{"as_of":"2026-08-23T17:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9bd7edb20a1dcad343475d0e2ca32e6b37595a9a4b9ba79d9a5cdea050a464b2","coverage":[{"denominator":33,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T20:11:41.947172Z","state":"measured"},{"denominator":33,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":33,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+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/2501.09355/citation-record","integrity":"/paper/2501.09355/integrity","json":"/paper/2501.09355/citation-record.json","paper":"/paper/2501.09355"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T20:11:42.694054Z","title":"Do, Karan Ahuja, Eric J","venue":null,"work_id":"7ebb07de-be3b-450e-b1b6-d811d7297de1","year":2024},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.793477Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:78137370adf026ee6a1771fdf3c5d0aec213f693a5b18cffdac730e58b6c8f7a","observation_id":"0e681961-342b-4112-9361-aac2abe24dde","resolution":{"observed_at":"2026-08-10T20:11:42.698506Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.677734Z","title":"Tal- lyqa: Answering complex counting questions","venue":null,"work_id":"9e2ab5ed-6f92-48f1-8fb1-7036394d9659","year":2019},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.799055Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:291d0ce3699dbde328d422e8f71ce62a0acc20f423eb7a3fb0b9e1288ba84634","observation_id":"42e43ad7-f328-47a1-8e7f-ec6f2ae6d8bb","resolution":{"observed_at":"2026-08-10T20:11:42.683844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.661264Z","title":"Paligemma: A versatile 3b vlm for trans- fer, 2024","venue":null,"work_id":"f9f28a32-1401-4db9-a3ac-75c6832d3468","year":2024},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.803915Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:973b457ee26cd5520bf62a6a4b3f18fc268e8144ea61e13fbdf0a42cb44522e7","observation_id":"9f4aa584-69f0-428b-bf62-a68a7ce61d62","resolution":{"observed_at":"2026-08-10T20:11:42.666170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.642206Z","title":"ProMISe: A proactive multi-turn dialogue dataset for information-seeking intent resolution","venue":null,"work_id":"7740c689-80ef-4ed4-b842-742eb4c8c418","year":2024},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.808894Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:cdfdcfac88c85520eeca7a00a1b6d62d3f6c7fdec5bcd78996c8c11b9f45a66a","observation_id":"67931a41-b041-4267-b1c5-ea81c438d95b","resolution":{"observed_at":"2026-08-10T20:11:42.648143Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.624143Z","title":"Baki Ko- caballi","venue":null,"work_id":"86c20e20-c0f2-4200-9723-cdd1fa2c5727","year":2024},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.814825Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:0808911487e78215c98ed5348c3e40554e189bce8371b79f002f776abbdeaae9","observation_id":"454af8d8-bb06-4b09-8fb9-6cf643e9e5f9","resolution":{"observed_at":"2026-08-10T20:11:42.629970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.607707Z","title":"Smart help: Strategic opponent modeling for proactive and adaptive robot assistance in households","venue":null,"work_id":"ca4489e8-7a4e-4266-944e-666d12e4e1ef","year":2024},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.819860Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:45bc3e621318cb4e1051b3b235a75f988d9f8f0f01c164cf559a124e7536c124","observation_id":"9a4bd676-42d2-4acb-baa6-7e140b34bca8","resolution":{"observed_at":"2026-08-10T20:11:42.612425Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.590423Z","title":"Scaling egocentric vision: The epic-kitchens dataset","venue":null,"work_id":"cefcf198-1649-4138-9ea8-796b5182207c","year":2018},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.825315Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:4c0c28976e80f9c2aacd743381d9fce1a1321d0a8b5a726eae4b9fef2cb09598","observation_id":"87fc992e-9c0d-4837-8978-39e447b94bef","resolution":{"observed_at":"2026-08-10T20:11:42.596453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.465150Z","title":"Towards human-centered proactive con- versational agents","venue":null,"work_id":"f7f2848b-02ad-4722-a37f-907fd1a2a385","year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.830846Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:2bd3d55924ad6def50d93e08c0815543f01b99c73ad312b8c1d7e9517fa010b5","observation_id":"c55bc85a-d333-4c96-b4e5-807f32af8d79","resolution":{"observed_at":"2026-08-10T20:11:42.470235Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.438572Z","title":"Prego: online mistake detection in procedural ego- centric videos","venue":null,"work_id":"bf0a3c17-3c07-4494-b234-a9c105ca12c3","year":2024},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.840260Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:d045c28dbfdff35a09c165f755f75f2ac1f5bef48625f5aff880c10726967d22","observation_id":"b5af7406-ceec-4685-bc5a-da8679066694","resolution":{"observed_at":"2026-08-10T20:11:42.443839Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.421846Z","title":null,"venue":null,"work_id":"a787a3d9-0513-4123-bbf4-0348fb15d572","year":2022},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.845182Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:e1ad9b47f8f9912679e8e1e4c745ccfde3a04a9d8cbf089f939c10bd97297f1d","observation_id":"c510b510-9d7e-42f6-9a3d-40e01b8c4e88","resolution":{"observed_at":"2026-08-10T20:11:42.427272Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.405058Z","title":null,"venue":null,"work_id":"ae45172e-dec9-484f-b93f-23c6e7590897","year":2024},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.850122Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:18838d349dee270eeba2e07f57f4ca3e7e71b766a7d7d6e528dbb49067c31ea2","observation_id":"7d1010cf-1457-4732-9afc-a382178bd33d","resolution":{"observed_at":"2026-08-10T20:11:42.410710Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.387076Z","title":"Proactive con- versational agents in the post-chatgpt world","venue":null,"work_id":"a403e71f-36f3-435e-bbf1-df6e436b8cb9","year":2023},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.854804Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:35ad3f098d335fb83b4c4ceb277db8b05781280888999f4998829a982823900e","observation_id":"05bab867-27a0-4afa-8263-799573d845bf","resolution":{"observed_at":"2026-08-10T20:11:42.392700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.372714Z","title":"Proactive agent: Shift- ing llm agents from reactive responses to active assistance,","venue":null,"work_id":"524c7367-6b2f-4b30-aeba-9ee9e48a0270","year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.859125Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:d5fcba6e6b48a041bf48291f93005deb8cec6ae1d1fa4f66ebeefce0a9cdb51a","observation_id":"87fa43ee-cf64-4437-ae87-7debe7498e56","resolution":{"observed_at":"2026-08-10T20:11:42.377525Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.08379","last_updated":"2025-07-16T09:17:10Z","snapshot_observed_at":"2026-08-16T13:43:40.401834Z","submitted_at":"2024-06-12T16:29:45Z","title":"Gazing Into Missteps: Leveraging Eye-Gaze for Unsupervised Mistake Detection in Egocentric Videos of Skilled Human Activities","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.08379","snapshot_observed_at":"2026-08-10T20:11:41.864013Z","title":"Eyes wide unshut: Unsupervised mistake detec- tion in egocentric video by detecting unpredictable gaze","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.864013Z"},"links":{"cited_paper":"/paper/2406.08379","citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:7e8bb8412f9d5ec2db979e8646d106cf0b349cbf675c479dab3b5512781c05c2","observation_id":"d34a8be8-b277-4ad6-83f8-89586a616c93","resolution":{"observed_at":"2026-08-10T20:11:41.864013Z","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":"2026-08-10T20:11:41.868991Z","title":"Ti-prego: Chain of thought and in- context learning for online mistake detection in procedural egocentric videos","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.868991Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:2fb10511b766a1cd428cfd73ed044444f966f0ca5c9ce7abdf59a7f6491b4caa","observation_id":"d5184cee-5108-4b6c-bb59-940b800fac0c","resolution":{"observed_at":"2026-08-10T20:11:41.868991Z","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":"2026-08-10T20:11:42.358894Z","title":"Quasi-online detection of take and re- lease actions from egocentric videos","venue":null,"work_id":"f48f6e5d-b4d2-4e75-96f2-03e07ec6e862","year":2023},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.873455Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:c4898ad093bbb4915ee916154c6e34f1239dfbc397d60f8f455b8c580ea65049","observation_id":"7409bc47-403d-41d3-b86a-72bcef2482b4","resolution":{"observed_at":"2026-08-10T20:11:42.363310Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.01486","last_updated":"2025-01-09T10:56:43Z","snapshot_observed_at":"2026-08-20T14:03:04.547729Z","submitted_at":"2024-06-03T16:11:39Z","title":"Differentiable Task Graph Learning: Procedural Activity Representation and Online Mistake Detection from Egocentric Videos","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01486","snapshot_observed_at":"2026-08-10T20:11:41.878094Z","title":"Differentiable task graph learning: Procedural ac- tivity representation and online mistake detection from ego- centric videos","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.878094Z"},"links":{"cited_paper":"/paper/2406.01486","citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:068ebb83087499fb07c6848869b0522b72c59a5658937eb6142895dde2c808be","observation_id":"d577182a-242e-4fe5-a911-6ea6fec8b72b","resolution":{"observed_at":"2026-08-10T20:11:41.878094Z","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":"2026-08-20T18:27:04.837880Z","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":"2026-08-10T20:11:41.882927Z","title":"Gemini: a family of highly capable multimodal models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.882927Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:062543ab5bdc828abca6318cb2d38d61e7fd829fecfd928447f5475b0f8f573f","observation_id":"5ed5520a-0b57-4ca6-b2dd-8b20a6864717","resolution":{"observed_at":"2026-08-10T20:11:41.882927Z","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":"2026-08-10T20:11:42.343134Z","title":"Meta smart glasses—large language models and the future for assistive glasses for individuals with vision impairments","venue":null,"work_id":"535eb55a-4650-4361-96f0-8eef9da33bf4","year":2024},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.888494Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:6d2b52ca3204d77c390c0eb42c98456db841471c32820a9cbbee61e711c60ff7","observation_id":"4e50659c-6709-45c1-94d8-38efefff046b","resolution":{"observed_at":"2026-08-10T20:11:42.348174Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.327582Z","title":"Oadtr: Online action detection with transformers","venue":null,"work_id":"b03171e3-7dcf-488c-915a-ae9e743e6688","year":2021},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.893664Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:47882ebdda923160aeb15294efbf933c872839659d96c738084b76fae17f6c05","observation_id":"2ca7540c-34f2-4b51-ae96-4894c001bf7a","resolution":{"observed_at":"2026-08-10T20:11:42.332666Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T20:11:41.897674Z","title":"Holoassist: an egocen- tric human interaction dataset for interactive ai assistants in the real world","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.897674Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:33a6c6e778ab33f253c81336501af1788522d2bc904eb773709ce0b517f10ec1","observation_id":"50632b59-8a3c-499c-93fc-7f2348665d48","resolution":{"observed_at":"2026-08-10T20:11:41.897674Z","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":"2026-08-10T20:11:41.901755Z","title":"Image quality assessment: from error visibility to structural similarity","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.901755Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:36ed7d7d6f06522dc9735c777090b81b7c782857ea56f9de3115ab97df4d23cd","observation_id":"617025da-65d8-4e3d-a9b1-b3be632ae553","resolution":{"observed_at":"2026-08-10T20:11:41.901755Z","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":"2026-08-10T20:11:42.291298Z","title":"Proagent: Building proac- tive cooperative agents with large language models","venue":null,"work_id":"8603e587-9297-4bb9-abe5-f7633f08befe","year":2024},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.905841Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:2bb18e0d44678cd297fba1c30927bca27022a0c85708bb439c055aff379d30b2","observation_id":"d3ab8d16-3fa0-4290-91dd-cd2972ccce0a","resolution":{"observed_at":"2026-08-10T20:11:42.296898Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.274590Z","title":null,"venue":null,"work_id":"b3347a3c-e014-426e-85d0-b9ebab379c36","year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.909801Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:075dba7dcabce200ac0fac673ed6ab275f217f42b0aa466b84769d82fe0c39cb","observation_id":"3a267506-fc3f-4687-b463-425b909f50ce","resolution":{"observed_at":"2026-08-10T20:11:42.279730Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.257685Z","title":null,"venue":null,"work_id":"0dcdb4c5-15e3-4ab5-9701-330a6bd30968","year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.914793Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:0c8398b946d3af852a300120e4f781b52fbcdcc4e52a8fe4e1b0e5c806a94314","observation_id":"e6fd86a6-e103-453f-9b30-1151832a5688","resolution":{"observed_at":"2026-08-10T20:11:42.263337Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.241606Z","title":null,"venue":null,"work_id":"a3543ca8-4406-4a29-8e14-4926140d68a7","year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.919319Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:afc907d3eb1d4dbeb1249b73acea5bcc5d8f2049d868922a2dcd8d564179cc6d","observation_id":"e58cdaf7-ba8b-4afb-83c3-13ca4ccab48b","resolution":{"observed_at":"2026-08-10T20:11:42.246301Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.224239Z","title":"This work concentrates on identifying ”take” and ”release” ac- tions—instances where the user’s hands interact with ob- jects—rather than on mistake or intervention detection","venue":null,"work_id":"c288d549-2f10-43e9-872f-c028c5623f1e","year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.923812Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:864f043da902af1741d4a0263c8dac141ab8a14245d61373f557b2ca6533e281","observation_id":"1882db0d-7822-4003-83df-432185893c40","resolution":{"observed_at":"2026-08-10T20:11:42.229751Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.207470Z","title":"Agent Conversation Interval The Agent Conversation Interval is a parameter for how long we suppose it will take a user to respond to an inter- vention by the AI Agent","venue":null,"work_id":"10d2c37e-f48e-4a7c-90d2-725aa79ce019","year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.928394Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:9243221abe90d5259133a39e8b777d39af83213672af1ae85cbf551e409603e1","observation_id":"9a7b5fa9-44cc-4561-a273-a9a90a8dd50f","resolution":{"observed_at":"2026-08-10T20:11:42.212392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.192030Z","title":null,"venue":null,"work_id":"f66fb24a-e01a-4f2d-8e91-3215db0b9205","year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.933228Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:f36f98bbd7665bf881a82ee010cb640b7374cca018559a53051f0ff02c3fc8d1","observation_id":"fc84db2f-e69d-4afa-baa9-f0e691440510","resolution":{"observed_at":"2026-08-10T20:11:42.196805Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.176649Z","title":null,"venue":null,"work_id":"a33123a3-92c4-471d-bb84-fcc7faf89e0f","year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.937856Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:78ec0768e1a5d1cf8e912d49e9515cffa2655654aa63123ec0ca8358a9b6531e","observation_id":"aba9e32b-bfc5-42b1-99f0-680d1f13d209","resolution":{"observed_at":"2026-08-10T20:11:42.181108Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.160954Z","title":"If the user inter- acts with a live wire while the power is on they could be seriously injured","venue":null,"work_id":"0ea4a796-8fb4-4090-a729-7f37779d17af","year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.942631Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:03ba9df0c1f959ffb542d42f3c15548aba7caa7e9361eeb2b7a0edb0ed2aac54","observation_id":"9f5c09bf-f4a4-4015-ab2f-69dd9264b739","resolution":{"observed_at":"2026-08-10T20:11:42.165641Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-10T20:11:42.141605Z","title":"This would be especially useful for fixing a motorcycle, which is often done by expert mechanics","venue":null,"work_id":"1cd48d86-9982-47bb-a03f-9befcb230bbb","year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.947172Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:9bba846b13536d961e5e40444e7496270e91e089d4e7f6d3677fb6be1eea61b1","observation_id":"cab1358e-7bba-4cb6-bdf8-d04586ccf167","resolution":{"observed_at":"2026-08-10T20:11:42.149602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T20:11:41.835656Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-10T20:11:41.835656Z"},"links":{"citing_paper":"/paper/2501.09355"},"observation_digest":"sha256:957632cfdc4d40a7e33135d5c377910656f20623e57c35f603f57f1573b3dbc8","observation_id":"5e7bdce6-772b-47df-9539-1eccdf2b5fbb","resolution":{"observed_at":"2026-08-10T20:11:41.835656Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.09355","last_updated":"2025-01-16T08:06:02Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-14T02:13:49.199000Z","submitted_at":"2025-01-16T08:06:02Z","title":"YETI (YET to Intervene) Proactive Interventions by Multimodal AI Agents in Augmented Reality Tasks"},"reference_resolution":{"displayed":33,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":13,"verified_exact":0,"verified_fuzzy":19},"total_outbound_references":33},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 23 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2501.09355."}