{"as_of":"2026-08-09T08:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1925a179707baff25b27db096a4caa8b561bfaea57f65c7d3e03ec0be88ee603","coverage":[{"denominator":62,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":62,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T11:43:17.032956Z","state":"measured"},{"denominator":62,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":62,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2607.19811/citation-record","integrity":"/paper/2607.19811/integrity","json":"/paper/2607.19811/citation-record.json","paper":"/paper/2607.19811"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T11:43:10.758977Z","title":"Sam 2: Segment anything in images and videos,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:10.758977Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:664624b11cb6dd335e514c01a64d3afc1e5c912ff51d101af744202aba88fe45","observation_id":"b28c428e-bd6e-4cf8-82ff-3854b89cac11","resolution":{"observed_at":"2026-08-01T11:43:10.758977Z","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":"2026-08-01T11:43:10.801210Z","title":"Segment anything,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:10.801210Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:26e10423731b0e683279b038b9e3f7547dd0a8e23d9d4f648375bb919e5d9f7f","observation_id":"89cba461-15a6-42c8-94cf-ccf6313b6778","resolution":{"observed_at":"2026-08-01T11:43:10.801210Z","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":"2026-08-01T11:43:10.853646Z","title":"A benchmark dataset and evaluation methodology for video object segmentation,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:10.853646Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:24d0646868f8977617977eb0cd54e82b23c7dfa3a3c0269fa85657a65f7c54b7","observation_id":"6eea5a55-a869-4526-8f08-9b422ee29b99","resolution":{"observed_at":"2026-08-01T11:43:10.853646Z","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":"2026-08-01T11:43:10.905594Z","title":"Rethinking space-time networks with improved memory coverage for efficient video object segmentation,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:10.905594Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:1f23fff26ad0e6068fc14332105eb361f9da1f9a635cf612df6495cfa39e9712","observation_id":"08fc176f-df6f-40bb-8e59-4ff096a13b32","resolution":{"observed_at":"2026-08-01T11:43:10.905594Z","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":"2026-08-01T11:43:10.958548Z","title":"Xmem: Long-term video object segmentation with an atkinson-shiffrin memory model,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:10.958548Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:e74b75612a08e1f252ed6b028b0ce2b771d8185517aa766a1f6ca36d2b032a33","observation_id":"0b07962b-95c2-4401-bba3-3d987b8bf62b","resolution":{"observed_at":"2026-08-01T11:43:10.958548Z","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":"2026-08-01T11:43:11.012093Z","title":"Putting the object back into video object segmentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:11.012093Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:0506426493fb7c02005395e5b05a61bedae7a0ff1a6048fb772f9e7d1e8b65d2","observation_id":"960d5bb8-17bc-4736-ad35-ed8a748a5239","resolution":{"observed_at":"2026-08-01T11:43:11.012093Z","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":"2026-08-01T11:43:11.063489Z","title":"Efficient-sam2: Accelerating sam2 with object-aware visual encoding and memory retrieval,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:11.063489Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:d9044dde5e5ca3a32ddf9f0b1cf5654b593285454cf0771f74f04e297bc743c0","observation_id":"ce6ae70c-c99c-44bc-bc62-8f55e4451f9b","resolution":{"observed_at":"2026-08-01T11:43:11.063489Z","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":"2026-08-01T11:43:11.139583Z","title":"Fast sam2 with text-driven token pruning,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:11.139583Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:756ead2a27f473b64eca2afbba3b683b768c27eac9c194644a4adb5c183c2629","observation_id":"5dafae6c-862c-43bd-aaf2-1f20f4922c1d","resolution":{"observed_at":"2026-08-01T11:43:11.139583Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.18013","last_updated":"2026-05-18T08:05:59Z","snapshot_observed_at":"2026-08-05T06:07:49.719500Z","submitted_at":"2026-05-18T08:05:59Z","title":"TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.18013","snapshot_observed_at":"2026-08-01T11:43:11.216668Z","title":"Tinysam 2: Extreme mem- ory compression for efficient track anything model,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:11.216668Z"},"links":{"cited_paper":"/paper/2605.18013","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:6fe7ed4fb9a1daf25915087f7217662b4a1c993983458caa4491d58f17af1aa9","observation_id":"c67e17da-b85a-43d2-9b1b-fdaafcfbe305","resolution":{"observed_at":"2026-08-01T11:43:11.216668Z","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":"2026-08-01T11:43:11.270794Z","title":"Surgical SAM 2: Real- time segment anything in surgical video by efficient frame pruning,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:11.270794Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:64f0f1ceb5647fdeb6a0d695bf5d19a69ec2491ce0450f37c5e6f94f1b900971","observation_id":"30542592-5f58-42fe-acf7-88a49c6d8f79","resolution":{"observed_at":"2026-08-01T11:43:11.270794Z","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":"2026-08-01T11:43:11.376530Z","title":"Tsms-sam2: multi-scale temporal sampling augmentation and memory-splitting pruning for promptable video object segmentation and tracking in surgical scenarios,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:11.376530Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:a548160f3bf91471eeca8fd609fe68abe4a7ba4a79b7331f1c2ac9d85ce7bfab","observation_id":"416ce3e4-b630-4810-ac09-888da6620d96","resolution":{"observed_at":"2026-08-01T11:43:11.376530Z","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":"2026-08-01T11:43:11.493867Z","title":"Efficient track anything,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:11.493867Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:1d7bebb424fbb1f79f2a70bc9ebf2816881a37671d9b7fa89e696fbd4782893f","observation_id":"3f4768b4-feba-4142-a6f8-0676cffe3fb6","resolution":{"observed_at":"2026-08-01T11:43:11.493867Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11922","last_updated":"2024-11-30T22:32:34Z","snapshot_observed_at":"2026-08-08T21:51:38.855361Z","submitted_at":"2024-11-18T05:59:03Z","title":"SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.11922","snapshot_observed_at":"2026-08-01T11:43:11.608780Z","title":"Samu- rai: Adapting segment anything model for zero-shot visual tracking with motion-aware memory,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:11.608780Z"},"links":{"cited_paper":"/paper/2411.11922","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:d424195c7ba48219d2dea3bf77a97f04bc3e50d10d713d97c8838538e7fe6a8d","observation_id":"b18d6867-db27-4f40-8d7e-8f3f21b6abdb","resolution":{"observed_at":"2026-08-01T11:43:11.608780Z","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":"2026-08-01T11:43:11.751250Z","title":"Ahcptq: Accurate and hardware-compatible post-training quantization for segment anything model,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:11.751250Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:02736c47a8e71e2f3f031d6efb4cb04b37e96e875d4b84a5d5728e28e59391b6","observation_id":"a3271173-d28c-4fdc-a822-a76622976dad","resolution":{"observed_at":"2026-08-01T11:43:11.751250Z","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":"2026-08-01T11:43:11.884098Z","title":"Q-sam2: Accurate quantization for segment anything model 2,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:11.884098Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:70cda8b8db9589ed2bc4c14d4d41065ff5f44ddca6a6d0039aa54763d0b44e81","observation_id":"9b3d4af8-a74e-4c37-8f55-76c5946f3396","resolution":{"observed_at":"2026-08-01T11:43:11.884098Z","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":"2026-08-01T11:43:11.957852Z","title":"Mix-qsam2: Mixed-precision quantization for high fidelity segmentation in resource constrained scenarios,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:11.957852Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:dbf7cdb9ff7642befc0d3850c0ef64fa8931fe40dfbdab56b74859ce3ce13301","observation_id":"9d38d729-4a65-41c3-8311-d9e359cec8d9","resolution":{"observed_at":"2026-08-01T11:43:11.957852Z","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":"2026-08-01T11:43:12.078412Z","title":"Q-minisam2: A quantization-based benchmark for resource-efficient video segmenta- tion,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:12.078412Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:24a85ff749f82c9c2fb0da3d68da60e8c361c586f380a71a599479eb804b4c2f","observation_id":"40ff3a74-0075-4633-9ee9-db3a65a087f5","resolution":{"observed_at":"2026-08-01T11:43:12.078412Z","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":"2026-08-01T11:43:12.206777Z","title":"Efficient video object segmentation and tracking with recurrent dynamic submodel,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:12.206777Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:21bbbe7145127dc0c5da94651e2eb11c5187a1e3a1ecf991c0a59b5943b0e2e4","observation_id":"77dd2664-bd22-4da9-925d-0cb16d4be973","resolution":{"observed_at":"2026-08-01T11:43:12.206777Z","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":"2026-08-01T11:43:12.321758Z","title":"Edgetam: On-device track anything model,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:12.321758Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:ea0f48cd5b8b7ef486d32e5fc5d6c3376d6cb8a390ee15560c627ff924f52d86","observation_id":"bacca0de-a691-4c86-8fc4-3f838dd99b5a","resolution":{"observed_at":"2026-08-01T11:43:12.321758Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.03088","last_updated":"2026-04-08T13:11:29Z","snapshot_observed_at":"2026-07-31T21:51:41.767129Z","submitted_at":"2025-03-05T01:04:45Z","title":"AHCQ-SAM: Toward Accurate and Hardware-Compatible Post-Training Segment Anything Model Quantization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.03088","snapshot_observed_at":"2026-08-01T11:43:12.446712Z","title":"Ahcq-sam: Toward accurate and hardware-compatible post-training seg- ment anything model quantization,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:12.446712Z"},"links":{"cited_paper":"/paper/2503.03088","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:4b5004bf0c187d54f0d61ff9fbbf33f5035a39a8a89f05a7aa68c3a5f4be3613","observation_id":"9ac497de-d8d7-4542-a2bb-3cc58024b56a","resolution":{"observed_at":"2026-08-01T11:43:12.446712Z","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":"2026-08-01T11:43:12.591422Z","title":"Lvos: A benchmark for large-scale long-term video object segmentation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:12.591422Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:b8afc4b9bb31bd78bccafbecf0cbf661f54b63263a214676e758a8fb96ea48f0","observation_id":"371ca45a-eb8d-4abd-84b1-2d977f335213","resolution":{"observed_at":"2026-08-01T11:43:12.591422Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2606.24449","last_updated":"2026-06-24T03:13:44Z","snapshot_observed_at":"2026-07-06T23:59:03.724013Z","submitted_at":"2026-06-23T11:35:15Z","title":"SENTRY: SAM2-Enhanced Neighbor-Aware and Temporally Reasoned Memory for Visual Tracking","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2606.24449","snapshot_observed_at":"2026-08-01T11:43:12.707979Z","title":"Sentry: Sam2-enhanced neighbor-aware and temporally reasoned memory for visual tracking,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:12.707979Z"},"links":{"cited_paper":"/paper/2606.24449","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:813c3862785fc57ede1ebca690001f6e16476ca50490f847894e423bc4b4156a","observation_id":"965824bc-9791-4ac2-a72a-20558e0a8c28","resolution":{"observed_at":"2026-08-01T11:43:12.707979Z","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":"2026-08-01T11:43:12.805366Z","title":"Object tracking: A survey,","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:12.805366Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:419e5e2db7ae96accdf297243389d399b242cd9180e9b7e54ddc78b90cfb2b62","observation_id":"8d85e197-0346-487b-b4cd-feca85a4cef2","resolution":{"observed_at":"2026-08-01T11:43:12.805366Z","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":"2026-08-01T11:43:12.940748Z","title":"A survey on deep learning technique for video segmentation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:12.940748Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:e2800c7e7634c6354db75c16c78ae3ec2c62bddbfdd6cbd65211de7a7c2f43ea","observation_id":"87b53170-cc44-4b23-84da-5bbd0360ba4f","resolution":{"observed_at":"2026-08-01T11:43:12.940748Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00874","last_updated":"2024-12-04T23:51:25Z","snapshot_observed_at":"2026-08-04T09:38:10.661882Z","submitted_at":"2024-08-01T18:49:45Z","title":"Medical SAM 2: Segment medical images as video via Segment Anything Model 2","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00874","snapshot_observed_at":"2026-08-01T11:43:13.069270Z","title":"Medical sam 2: Segment medical images as video via segment anything model 2,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:13.069270Z"},"links":{"cited_paper":"/paper/2408.00874","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:610475c5c632dc7ec5aa33b098364551ea9f271ead1c57e987f0fdd486ad0dff","observation_id":"9d6bdf99-d138-429f-9659-f56ee41c8642","resolution":{"observed_at":"2026-08-01T11:43:13.069270Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.03600","last_updated":"2025-04-04T17:13:37Z","snapshot_observed_at":"2026-08-08T02:19:23.143138Z","submitted_at":"2025-04-04T17:13:37Z","title":"MedSAM2: Segment Anything in 3D Medical Images and Videos","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.03600","snapshot_observed_at":"2026-08-01T11:43:13.236874Z","title":"Medsam2: Segment anything in 3d medical images and videos,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:13.236874Z"},"links":{"cited_paper":"/paper/2504.03600","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:9e48ccf3367809fd7c72db68a2e555d2f9dd71c52b84db4f8217c8e5a6ef027e","observation_id":"0c415da8-2190-476d-8ca4-6c3d95c9e9b7","resolution":{"observed_at":"2026-08-01T11:43:13.236874Z","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":"2026-08-01T11:43:13.348653Z","title":"Sam2long: Enhancing sam 2 for long video segmentation with a training-free memory tree,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:13.348653Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:f16cfb11872fa79230e1b7b6d39eac5ccc7e7954e7d5802feb98e2a1b2b072c1","observation_id":"11ed655a-7c8c-46b6-a63e-b819fe237948","resolution":{"observed_at":"2026-08-01T11:43:13.348653Z","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":"2026-08-01T11:43:13.473268Z","title":"A distractor-aware memory for visual object tracking with sam2,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:13.473268Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:4a8a345b37948d63ae9dcff26d7fcda0ac7e4db93ce58d4d9147d4ef905a5a09","observation_id":"7b4945a1-90ae-4d7d-9e04-13f67102fb1a","resolution":{"observed_at":"2026-08-01T11:43:13.473268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.12156","last_updated":"2023-06-21T10:08:29Z","snapshot_observed_at":"2026-07-06T15:45:01.961896Z","submitted_at":"2023-06-21T10:08:29Z","title":"Fast Segment Anything","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.12156","snapshot_observed_at":"2026-08-01T11:43:13.566960Z","title":"Fast segment anything,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:13.566960Z"},"links":{"cited_paper":"/paper/2306.12156","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:990bd6962fb082a0941f3633e1cd24adb5d422729fa9c6c93bb5c09a6aee0bc4","observation_id":"0d8451d8-7b17-4eac-94ea-e9a7210318ff","resolution":{"observed_at":"2026-08-01T11:43:13.566960Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.14289","last_updated":"2023-07-01T07:26:22Z","snapshot_observed_at":"2026-08-08T16:17:33.420400Z","submitted_at":"2023-06-25T16:37:25Z","title":"Faster Segment Anything: Towards Lightweight SAM for Mobile Applications","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.14289","snapshot_observed_at":"2026-08-01T11:43:13.678289Z","title":"Faster segment anything: Towards lightweight sam for mobile applications,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:13.678289Z"},"links":{"cited_paper":"/paper/2306.14289","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:777490b0e2a8ec5b2a96b9a7c99bd6c78a70e0c2ca7fb05dacb17858bdd4270d","observation_id":"b521a8ac-5233-4818-8566-70df2080f2f9","resolution":{"observed_at":"2026-08-01T11:43:13.678289Z","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":"2026-08-01T11:43:13.758268Z","title":"Efficientsam: Leveraged masked image pretraining for efficient segment anything,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:13.758268Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:a1d054d1e6009b64d059567884af62f9bcc96afdc668a27e979b6ba0de603dd0","observation_id":"a02c9f86-1814-4b42-9576-d13f352c9e25","resolution":{"observed_at":"2026-08-01T11:43:13.758268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.06660","last_updated":"2025-09-07T19:09:41Z","snapshot_observed_at":"2026-07-06T17:00:00.321552Z","submitted_at":"2023-12-11T18:59:52Z","title":"EdgeSAM: Prompt-In-the-Loop Distillation for SAM","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.06660","snapshot_observed_at":"2026-08-01T11:43:13.812218Z","title":"Edgesam: Prompt-in-the- loop distillation for on-device deployment of sam,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:13.812218Z"},"links":{"cited_paper":"/paper/2312.06660","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:e37cc80cb4b1d6ae1510abe8f0dda66dee4215eb6516db4fc48323a9c2703977","observation_id":"93d25026-318c-413c-be85-757cc54f6409","resolution":{"observed_at":"2026-08-01T11:43:13.812218Z","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":"2026-08-01T11:43:13.848938Z","title":"Tinysam: Pushing the envelope for efficient segment anything model,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:13.848938Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:290544bb2991ac8410d82f8dfc300515d1722aa9b71ea7c8ef969d9aa6cd4cf2","observation_id":"54c6085e-2d75-41e0-9f47-abdca1f0e1f0","resolution":{"observed_at":"2026-08-01T11:43:13.848938Z","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":"2026-08-01T11:43:13.894506Z","title":"Slimsam: 0.1% data makes segment anything slim,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:13.894506Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:e1b10284d127e149ecc30dcd2c5cb220a9a2a44f66bd7e74549b6f9e66a0458d","observation_id":"2e630a90-952e-43e0-8620-ed190c57aa05","resolution":{"observed_at":"2026-08-01T11:43:13.894506Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.08504","last_updated":"2025-01-15T00:54:12Z","snapshot_observed_at":"2026-08-05T14:29:46.167170Z","submitted_at":"2025-01-15T00:54:12Z","title":"SuperSAM: Crafting a SAM Supernetwork via Structured Pruning and Unstructured Parameter Prioritization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.08504","snapshot_observed_at":"2026-08-01T11:43:14.066618Z","title":"Supersam: Crafting a sam supernetwork via structured pruning and unstructured parameter prioritization,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:14.066618Z"},"links":{"cited_paper":"/paper/2501.08504","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:46b507816f9d74492a07add84bb31c1541079c5a144cb28e8cb25a658a997e92","observation_id":"e5abb12f-ee1d-46aa-b63c-6e110d51213f","resolution":{"observed_at":"2026-08-01T11:43:14.066618Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.17633","last_updated":"2026-05-17T19:54:22Z","snapshot_observed_at":"2026-07-06T23:28:36.134614Z","submitted_at":"2026-05-17T19:54:22Z","title":"SparseSAM: Structured Sparsification of Activations in Segment Anything Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.17633","snapshot_observed_at":"2026-08-01T11:43:14.189200Z","title":"Sparsesam: Structured sparsification of activations in segment anything models,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:14.189200Z"},"links":{"cited_paper":"/paper/2605.17633","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:e1905359a7dbc072d9acca60738a48aecb2fe4d3e2c247df34ec56ae465edec5","observation_id":"338f8344-7367-44bc-8c7a-92be1741ec42","resolution":{"observed_at":"2026-08-01T11:43:14.189200Z","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":"2026-08-01T11:43:14.225415Z","title":"Structsam: structure-aware prompt adaptation for robust lung cancer lesion segmentation in ct,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:14.225415Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:290e04b9acb62a8fe59be39564db3e502c29d30ed10940680f92e0107bec2d70","observation_id":"e7577f7b-f033-458c-8b21-ea8d2152addf","resolution":{"observed_at":"2026-08-01T11:43:14.225415Z","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":"2026-08-01T11:43:14.309015Z","title":"Car-sam: Cross-attention recon- struction for post-training quantization of the segment anything model,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:14.309015Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:5665f59a03b18c962711f51863627eaaf2cbf5b2a668ff66cd0db665bce72179","observation_id":"892b8476-c909-40f9-aa43-e9e0f8712f5e","resolution":{"observed_at":"2026-08-01T11:43:14.309015Z","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":"2026-08-01T11:43:14.437030Z","title":"Saq-sam: Semantically- aligned quantization for segment anything model,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:14.437030Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:940a4e99a70148242ae66d09ac9097bee6997b43efbec33f6845bdb9de841541","observation_id":"c1fcf823-cdd0-4349-ba93-89f38ac771e1","resolution":{"observed_at":"2026-08-01T11:43:14.437030Z","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":"2026-08-01T11:43:14.493536Z","title":"Efficientvit-sam: Accelerated segment anything model without performance loss,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:14.493536Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:a00337876883def801b3eaee8f38f2faf24f3f69a6ad43ffc39e8e3222f8c633","observation_id":"772d9495-8e84-4298-977e-f8d5f6d03fd2","resolution":{"observed_at":"2026-08-01T11:43:14.493536Z","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":"2026-08-01T11:43:14.610585Z","title":"Ptq4sam: Post-training quantization for segment anything,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:14.610585Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:8bc4221c9fea0a4314487c6f6fb88ffbaca92015bc44de2d57c3f1cc13a2e2cd","observation_id":"3e0acce2-73ce-4914-926b-0faedb66e35a","resolution":{"observed_at":"2026-08-01T11:43:14.610585Z","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":"2026-08-01T11:43:14.721173Z","title":"On efficient variants of segment anything model: A survey: X. sun et al","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:14.721173Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:7197356102b9a4ea4f8253fca09c7f4493697650ce7997e871ea599b0eaf9295","observation_id":"a6b573c2-cfdb-483d-bfb0-38de2b4086d0","resolution":{"observed_at":"2026-08-01T11:43:14.721173Z","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":"2026-08-01T11:43:14.802334Z","title":"Repvit: Revisiting mobile cnn from vit perspective,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:14.802334Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:fa7f76d3270d1bacdf7c5d649ec4356bc7258a52dccc40ede5d17905a880069d","observation_id":"b159bda4-e19c-4f6a-afc4-ed2569298819","resolution":{"observed_at":"2026-08-01T11:43:14.802334Z","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":"2026-08-01T11:43:14.916646Z","title":"Sam2lora: Composite loss-guided, parameter-efficient finetuning of sam2 for retinal fundus segmentation,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:14.916646Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:dc9e4d5d6b8a9b03f05b8df2a2c78d030996f7846288d474ca08cbcdd5b467bd","observation_id":"8bdde97d-0233-43a0-8e72-14f67f5ec65b","resolution":{"observed_at":"2026-08-01T11:43:14.916646Z","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":"2026-08-01T11:43:15.026736Z","title":"Uniultra: Interactive parameter-efficient sam2 for universal ultrasound segmentation,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:15.026736Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:9a554ac2b17e2ee780ab5771ee1b26e2c7b5966befbcae915dc921134c53b150","observation_id":"de6154dd-2098-4cc6-a615-e3280cd2bad5","resolution":{"observed_at":"2026-08-01T11:43:15.026736Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.05979","last_updated":"2026-05-07T10:24:01Z","snapshot_observed_at":"2026-07-06T23:18:31.432422Z","submitted_at":"2026-05-07T10:24:01Z","title":"Prompt-Free and Efficient SAM2 Adaptation for Biomedical Semantic Segmentation via Dual Adapters","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.05979","snapshot_observed_at":"2026-08-01T11:43:15.140929Z","title":"Prompt-free and efficient sam2 adaptation for biomedical semantic segmentation via dual adapters,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:15.140929Z"},"links":{"cited_paper":"/paper/2605.05979","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:ffe60dfe440e6e156674aa5c2b700704d1b9a3f5f7b1034447512ff21b726a5c","observation_id":"895ce130-d55d-4440-96b9-dbffc22ee1f5","resolution":{"observed_at":"2026-08-01T11:43:15.140929Z","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":"2026-08-01T11:43:15.232747Z","title":"Sam2v-btr: Accelerat- ing sam 2 training for 3d medical image segmentation through bootstrap and memory annealing,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:15.232747Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:b992bbe3b5e0aaafb71cb6d78c4f96ca4bff02ff6bc145bab6aadddee643cee9","observation_id":"ce35a665-cb73-4336-aa42-60fabfc1b75f","resolution":{"observed_at":"2026-08-01T11:43:15.232747Z","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":"2026-08-01T11:43:15.321502Z","title":"Mft: Memory- aware fine-tuning of sam2 for efficient long-sequence video object segmentation,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:15.321502Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:667d43a5e2078ded2f4200a416e4e59b3ed4c52b42a870985157aaf93439fe49","observation_id":"e601e335-9367-4916-9bb4-bc3d99d53f84","resolution":{"observed_at":"2026-08-01T11:43:15.321502Z","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":"2026-08-01T11:43:15.437391Z","title":"Dynamicvit: Efficient vision transformers with dynamic token sparsification,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:15.437391Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:d940b0da930a22691c7e387dc686034d63d380df69547105fe7532100e1f63d0","observation_id":"83936e27-00de-449a-921e-5f4127b1c5bb","resolution":{"observed_at":"2026-08-01T11:43:15.437391Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2202.07800","last_updated":"2022-04-13T23:46:08Z","snapshot_observed_at":"2026-08-03T03:15:29.208149Z","submitted_at":"2022-02-16T00:19:42Z","title":"Not All Patches are What You Need: Expediting Vision Transformers via Token Reorganizations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.07800","snapshot_observed_at":"2026-08-01T11:43:15.551554Z","title":"Not all patches are what you need: Expediting vision transformers via token reorganizations,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:15.551554Z"},"links":{"cited_paper":"/paper/2202.07800","citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:f6fcdad53bc85c30dd05d075bf57c24c9721c9d0e6adef859f305190f3d0c449","observation_id":"8a736969-6d7f-457e-936d-76c9fe19ab07","resolution":{"observed_at":"2026-08-01T11:43:15.551554Z","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":"2026-08-01T11:43:15.641108Z","title":"A-vit: Adaptive tokens for efficient vision transformer,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:15.641108Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:82fa1b600789f383352e5cd0b32d8f68d00d3cdeb09a1def08e5712966994d9d","observation_id":"8c6f76cc-816b-4a88-a4ab-f3e366afff3f","resolution":{"observed_at":"2026-08-01T11:43:15.641108Z","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":"2026-08-01T11:43:15.747396Z","title":"Token merging: Your vit but faster,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:15.747396Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:d18b55b19926af1a29f692bbca1c0e44b0156cf19f018bd9d6db19c92299373d","observation_id":"3775ea7b-8419-47d3-9706-b9ba53c3cc31","resolution":{"observed_at":"2026-08-01T11:43:15.747396Z","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":"2026-08-01T11:43:15.851407Z","title":"Token merging for fast stable diffusion,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:15.851407Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:842a264a7ab045ae4ebd5de319de43a5a0bea339dced919666650c6cf3ec5ee5","observation_id":"064b6868-da69-448e-8d0d-f21cb85e81d8","resolution":{"observed_at":"2026-08-01T11:43:15.851407Z","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":"2026-08-01T11:43:15.955835Z","title":"Algm: Adaptive local-then-global token merging for efficient semantic segmentation with plain vision transformers,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:15.955835Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:845ec6460f05a8c998ec0fecfc3980d8f773985c121d64b4274d0d823d419450","observation_id":"779f0f1f-99ba-4a15-8fc5-f2125282b347","resolution":{"observed_at":"2026-08-01T11:43:15.955835Z","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":"2026-08-01T11:43:16.115392Z","title":"Segformer++: Efficient token-merging strategies for high-resolution semantic segmen- tation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:16.115392Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:1756b972b3df7e027aaa2e1155e30ed8d1e3264022e50a8b7016cfdda3799033","observation_id":"a170162d-66d6-4dcc-8806-0b1272439568","resolution":{"observed_at":"2026-08-01T11:43:16.115392Z","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":"2026-08-01T11:43:16.277540Z","title":"Efficient and robust video object segmentation through isogenous memory sampling and frame relation mining,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:16.277540Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:c2fe6b720d78d89ca8b03f87ce1d0ea593b1ad741a2c6f4d8a33e972bc20f39b","observation_id":"a03c1dc6-77ea-44c7-a188-d5c5fed8b7f5","resolution":{"observed_at":"2026-08-01T11:43:16.277540Z","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":"2026-08-01T11:43:16.474529Z","title":"Beyond appearance: Multi-frame spatio-temporal context memory networks for efficient and robust video object segmentation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:16.474529Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:a41cf1a1fff227c35f6fdebafa7f06e660660842beda21a27e812fe8f23987fe","observation_id":"e99f47ba-ed4b-4fea-9656-a701dc60d1aa","resolution":{"observed_at":"2026-08-01T11:43:16.474529Z","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":"2026-08-01T11:43:16.587640Z","title":"Region aware video object segmentation with deep motion modeling,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:16.587640Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:e0bad2065133d44f58e00f09d3853a6a768448f161f4ef8aed7abd8489f01aa0","observation_id":"4c98f7c3-9611-47b3-808b-7a5ae0a1ca6e","resolution":{"observed_at":"2026-08-01T11:43:16.587640Z","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":"2026-08-01T11:43:16.685177Z","title":"Prototypical matching networks for video object segmentation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:16.685177Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:f03b4570eb9b66ec3d63e4112277ab6b8db382d54490252ca98a952b5af817c6","observation_id":"90fa3a78-4a96-43a6-8b40-2f85a8f6c2d7","resolution":{"observed_at":"2026-08-01T11:43:16.685177Z","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":"2026-08-01T11:43:16.832748Z","title":"Delving deeper into mask utilization in video object segmentation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:16.832748Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:0f5960756a3873bc403038d91571c35e72c9441e93ded7d271bc531ca17c98c7","observation_id":"571453d3-c755-4044-a6cf-3822b0598d95","resolution":{"observed_at":"2026-08-01T11:43:16.832748Z","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":"2026-08-01T11:43:16.952037Z","title":"Mosev2: A more challenging dataset for video object segmentation in complex scenes,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:16.952037Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:e099e6043d2aae48d05c2b86d6e1aba2323660f413c62b5903f6638a00c3a303","observation_id":"805206b2-f423-44a1-815b-724b721704c3","resolution":{"observed_at":"2026-08-01T11:43:16.952037Z","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":"2026-08-01T11:43:17.032956Z","title":"Mose: A new dataset for video object segmentation in complex scenes,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-01T11:43:17.032956Z"},"links":{"citing_paper":"/paper/2607.19811"},"observation_digest":"sha256:2e556a62c8077b5c869748bba9288497398c225de55bab5e1620f14fbcfc10e0","observation_id":"bbaeee49-692d-4f58-b960-d46139a75054","resolution":{"observed_at":"2026-08-01T11:43:17.032956Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.19811","last_updated":"2026-07-22T06:42:27Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-06T18:57:58.306282Z","submitted_at":"2026-07-22T06:42:27Z","title":"Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2"},"reference_resolution":{"displayed":62,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":62,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":62},"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 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2607.19811."}