{"as_of":"2026-08-14T11:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0c4dc009008cf8baa103fd0d1f663220a2e753ca0cc56dd00b7a0fc90bee6d4b","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":"2026-08-14T06:32:32.682623+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":"2026-08-12T15:59:25.650704Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":152,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":"2304.06718","doi":"10.48550/arxiv.2304.06718","metadata_source":"arxiv_reference","pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2304.06718 , year=","venue":"arXiv (Cornell University)","work_id":"685078c7-c944-44c7-8b14-fdd01972f83c","year":2023},"citing_paper":{"arxiv_id":"2303.16199","last_updated":"2024-09-18T23:54:36Z","snapshot_observed_at":"2026-08-13T10:46:50.834601Z","submitted_at":"2023-03-28T17:59:12Z","title":"LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention","version":3},"reference_index":299,"source":"arxiv_source","source_observed_at":"2026-05-14T23:07:42.245641Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2303.16199"},"observation_digest":"sha256:0ae9616bbcdedd26e6fc5390aabb0d2e71bc0edb78cff669a8dd70b0a6496bb1","observation_id":"9978467e-fe73-445f-ad36-107fed6fde64","resolution":{"observed_at":"2026-05-14T23:07:42.969180Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":"2304.06718","doi":"10.48550/arxiv.2304.06718","metadata_source":"arxiv_reference","pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2304.06718 , year=","venue":"arXiv (Cornell University)","work_id":"685078c7-c944-44c7-8b14-fdd01972f83c","year":2023},"citing_paper":{"arxiv_id":"2305.10355","last_updated":"2023-10-26T02:52:40Z","snapshot_observed_at":"2026-08-12T18:48:30.326248Z","submitted_at":"2023-05-17T16:34:01Z","title":"Evaluating Object Hallucination in Large Vision-Language Models","version":3},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-05-11T13:44:09.626361Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2305.10355"},"observation_digest":"sha256:1029fd2794a8eb0db639812b871c062eb11a425e16fe8b14355eecb75262523b","observation_id":"2643566a-fe84-4a14-a8b4-a44edef62890","resolution":{"observed_at":"2026-05-11T13:44:09.728006Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":"2304.06718","doi":"10.48550/arxiv.2304.06718","metadata_source":"arxiv_reference","pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2304.06718 , year=","venue":"arXiv (Cornell University)","work_id":"685078c7-c944-44c7-8b14-fdd01972f83c","year":2023},"citing_paper":{"arxiv_id":"2309.17421","last_updated":"2023-10-11T05:07:37Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-29T17:34:51Z","title":"The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)","version":2},"reference_index":160,"source":"pdf_text","source_observed_at":"2026-05-15T23:26:06.183574Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2309.17421"},"observation_digest":"sha256:12760286a99e525554c90fd4d7abd2b9ffed139812d44be0d671928b6f79e64c","observation_id":"e1790811-4204-4ca4-9a5a-74e6d6e1a2e4","resolution":{"observed_at":"2026-05-15T23:26:06.571484Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":"2304.06718","doi":"10.48550/arxiv.2304.06718","metadata_source":"arxiv_reference","pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2304.06718 , year=","venue":"arXiv (Cornell University)","work_id":"685078c7-c944-44c7-8b14-fdd01972f83c","year":2023},"citing_paper":{"arxiv_id":"2310.11441","last_updated":"2023-11-06T07:39:49Z","snapshot_observed_at":"2026-08-12T21:25:32.312122Z","submitted_at":"2023-10-17T17:51:31Z","title":"Set-of-Mark Prompting Unleashes Extraordinary Visual Grounding in GPT-4V","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-12T14:01:49.854238Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2310.11441"},"observation_digest":"sha256:747fcce1bb029406f1984c9e97f8af4c1404a2e4bb1dd79115c5c753f2c80edd","observation_id":"8b2cf28e-a79f-422d-9fc3-f31abffb0f22","resolution":{"observed_at":"2026-05-12T14:01:49.971425Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-12T15:59:25.650704Z","title":"Segment Everything Everywhere All at Once,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.13774","last_updated":"2024-11-21T01:04:53Z","snapshot_observed_at":"2026-08-12T20:11:41.439480Z","submitted_at":"2024-11-21T01:04:53Z","title":"Segment Any Class (SAC): Multi-Class Few-Shot Semantic Segmentation via Class Region Proposals","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T15:59:25.650704Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2411.13774"},"observation_digest":"sha256:f0902d7d9723f9b00bf4f6eef3e641ef317aae346587dc4e5e90f58854e67227","observation_id":"7549e8c7-ec05-416b-9ffd-aed3fed4a5df","resolution":{"observed_at":"2026-08-12T15:59:25.650704Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-12T10:32:37.658180Z","title":"Segment everything every- where all at once","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.19141","last_updated":"2024-11-28T13:42:35Z","snapshot_observed_at":"2026-08-13T08:13:12.147671Z","submitted_at":"2024-11-28T13:42:35Z","title":"On Moving Object Segmentation from Monocular Video with Transformers","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-12T10:32:37.658180Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2411.19141"},"observation_digest":"sha256:668022d1d6a66d1768c003d902988721714b5e2ebdd8ee2aaf8ef9854d94b3a1","observation_id":"d04424b4-f706-4b9d-bbb7-ed537bcff581","resolution":{"observed_at":"2026-08-12T10:32:37.658180Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-11T16:14:48.548439Z","title":"Segment everything everywhere all at once,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10224","last_updated":"2024-12-13T15:49:18Z","snapshot_observed_at":"2026-08-11T16:44:19.127828Z","submitted_at":"2024-12-13T15:49:18Z","title":"SPT: Sequence Prompt Transformer for Interactive Image Segmentation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T16:14:48.548439Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2412.10224"},"observation_digest":"sha256:f8e0e58f5437464ed263fc62f3696667ed4bf5c81feec4d3ba300db3dd9496c4","observation_id":"e11f8985-7854-4909-819e-3f0d531b355f","resolution":{"observed_at":"2026-08-11T16:14:48.548439Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-11T10:50:38.744997Z","title":"Segment everything everywhere all at once,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.16085","last_updated":"2024-12-20T17:33:35Z","snapshot_observed_at":"2026-08-12T20:11:41.069208Z","submitted_at":"2024-12-20T17:33:35Z","title":"Efficient MedSAMs: Segment Anything in Medical Images on Laptop","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T10:50:38.744997Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2412.16085"},"observation_digest":"sha256:7b774442c9c973f35d626fe91dbb553be45045f4a4ac7609617609764c35d93b","observation_id":"bc6709a6-a0f8-458f-b694-84a49a40c2d5","resolution":{"observed_at":"2026-08-11T10:50:38.744997Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-10T20:25:42.050894Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.08580","last_updated":"2025-01-15T05:00:03Z","snapshot_observed_at":"2026-08-14T05:45:14.827160Z","submitted_at":"2025-01-15T05:00:03Z","title":"Densely Connected Parameter-Efficient Tuning for Referring Image Segmentation","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-10T20:25:42.050894Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2501.08580"},"observation_digest":"sha256:5efd40a12326f18a13735924a7302bae351de2da36680216f198bf65e764dbaf","observation_id":"bd4719e0-15b3-42b3-9578-8f098841b46b","resolution":{"observed_at":"2026-08-10T20:25:42.050894Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-09T22:41:21.282407Z","title":"Segment everything everywhere all at once","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18753","last_updated":"2025-01-30T21:07:14Z","snapshot_observed_at":"2026-08-10T01:57:58.405485Z","submitted_at":"2025-01-30T21:07:14Z","title":"INT: Instance-Specific Negative Mining for Task-Generic Promptable Segmentation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-09T22:41:21.282407Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2501.18753"},"observation_digest":"sha256:77a04b5204e29717a7ee05ffcecd05cd852bb08a1155c9d37c664f9e19d8ddeb","observation_id":"4425fb4d-72d7-4ee2-b1a8-ea561125a597","resolution":{"observed_at":"2026-08-09T22:41:21.282407Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-07T14:23:56.532387Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.19242","last_updated":"2025-05-25T17:42:53Z","snapshot_observed_at":"2026-08-13T10:01:36.282685Z","submitted_at":"2025-05-25T17:42:53Z","title":"Deformable Attentive Visual Enhancement for Referring Segmentation Using Vision-Language Model","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T14:23:56.532387Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2505.19242"},"observation_digest":"sha256:2a913cc335915b1a3370a9c0d0e819b116d518bba586328354ba1f5d33752ad5","observation_id":"abf5aaca-21bb-4d6a-a111-80dc9d3d8b09","resolution":{"observed_at":"2026-08-07T14:23:56.532387Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-06T19:43:43.308601Z","title":"arXiv preprint arXiv:2304.06718 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.04815","last_updated":"2025-07-07T09:33:19Z","snapshot_observed_at":"2026-08-12T20:10:05.225575Z","submitted_at":"2025-07-07T09:33:19Z","title":"From Vision To Language through Graph of Events in Space and Time: An Explainable Self-supervised Approach","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T19:43:43.308601Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2507.04815"},"observation_digest":"sha256:42fc9970eb75891c41f5af250a6cb2577f13b827018833fa846dfa7b67d63208","observation_id":"2c663d35-f275-4fdf-89a6-cb6c53056acc","resolution":{"observed_at":"2026-08-06T19:43:43.308601Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-06T17:56:03.866876Z","title":"Segment Everything Everywhere All at Once","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.09562","last_updated":"2025-07-13T10:10:17Z","snapshot_observed_at":"2026-08-10T14:22:16.593740Z","submitted_at":"2025-07-13T10:10:17Z","title":"Prompt Engineering in Segment Anything Model: Methodologies, Applications, and Emerging Challenges","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-06T17:56:03.866876Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2507.09562"},"observation_digest":"sha256:82e1290b23bc2e7190c265e2fa608b89218de5e62b997cdc6f8b9bfce682c501","observation_id":"8e008236-00e6-4e64-8d6f-cc78ffb88613","resolution":{"observed_at":"2026-08-06T17:56:03.866876Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-06T15:25:13.523578Z","title":"Segment everything everywhere all at once, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.16038","last_updated":"2025-07-21T20:11:57Z","snapshot_observed_at":"2026-08-09T11:29:48.423637Z","submitted_at":"2025-07-21T20:11:57Z","title":"Discovering and using Spelke segments","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T15:25:13.523578Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2507.16038"},"observation_digest":"sha256:6d861ad86b1023067cd206eeb6756a0fc623a1139dcafdac96399461102bf367","observation_id":"04472d0b-2cf9-4923-ba9c-f146fb714665","resolution":{"observed_at":"2026-08-06T15:25:13.523578Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-05T14:47:12.824391Z","title":"Segment everything everywhere all at once,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.20965","last_updated":"2025-08-28T16:22:54Z","snapshot_observed_at":"2026-08-10T11:21:38.482955Z","submitted_at":"2025-08-28T16:22:54Z","title":"DrivingGaussian++: Towards Realistic Reconstruction and Editable Simulation for Surrounding Dynamic Driving Scenes","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-05T14:47:12.824391Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2508.20965"},"observation_digest":"sha256:4cf92942e2b578ad59ba77092b89e199f5f3054d06e7d7d4febb1f800a32080c","observation_id":"014c5b24-eefd-4e5b-88c6-b05da2a6081b","resolution":{"observed_at":"2026-08-05T14:47:12.824391Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once","version":4},"cited_work":{"arxiv_id":"2304.06718","doi":"10.48550/arxiv.2304.06718","metadata_source":"arxiv_reference","pith_arxiv_id":"2304.06718","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2304.06718 , year=","venue":"arXiv (Cornell University)","work_id":"685078c7-c944-44c7-8b14-fdd01972f83c","year":2023},"citing_paper":{"arxiv_id":"2605.18010","last_updated":"2026-05-18T08:05:07Z","snapshot_observed_at":"2026-08-02T12:16:21.427153Z","submitted_at":"2026-05-18T08:05:07Z","title":"Functionalization via Structure Completion and Motion Rectification","version":1},"reference_index":169,"source":"arxiv_source","source_observed_at":"2026-05-20T12:25:07.157086Z"},"links":{"cited_paper":"/paper/2304.06718","citing_paper":"/paper/2605.18010"},"observation_digest":"sha256:790744b52f3872b060d909da706d237a83ffd9bdd39f64aea0997b7ceb17e8cb","observation_id":"c303e814-4ce6-4193-8f03-493afad9fc66","resolution":{"observed_at":"2026-05-20T12:28:17.082194Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2304.06718/citation-record","integrity":"/paper/2304.06718/integrity","json":"/paper/2304.06718/citation-record.json","paper":"/paper/2304.06718"},"outbound":[],"paper":{"arxiv_id":"2304.06718","last_updated":"2023-07-11T18:13:14Z","latest_version":4,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-13T12:03:21.129454Z","submitted_at":"2023-04-13T17:59:40Z","title":"Segment Everything Everywhere All at Once"},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2304.06718."}