z","snapshot_observed_at":"2026-07-06T23:18:17.333660Z","submitted_at":"2026-05-07T04:45:52Z","title":"Large Vision-Language Models Get Lost in Attention","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-05-08T11:54:01.224588Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2605.05668"},"observation_digest":"sha256:70901f3c9b50f9f488913d2a6ce591794c1ef44ebc091f42fcd4bdcfc11c1836","observation_id":"a5d929e3-9f52-43a3-a9b2-05d1577c64ae","resolution":{"observed_at":"2026-05-11T19:26:10.080049Z","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":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":"2502.11501","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-07-04T07:59:40.278596Z","title":"arXiv preprint arXiv:2502.11501 , year=","venue":null,"work_id":"e464475a-9870-43b1-8060-a9866dce6505","year":2025},"citing_paper":{"arxiv_id":"2605.20950","last_updated":"2026-05-20T09:37:53Z","snapshot_observed_at":"2026-07-06T23:31:27.989406Z","submitted_at":"2026-05-20T09:37:53Z","title":"Focus-then-Context: Subject-Centric Progressive Visual Token Reduction for Vision-Language Models","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-05-21T05:20:55.448430Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2605.20950"},"observation_digest":"sha256:e86a6c415198f14d154a2616dd0b3f36fdcaff2ef5d9dfae861985bc90d822fb","observation_id":"9cc8022e-c01d-4d40-8cbf-3fa1fc91534d","resolution":{"observed_at":"2026-05-21T05:23:58.605727Z","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":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":"2502.11501","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-07-04T07:59:40.278596Z","title":"arXiv preprint arXiv:2502.11501 , year=","venue":null,"work_id":"e464475a-9870-43b1-8060-a9866dce6505","year":2025},"citing_paper":{"arxiv_id":"2606.21848","last_updated":"2026-07-31T19:30:57Z","snapshot_observed_at":"2026-08-06T23:11:21.421315Z","submitted_at":"2026-06-20T03:12:30Z","title":"Keyless Attention: Value-Space Routing and Value-Only Caching for Efficient Transformers","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-06-26T12:20:42.292943Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2606.21848"},"observation_digest":"sha256:a5ed9ee7eb9be5bdf785f53a24d5ce2258847ff8cfdabc9421ac0ff91ba4a5a0","observation_id":"bf57bfcd-9552-47b0-94db-80ba461bfc23","resolution":{"observed_at":"2026-07-04T07:59:40.279798Z","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":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":"2502.11501","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-07-04T07:59:40.278596Z","title":"arXiv preprint arXiv:2502.11501 , year=","venue":null,"work_id":"e464475a-9870-43b1-8060-a9866dce6505","year":2025},"citing_paper":{"arxiv_id":"2606.27660","last_updated":"2026-07-01T13:33:39Z","snapshot_observed_at":"2026-07-07T00:01:49.598947Z","submitted_at":"2026-06-26T02:33:20Z","title":"MVPruner: Dynamic Token Pruning for Accelerating Multi-view Vision-Language Models in Autonomous Driving","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-29T05:08:46.145616Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2606.27660"},"observation_digest":"sha256:7fbb205295bc770724c542dc1e1cba7e709e0af861108f8940c8e5b632b26969","observation_id":"f965618d-3fd9-4fa3-a16b-f526ae8f687d","resolution":{"observed_at":"2026-06-29T18:23:51.145423Z","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":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":"2502.11501","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-07-04T07:59:40.278596Z","title":"arXiv preprint arXiv:2502.11501 , year=","venue":null,"work_id":"e464475a-9870-43b1-8060-a9866dce6505","year":2025},"citing_paper":{"arxiv_id":"2606.27660","last_updated":"2026-07-01T13:33:39Z","snapshot_observed_at":"2026-07-07T00:01:49.598947Z","submitted_at":"2026-06-26T02:33:20Z","title":"MVPruner: Dynamic Token Pruning for Accelerating Multi-view Vision-Language Models in Autonomous Driving","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-02T21:35:33.280591Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2606.27660"},"observation_digest":"sha256:7c2bb33bf46ddc69255351ae55026f2755b522d87208a91a7aefe360a305376b","observation_id":"1e6d415a-bb83-4e9c-8b6a-dbba3bfc937b","resolution":{"observed_at":"2026-07-02T21:37:24.214614Z","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":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-08-01T08:36:21.154823Z","title":"arXiv preprint arXiv:2502.11501 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.21076","last_updated":"2026-07-23T09:08:57Z","snapshot_observed_at":"2026-08-07T17:22:43.277210Z","submitted_at":"2026-07-23T09:08:57Z","title":"C-PTQ: Fisher-weighted Channel-wise Sensitivity for Post-training Quantization of MLLMs","version":1},"reference_index":296,"source":"arxiv_source","source_observed_at":"2026-08-01T08:36:21.154823Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2607.21076"},"observation_digest":"sha256:5e5bd18651a52031f9ddb587110320234602b6fafadb2a6c9e70aa2e65e7fc34","observation_id":"f99326ed-04e6-4013-9ff7-d76852e4549d","resolution":{"observed_at":"2026-08-01T08:36:21.154823Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.11501","last_updated":"2025-05-29T09:18:35Z","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.11501","snapshot_observed_at":"2026-08-04T00:46:06.737279Z","title":"Wasserthal, J.; Breit, H.-C.; Meyer, M","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.00345","last_updated":"2026-07-31T23:27:39Z","snapshot_observed_at":"2026-08-07T08:23:31.458624Z","submitted_at":"2026-07-31T23:27:39Z","title":"ORCA: ORgan-Centroid Aggregation for Training-Free 3D CT Visual Token Compression","version":1},"reference_index":1963,"source":"pdf_text","source_observed_at":"2026-08-04T00:46:06.737279Z"},"links":{"cited_paper":"/paper/2502.11501","citing_paper":"/paper/2608.00345"},"observation_digest":"sha256:824b9fbe63d250b8c2603f51bf53cc46aaa97b9d8a63ec1c2e326bc7638ca66a","observation_id":"eaf86382-522b-44fd-8584-c050410f15fa","resolution":{"observed_at":"2026-08-04T00:46:06.737279Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2502.11501/citation-record","integrity":"/paper/2502.11501/integrity","json":"/paper/2502.11501/citation-record.json","paper":"/paper/2502.11501"},"outbound":[],"paper":{"arxiv_id":"2502.11501","last_updated":"2025-05-29T09:18:35Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T18:13:30.730921Z","submitted_at":"2025-02-17T07:05:36Z","title":"Token Pruning in Multimodal Large Language Models: Are We Solving the Right Problem?"},"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 16 inbound Pith citation observations for arXiv:2502.11501."}