{"as_of":"2026-08-18T18:17:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9e897e213a864feda9ee4e56101407ae4710bf3c10561a3aab72059abad98dcb","coverage":[{"denominator":48,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T20:24:19.663080Z","state":"measured"},{"denominator":48,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":48,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+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/2508.10645/citation-record","integrity":"/paper/2508.10645/integrity","json":"/paper/2508.10645/citation-record.json","paper":"/paper/2508.10645"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:27.771494Z","title":"Radford, J","venue":null,"work_id":"60345948-e7af-4b36-925f-84674a90d487","year":2021},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:14.549361Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:09e3480ceadf0163dfdca199005c0cce6f801e478e9215511865d15f8df0e654","observation_id":"97a81dbb-0d6d-4243-a075-142329b2bc25","resolution":{"observed_at":"2026-08-05T20:24:27.831735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:27.602622Z","title":"Rasheed, M","venue":null,"work_id":"284730db-52dd-441e-8d1b-e1ce2f6d9a34","year":2023},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:14.624166Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:12d02ebeada3042e0be2eab3e2a249268866b2abbf91c2bf577978671c1003fe","observation_id":"6a857104-1393-4ecd-b75b-5e91e01a9b0a","resolution":{"observed_at":"2026-08-05T20:24:27.694729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:27.473403Z","title":null,"venue":null,"work_id":"eb5100cf-b970-4f68-84b4-53cc677aab0a","year":2023},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:14.705147Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:8fc0cca0e42f7643f842be6332f58ee86f5a423f5bbf862ca303b8e9876eb528","observation_id":"41698564-cdba-449b-a3a7-77e9a2f36733","resolution":{"observed_at":"2026-08-05T20:24:27.529038Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:27.276384Z","title":null,"venue":null,"work_id":"9453e9b8-eb5b-4ec1-ab12-dc7248d0a21b","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:14.794726Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:d2e328d5293f09e06907c9ded2dec7fe623f8a33def33fd2ce5a42faf943cbcd","observation_id":"bfdab814-5222-4284-a651-ab0326c093da","resolution":{"observed_at":"2026-08-05T20:24:27.368796Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:27.064729Z","title":null,"venue":null,"work_id":"796b4985-af81-4e31-aa70-d4327f6fd22a","year":2022},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:14.886870Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:bcc1b2b22eff1e3ea8eebd1473fdf1d93b7ebb0efd606b714abc33a740a87e3f","observation_id":"a2b742f1-17a2-46d9-881e-e5af34e223f7","resolution":{"observed_at":"2026-08-05T20:24:27.160999Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:26.827714Z","title":null,"venue":null,"work_id":"fd148701-a3c0-4156-8ee3-49ef5f5d01e3","year":2022},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:14.986845Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:295f2a06996127ba52d3e0e3859ca7a8013170b24aa22a9149281fb48bc38168","observation_id":"5b085279-07d6-4f2a-8cc5-46d09c1db7ff","resolution":{"observed_at":"2026-08-05T20:24:26.956262Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:26.626166Z","title":null,"venue":null,"work_id":"3c5d41c9-8c51-468a-b2b3-c60a3a3636c8","year":2023},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:15.041651Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:f7dc9989e3c19e68302097b7e7d339f6a4fdbab37e7b77b973906888237010a9","observation_id":"33461b7a-93c1-4f1f-a028-4eb07016151d","resolution":{"observed_at":"2026-08-05T20:24:26.702520Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:26.363697Z","title":null,"venue":null,"work_id":"0db5b58a-66a7-4b00-a40f-1ee17785f7ac","year":2023},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:15.119602Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:e7fd75c31b4f2a5cd1aff5cd830145c9eba9559b80e2a757aca58cd48cfd43b7","observation_id":"b9a2677f-5140-4720-9c57-30c5d783d920","resolution":{"observed_at":"2026-08-05T20:24:26.502774Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:26.134435Z","title":null,"venue":null,"work_id":"dd2b47e3-9a95-4509-bd45-3188f9ac7018","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:15.206025Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:c9d2d7e7648e225d8e46e5dd905ff5a0cfb13f998c0d1d1fb9ba820594a66b6b","observation_id":"2165b13a-8212-42d5-89fd-fba5a27c6066","resolution":{"observed_at":"2026-08-05T20:24:26.241326Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:25.904007Z","title":"Yang, R.-Y","venue":null,"work_id":"666064d8-462a-432a-8d13-cd722169aa4f","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:15.298328Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:9cf657c850e4676ec1ccc8579d536a3d0be388bf96e6f29a2318dc3415a05378","observation_id":"56b155dc-6c5a-489c-ba00-e59d28872c5b","resolution":{"observed_at":"2026-08-05T20:24:26.002853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:25.718066Z","title":null,"venue":null,"work_id":"d3494a09-1a39-4893-92dc-6dfcf3b2991a","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:15.394622Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:2a62e134102282535eea57331e2f13d62c18bb1cab50e3e05c02145031d8b363","observation_id":"cd06fe63-2a23-486b-be01-90377deb63d3","resolution":{"observed_at":"2026-08-05T20:24:25.789426Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:25.523922Z","title":null,"venue":null,"work_id":"50071b50-b509-4511-8e5b-a206bb044bc5","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:15.484849Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:698c43ae437f3a6180d1345574726a882589ed2e71f2074aa962343946d14d6e","observation_id":"cb7c8035-b0f8-46a0-8a10-82ab7222388f","resolution":{"observed_at":"2026-08-05T20:24:25.629142Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:25.330572Z","title":null,"venue":null,"work_id":"227d36dd-b47d-4d75-831d-7a8e7c66e82b","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:15.559459Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:22121f20e776597de7a68bd868f18fd3b6765768ee3a133ddc23b770b27ae6c1","observation_id":"ef4f43e5-2550-4976-b214-6b9580010cfb","resolution":{"observed_at":"2026-08-05T20:24:25.404963Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:25.141562Z","title":"Roy and A","venue":null,"work_id":"249d3661-26e2-44f0-8637-086a0630d642","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:15.633944Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:568adf0f41bc81e4a973a7afc25ddb254b761aa6c9abd9d47f4748d686de8805","observation_id":"7e016b33-d980-4503-bf8f-f70af4d1a776","resolution":{"observed_at":"2026-08-05T20:24:25.215646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:24.928285Z","title":null,"venue":null,"work_id":"f0a77efb-8ba1-4490-b6ae-0849156815d6","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:15.728017Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:bf5174512a7d455e9e8706ca2267b1eeb5f2892a7c42eeeb6e133023f9c96912","observation_id":"cc99cbb3-76d1-41e9-9601-a61d9c593fee","resolution":{"observed_at":"2026-08-05T20:24:24.981613Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:24.831351Z","title":"Zhang, K","venue":null,"work_id":"152bcdb1-0cb3-48c2-a73c-9e452d3b9503","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:15.855104Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:faf2bf2e2c912a059e86b69b784e3eee84702b06fccb2477e26698aeb860db13","observation_id":"f4a761aa-0022-4bee-ada4-116d87328ea4","resolution":{"observed_at":"2026-08-05T20:24:24.869845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:24.721465Z","title":null,"venue":null,"work_id":"d2973fc8-9edc-46bb-b749-a9b202a9cb42","year":2021},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:15.929493Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:5f4c517e7b5998f8e871a477e0262ba7179a5addb8bf84894888b4ca171c728c","observation_id":"d883c821-6fd8-4f5e-bfe9-e2920afe7f44","resolution":{"observed_at":"2026-08-05T20:24:24.782515Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:24.578152Z","title":null,"venue":null,"work_id":"8b417248-e4a0-4f01-89af-52a9466b1cd8","year":2022},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:16.049397Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:7edba61571da3aab0e37c2d9d5d8898e2128ff228440243491357320ac840eb8","observation_id":"245bc129-2d82-4d0e-b088-8b36fdc83c42","resolution":{"observed_at":"2026-08-05T20:24:24.623448Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:24.395517Z","title":null,"venue":null,"work_id":"b0a2681b-5967-4706-a4b4-b5e38ba4a6c3","year":2023},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:16.129214Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:fbc90f8482eb288d75d234f833aec213d8724439cfb255796a066ee033607003","observation_id":"74f7c746-0b33-44a9-a415-31f0956e9de9","resolution":{"observed_at":"2026-08-05T20:24:24.459638Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:24.124155Z","title":"Alayrac, J","venue":null,"work_id":"ad3d43c0-52b0-4936-a604-dc2759cee391","year":2022},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:16.203857Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:f05afee1a8559a00707c36f1ad99fa8ed923f2e266a4b2cf0649c60565f09733","observation_id":"ba14b37b-4cc6-4c10-8d83-56b246f95201","resolution":{"observed_at":"2026-08-05T20:24:24.300799Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:23.988776Z","title":null,"venue":null,"work_id":"e3fbdc08-cc4c-40be-a97e-6ab9f1c5ea2a","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:16.322916Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:220b86b1e23702253a4c11386899801bfb41d5d402d1e80f9ef30c04375ec16a","observation_id":"a506a7e9-1a26-4a67-aedd-a11046b046e1","resolution":{"observed_at":"2026-08-05T20:24:24.062322Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:23.844916Z","title":null,"venue":null,"work_id":"52d94497-b82f-4cc4-90fd-494b96237372","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:16.513802Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:65c7a1ac5e52369432d2d9aa68203eccae8070f27008304cc5089c39977a289c","observation_id":"81e695ab-a8b3-4a0d-88ef-21e85b09c461","resolution":{"observed_at":"2026-08-05T20:24:23.897682Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:23.656874Z","title":"Lester, R","venue":null,"work_id":"0c8fc594-5e6a-4b0f-9f4d-9af48dfa2002","year":2021},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:16.623185Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:b1b341d85bc19334bf934c34baa25a4504818860ea60ad6a51c1e305dfa35813","observation_id":"eaca2c8f-9fee-45bb-91af-9aee4dd73fda","resolution":{"observed_at":"2026-08-05T20:24:23.774477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.08497","last_updated":"2025-03-26T07:35:10Z","snapshot_observed_at":"2026-08-18T00:50:27.920542Z","submitted_at":"2025-03-11T14:48:01Z","title":"MMRL: Multi-Modal Representation Learning for Vision-Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.08497","snapshot_observed_at":"2026-08-05T20:24:16.679388Z","title":"Guo and X","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:16.679388Z"},"links":{"cited_paper":"/paper/2503.08497","citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:3df13b5d0263703f66e6e86642c7afcf62ff375cf7658dcc1f8f240b6ef138cf","observation_id":"15eb4b1a-5330-4c04-a667-d81df7c6f61c","resolution":{"observed_at":"2026-08-05T20:24:16.679388Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:23.467462Z","title":null,"venue":null,"work_id":"6ffe2387-4c41-4d8e-ba4e-dacdc8e7d420","year":1908},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:16.742310Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:32ba225baa8420097d0d64ae234cdacf678346cfeaed513acd04920b6cea0fa5","observation_id":"0e851ce1-b5d4-4267-9415-8299ed8a1d85","resolution":{"observed_at":"2026-08-05T20:24:23.538213Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:23.275741Z","title":null,"venue":null,"work_id":"6f9c7da9-3448-461e-9cdb-e8f70cf106aa","year":2025},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:16.838949Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:446281195cf39b1182a537945d9a0731465deb584f9eb95b37a701cfe8528cc7","observation_id":"33743227-1242-4025-bf53-34eb0639ed7e","resolution":{"observed_at":"2026-08-05T20:24:23.332651Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:23.100111Z","title":null,"venue":null,"work_id":"2d98cf6a-ffa8-4967-8238-94ac88354605","year":2023},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:16.888925Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:9d504012f5c5a9077c64c77064e310a72228fbda6f8037640c51ec448864923a","observation_id":"a3b14114-c63e-4026-9284-848927769ca8","resolution":{"observed_at":"2026-08-05T20:24:23.187706Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-05T20:24:16.986481Z","title":"Touvron, T","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:16.986481Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:a55a1a0458dba1dd452b53680b6e2c72d83f3dc0c758d9c89f70d4deab5a42af","observation_id":"1781b835-9952-4dc3-a83f-980dbad8a90a","resolution":{"observed_at":"2026-08-05T20:24:16.986481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-05T20:24:17.161679Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:17.161679Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:150b4a494baf26586aef13bfb189577c85d1e2a2e53e163f8253d55b7d185ce0","observation_id":"3e2cee13-e1db-44fd-9732-6f3d343dcd38","resolution":{"observed_at":"2026-08-05T20:24:17.161679Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:22.895594Z","title":null,"venue":null,"work_id":"28de86ca-1d8c-4f4d-9213-319e5cfc4cc1","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:17.295677Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:925c0f27c38e7243557c8ef91c08f0da3e67842a4481a76a7b74486c2fee9299","observation_id":"f9a91104-fd8c-497d-a883-a0257a76d74f","resolution":{"observed_at":"2026-08-05T20:24:22.983993Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:22.709005Z","title":null,"venue":null,"work_id":"952ef75e-1a38-4615-bf61-dba8ced150e0","year":2024},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:17.416128Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:1c9dcfcddcc6fb79d508d1556da4e20ab90563a8f27ef718c08e052339025c07","observation_id":"66e24398-cd1e-4747-835b-d687b238edad","resolution":{"observed_at":"2026-08-05T20:24:22.821429Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:22.533702Z","title":null,"venue":null,"work_id":"d5ad970b-942b-45b6-b723-9ba69aec8606","year":2025},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:17.503537Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:3213852d3d9ee8c53ee01c2ffafc80b6c1438e8876af0f5880ed6589e532ca80","observation_id":"ccccf178-b5e7-4e05-8668-eb5d25cdea1b","resolution":{"observed_at":"2026-08-05T20:24:22.612241Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:22.331631Z","title":null,"venue":null,"work_id":"221644c3-ee39-4170-8bb5-a242f9a85323","year":2009},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:17.618926Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:200c1cc7414596a658bb592db741e2d1b8420378833aafdc011cbb3e7b288c7e","observation_id":"915edd74-3bd1-4a5a-8bc4-afdedc934925","resolution":{"observed_at":"2026-08-05T20:24:22.421118Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:22.146151Z","title":"Fei-Fei, R","venue":null,"work_id":"8ccf08c3-3740-402e-bca0-88098879b1d8","year":2004},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:17.738130Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:9b376ed20a584438ea86235b79a58ad43beb3795f515ef28c8de5b2f8aef3d0e","observation_id":"03e76d62-a2d7-48bc-85dd-236182549fa9","resolution":{"observed_at":"2026-08-05T20:24:22.241061Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:21.951360Z","title":"Krause, M","venue":null,"work_id":"23ce7e5d-80e3-4e00-9a94-e1b9e0d69977","year":2013},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:17.929808Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:8b716ce23506aaefee5c56d57977867e1817481cfeda3c214e459c287953182c","observation_id":"ab55b3cc-2cb7-4174-a2d2-e7b32f341835","resolution":{"observed_at":"2026-08-05T20:24:22.036744Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:21.777409Z","title":null,"venue":null,"work_id":"4ba77460-3675-437d-b650-e297ea032956","year":2012},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:18.102594Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:f39576ec2c9e2010579cb1675c71a74cb89e48b062bb6089c866846baf407bf6","observation_id":"7a714a8b-a14c-4c15-ada6-f24e4834a8cf","resolution":{"observed_at":"2026-08-05T20:24:21.860022Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1306.5151","last_updated":"2013-06-21T14:31:57Z","snapshot_observed_at":"2026-08-12T17:35:23.022229Z","submitted_at":"2013-06-21T14:31:57Z","title":"Fine-Grained Visual Classification of Aircraft","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1306.5151","snapshot_observed_at":"2026-08-05T20:24:18.209171Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:18.209171Z"},"links":{"cited_paper":"/paper/1306.5151","citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:f3ae6838fbb6a19da1a177c77124f9d3d8573c5479e78d121e52ba9c791319e2","observation_id":"ab660ca9-efbd-4677-8f8b-24f6fb2520d0","resolution":{"observed_at":"2026-08-05T20:24:18.209171Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:21.603254Z","title":"Nilsback and A","venue":null,"work_id":"a8871eaa-ec5b-46ac-a839-e102e8f29c65","year":2008},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:18.369230Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:ffdb8e09d3e30beef205459259c0d6242351f19caec05bb79438e7f066d0e5a6","observation_id":"a8ab6a03-3ff2-4f18-b6d9-f605b9a04e89","resolution":{"observed_at":"2026-08-05T20:24:21.657966Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:21.427570Z","title":"Bossard, M","venue":null,"work_id":"84f85a2c-0ad7-4d04-9efe-e5e4c821eb6a","year":2014},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:18.457941Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:9b5668ce65c0d547a8f7940d81ddfb2f652c52fa6ebcbf371dbcdca206abee28","observation_id":"fa9fbc7a-dc49-45c1-9ce3-5eed5d90d801","resolution":{"observed_at":"2026-08-05T20:24:21.518385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:21.239837Z","title":null,"venue":null,"work_id":"b77426b1-2778-4797-9718-08e56d853c9f","year":2010},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:18.633482Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:b05fefc8eb1c01812c52cc29d224845b038441e3b02ae0a34eb982fa0e1fb78c","observation_id":"83148413-1c9a-419a-b70c-f7daca6b13ab","resolution":{"observed_at":"2026-08-05T20:24:21.326336Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:21.028972Z","title":"Cimpoi, S","venue":null,"work_id":"4928c62a-600c-4dc0-afe2-5825065c8d19","year":2014},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:18.795566Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:69efe875db8fd0798bd49f7e0ad49852321d05634705646c5bda398f2486eb3f","observation_id":"dcbdb09a-c064-4b40-baec-f550bea30268","resolution":{"observed_at":"2026-08-05T20:24:21.138045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:20.875084Z","title":"Helber, B","venue":null,"work_id":"2f2b8697-90e4-4058-bf7e-88503a1cffc1","year":2019},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:18.908232Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:0ecd7d059616c8048749c790090957685a507c81101c562d5127b47babc90b6c","observation_id":"08e09d3f-9629-47f5-a13c-47b7501917b9","resolution":{"observed_at":"2026-08-05T20:24:20.937280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1212.0402","last_updated":"2012-12-03T14:45:31Z","snapshot_observed_at":"2026-08-16T21:21:44.768787Z","submitted_at":"2012-12-03T14:45:31Z","title":"UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1212.0402","snapshot_observed_at":"2026-08-05T20:24:19.068737Z","title":"Soomro, A","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:19.068737Z"},"links":{"cited_paper":"/paper/1212.0402","citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:291520cc55f6a228a0946a1a059842c25b78b1416a22aafd8b498ed58c1304b2","observation_id":"bc86da7b-1832-444a-b8a2-684e3728071d","resolution":{"observed_at":"2026-08-05T20:24:19.068737Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:20.689038Z","title":"Recht, R","venue":null,"work_id":"ee74a2fb-a4d7-442e-a8cc-84473384f34c","year":2019},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:19.165794Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:a51acff012d8d5931892c9b99d530c5c465f5f39b43adef5d24939c631e6d8ff","observation_id":"8a5fc4e7-c4e8-4ccb-b6db-2f615c604236","resolution":{"observed_at":"2026-08-05T20:24:20.782075Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:20.542678Z","title":null,"venue":null,"work_id":"5cb096b4-0793-46b3-8189-996a6d7066ed","year":2019},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:19.318740Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:628c768b6458d10ae886055a6b74bb11233effc051dd8c4841ab169de68cd303","observation_id":"c28db5d1-6bfb-4bb7-bef4-a0d034fd1ec0","resolution":{"observed_at":"2026-08-05T20:24:20.603381Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:20.354344Z","title":"Hendrycks, K","venue":null,"work_id":"81b43e9d-8eca-4c8b-955c-61e4e8fa0b93","year":2021},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:19.433455Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:7deed488516d3bb7048c00262ab1ced3c6412e7a3d8038afdf715548a72c674a","observation_id":"076ac091-7dac-46e6-879c-437b6d8162f4","resolution":{"observed_at":"2026-08-05T20:24:20.450602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:20.160845Z","title":"Hendrycks, S","venue":null,"work_id":"c7326147-96dc-43ce-ab07-764ceb0c3d90","year":2021},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:19.550790Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:248bb5f6e04c3888ea83f015bc5c55f77ceacf401309e414db36b6493c2089b8","observation_id":"b6512033-ebd5-4491-b205-2c210a550144","resolution":{"observed_at":"2026-08-05T20:24:20.232970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T20:24:19.967349Z","title":"Paszke, S","venue":null,"work_id":"af8d8087-e739-453e-8605-dd26a0dc7169","year":2019},"citing_paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-05T20:24:19.663080Z"},"links":{"citing_paper":"/paper/2508.10645"},"observation_digest":"sha256:2eac7b5a05f655b6fec34675a9c40928eab26450fb15d122771764bc6757c11a","observation_id":"85bc4f54-8d90-466f-b194-8e066adbc900","resolution":{"observed_at":"2026-08-05T20:24:20.039503Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.10645","last_updated":"2025-08-14T13:41:59Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T02:22:04.622701Z","submitted_at":"2025-08-14T13:41:59Z","title":"SemPT: Semantic Prompt Tuning for Vision-Language Models"},"reference_resolution":{"displayed":48,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":31,"verified_exact":0,"verified_fuzzy":17},"total_outbound_references":48},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2508.10645."}