{"as_of":"2026-08-21T19:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:60cf4b109e5ea0821cbdc17be7b0ad8d219d39124ec21485479b2951726c81f9","coverage":[{"denominator":57,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":57,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:27:51.471755Z","state":"measured"},{"denominator":59,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":59,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-10T16:22:38.263172Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-11T13:36:07.653386Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"cited_work":{"arxiv_id":"2507.21072","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.21072","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Snap, segment, deploy: A visual data and detection pipeline for wearable industrial assistants","venue":null,"work_id":"9be93234-8382-4983-9922-37445e2ba76c","year":2025},"citing_paper":{"arxiv_id":"2604.10409","last_updated":"2026-04-12T02:09:19Z","snapshot_observed_at":"2026-08-11T06:43:13.554176Z","submitted_at":"2026-04-12T02:09:19Z","title":"IMPACT: A Dataset for Multi-Granularity Human Procedural Action Understanding in Industrial Assembly","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-10T16:22:38.263172Z"},"links":{"cited_paper":"/paper/2507.21072","citing_paper":"/paper/2604.10409"},"observation_digest":"sha256:183b131e03960af36199c76ab50fb998e627adb038997b9db79d2d20e2e9aea7","observation_id":"47f4f090-80ac-4cef-8858-c8f806582207","resolution":{"observed_at":"2026-05-11T09:00:58.074734Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"cited_work":{"arxiv_id":"2507.21072","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.21072","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Snap, segment, deploy: A visual data and detection pipeline for wearable industrial assistants","venue":null,"work_id":"9be93234-8382-4983-9922-37445e2ba76c","year":2025},"citing_paper":{"arxiv_id":"2604.20136","last_updated":"2026-04-22T03:03:33Z","snapshot_observed_at":"2026-08-11T14:34:45.741543Z","submitted_at":"2026-04-22T03:03:33Z","title":"IMPACT-CYCLE: A Contract-Based Multi-Agent System for Claim-Level Supervisory Correction of Long-Video Semantic Memory","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-10T01:26:42.020898Z"},"links":{"cited_paper":"/paper/2507.21072","citing_paper":"/paper/2604.20136"},"observation_digest":"sha256:f76bf179c50bf456209b595ad8a84231b81256b86968f75e30d55e87d9043570","observation_id":"6fc6ea07-ce7c-4f83-bcd8-88096c17f6dd","resolution":{"observed_at":"2026-05-11T13:36:07.662636Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.21072/citation-record","integrity":"/paper/2507.21072/integrity","json":"/paper/2507.21072/citation-record.json","paper":"/paper/2507.21072"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:27:52.349162Z","title":null,"venue":null,"work_id":"89a4703b-1563-4acd-9a5b-f38a7c1eb1da","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.209142Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:935964d1824eb2f821dae50d853d7ce908cbbbdc801b67d8bd255ac617623fb0","observation_id":"1e3d74d3-e400-4a6b-8275-5ffc3c138679","resolution":{"observed_at":"2026-08-07T05:27:52.353733Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.335224Z","title":null,"venue":null,"work_id":"09b99748-e75e-4bfc-bcc5-bbdd04b9b077","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.214543Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:84d8b609869a542485c4c2bf59676f4b90636784a9b94f6bdbb6147f49632de6","observation_id":"76fee197-a034-4dd9-9a4e-98e08cb3777a","resolution":{"observed_at":"2026-08-07T05:27:52.339715Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.320722Z","title":null,"venue":null,"work_id":"761bd9bc-8cb6-4e72-831c-51124b745448","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.219319Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:3f63d1513c8d1d49ae66ca1506e2ee2e01cb5a705abe9b060fb9c3f55199ee60","observation_id":"b5bfdae8-4c65-4d11-8f8a-c2c268e6d879","resolution":{"observed_at":"2026-08-07T05:27:52.325075Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.00714","last_updated":"2024-10-28T16:37:57Z","snapshot_observed_at":"2026-07-06T18:55:41.459417Z","submitted_at":"2024-08-01T17:00:08Z","title":"SAM 2: Segment Anything in Images and Videos","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.00714","snapshot_observed_at":"2026-08-07T05:27:51.223916Z","title":"Sam 2: Segment anything in images and videos.arXiv preprint arXiv:2408.00714, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.223916Z"},"links":{"cited_paper":"/paper/2408.00714","citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:9d4c5ba95ecb7776fbbcbb5e483fc8c1c9d20b4b9faf1ccc318bd32ee2f3a52b","observation_id":"46b19cba-4eec-4e56-add9-d5e34fa2707d","resolution":{"observed_at":"2026-08-07T05:27:51.223916Z","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":"2026-08-07T05:27:52.306081Z","title":null,"venue":null,"work_id":"7f5d96cf-56e0-4b4d-8713-543b72d103f9","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.229441Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:318541d2f90709fa7f2d02a7ac0ae8a45129d1f008a22c1864a84017754ae794","observation_id":"11ebacee-4bc6-443a-a9d1-ff5c9f994d20","resolution":{"observed_at":"2026-08-07T05:27:52.310527Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.291363Z","title":null,"venue":null,"work_id":"e552c3c5-0740-44c0-a324-50002aa38799","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.234214Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:de075c43f7ed0a4e943fe2a92cc9d9574f1580b56696a0dc05233ab5be689978","observation_id":"4cf18fa8-6e29-4d5a-a4a7-339d329bbfac","resolution":{"observed_at":"2026-08-07T05:27:52.295906Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.275136Z","title":"Iar-net: A human-object context guided action recognition network for industrial environment monitoring.IEEE Transactions on Instrumentation and Measurement, 2024","venue":null,"work_id":"fd51fc97-ea3f-4acb-88e8-3e4f4d171c65","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.239296Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:d5542fb88f1328ca5226b14b770f00e0ed57046ec6cfd64116f4ea40543488ae","observation_id":"9216d915-e233-42c5-888a-015c9d3fb630","resolution":{"observed_at":"2026-08-07T05:27:52.280171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.259817Z","title":"Retrieval-augmented generation for knowledge-intensive nlp tasks.Advances in neural information processing systems, 33:9459–9474, 2020","venue":null,"work_id":"3b415094-ac73-49c9-80dc-90469a8289ff","year":2020},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.243424Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:23508e9b6e4e5a16361d72d69bd8e0e1563de0eda65eb0b717b3ea4cf3eb9394","observation_id":"5f3cdc4d-a492-4475-b1ea-9549da306b39","resolution":{"observed_at":"2026-08-07T05:27:52.265204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.243687Z","title":"Learning deep object detectors from 3d models","venue":null,"work_id":"2039fbe4-e3e4-4166-80df-363fdeee78a2","year":2015},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.247905Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:85936ad0ecf5d7929e34dda54005bc1aed9a703e98b5f9165b99cccb6d18ed53","observation_id":"e4e53403-3eec-45ba-9e50-719513634a64","resolution":{"observed_at":"2026-08-07T05:27:52.249159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.226947Z","title":"Playing for data: Ground truth from computer games","venue":null,"work_id":"8a7b13ad-524c-42a9-9f32-078511e80d20","year":2016},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.252335Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:7316bc4118d878d6bc4f741a0506f891c7fde74bdbfaf1d5fa0d40736b698c56","observation_id":"1e8d93cc-7437-4c08-9a03-757c2824a186","resolution":{"observed_at":"2026-08-07T05:27:52.231866Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.211864Z","title":"Playing for benchmarks","venue":null,"work_id":"26e621cd-a081-4fa0-97df-284cf045cb17","year":2017},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.256918Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:28178decd81c6b69bdd395055058999d26f4435cf22205230aa898bc8248940d","observation_id":"58ee4b98-6114-4b52-bda0-599ad999b769","resolution":{"observed_at":"2026-08-07T05:27:52.216735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.196899Z","title":"Virtual worlds as proxy for multi-object tracking analysis","venue":null,"work_id":"8fcfd6b3-e1ab-402d-a033-a8a187a876df","year":2016},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.261370Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:ec168741b79808005998b675ea67908214bfc8f4c1c1ae975e03e33abc414983","observation_id":"3f6be01c-1ed1-4001-93ca-c81bf28ebdf0","resolution":{"observed_at":"2026-08-07T05:27:52.201609Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.182239Z","title":"Unlimited road-scene synthetic annotation (ursa) dataset","venue":null,"work_id":"313979b3-54e3-49ad-a09f-136ae697aff7","year":2018},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.266261Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:9fe60f5fb440997b6a701dbc4a8394035c751bd8f3642dff0e25b0f6c37acc2b","observation_id":"ec537c06-0f75-4e4d-9c5e-1f1b4015f072","resolution":{"observed_at":"2026-08-07T05:27:52.186924Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.167069Z","title":"Procsy: Procedural synthetic dataset generation towards influence factor stud- ies of semantic segmentation networks","venue":null,"work_id":"2d38ca99-899f-4cc1-8b4a-c793c62f33de","year":2019},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.270850Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:c304f8662bb12a30d6538119c528d9963db8880a191cd5fc62907be752b7b85f","observation_id":"75313099-ddc1-47e5-8310-679c1988778d","resolution":{"observed_at":"2026-08-07T05:27:52.171919Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.275198Z","title":"Domain randomization for transferring deep neural networks from simulation to the real world","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.275198Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:47c5e0b62367488274212ff243b0a1d5ab8ff4c63b46bf5f5adbf63c175475e4","observation_id":"4cc23b4b-157f-42e6-a6d8-8d91a75ffc11","resolution":{"observed_at":"2026-08-07T05:27:51.275198Z","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":"2026-08-07T05:27:52.141921Z","title":"Training deep networks with synthetic data: Bridging the reality gap by domain randomization","venue":null,"work_id":"48a3ca72-0f9b-49a6-a2f1-b3eafedcef14","year":2018},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.279531Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:d5f8370ead9b24a441bf53df28e2bd1619fef3f2c5ac3cf0d905862bcaff2de8","observation_id":"55a8411b-a973-481c-a02d-128192b72023","resolution":{"observed_at":"2026-08-07T05:27:52.146504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.11778","last_updated":"2018-06-11T09:50:33Z","snapshot_observed_at":"2026-08-14T19:13:25.929210Z","submitted_at":"2018-05-30T02:27:10Z","title":"Object Detection using Domain Randomization and Generative Adversarial Refinement of Synthetic Images","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.11778","snapshot_observed_at":"2026-08-07T05:27:51.284800Z","title":"Object detection using domain randomization and generative adversar- ial refinement of synthetic images.arXiv preprint arXiv:1805.11778, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.284800Z"},"links":{"cited_paper":"/paper/1805.11778","citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:9ad670fd7bb287960d0b9e7160eb62a30a8753a1bf093160a76932b737cc3044","observation_id":"86d4c554-56eb-40ac-ae4d-ab780d1406c6","resolution":{"observed_at":"2026-08-07T05:27:51.284800Z","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":"2026-08-07T05:27:52.126877Z","title":"Synthetic data generation based on rdb-cyclegan for industrial object detection.Mathematics, 11(22):4588, 2023","venue":null,"work_id":"fdbfd81b-ed04-4ff4-8c1a-1160e4e5a313","year":2023},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.290224Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:89be8c4e00b1225a85694b8fc097d36a0c2440e48e3af09edb61d082cd9e569b","observation_id":"88476357-3536-4afa-ab7c-26f51986fec4","resolution":{"observed_at":"2026-08-07T05:27:52.131813Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.111299Z","title":null,"venue":null,"work_id":"acbef90c-ceb1-4d6a-903f-7bdb93623065","year":2020},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.294859Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:203afd95b2267c88a79f3a508ee706d03f114c16964a51e4eea7cc3e919e90a8","observation_id":"1bc2d254-ab0f-4bae-b835-ca451befefec","resolution":{"observed_at":"2026-08-07T05:27:52.116362Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.094804Z","title":"Bigdatasetgan: Synthesizing imagenet with pixel-wise annotations","venue":null,"work_id":"f34799af-ec8d-4b8d-9c5c-b00d813aa97a","year":2022},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.299458Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:321ad8ad8c460a5dc492aa84a4ef16f6f075eea77fbacf257d50040e438f7ad5","observation_id":"26a892e2-9227-4240-9089-a46fd220651e","resolution":{"observed_at":"2026-08-07T05:27:52.099696Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.079118Z","title":"Instagen: Enhancing object detection by training on synthetic dataset","venue":null,"work_id":"dea15f54-e96c-494b-aec2-cb90586f98c6","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.304130Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:5eeffc9fa64226e342ae7b69567cb93daa6cf6f6a1a40446a847cd201a905885","observation_id":"0f4699d7-78ed-4e12-9ace-15bb841b7507","resolution":{"observed_at":"2026-08-07T05:27:52.084084Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.063999Z","title":"Cut, paste and learn: Surprisingly easy synthesis for instance detection","venue":null,"work_id":"e953e923-f5f9-458d-a029-f16ab9723372","year":2017},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.308477Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:7c0398d2e9c1d02c60babf841732e27cb1296a6e3e98896de2c1604028def95b","observation_id":"b3bbf120-56ae-4c86-9b22-29c3b9b8f434","resolution":{"observed_at":"2026-08-07T05:27:52.068892Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.048261Z","title":"The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes","venue":null,"work_id":"54eae0a0-10d9-428f-b404-328a35628b9a","year":2016},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.313837Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:9c1b38d24eecf487be6ea4fdacf413a3a08170ec02388d284698a9283316e73a","observation_id":"9dbbab89-bc95-4e32-90f3-b87aed7c14a5","resolution":{"observed_at":"2026-08-07T05:27:52.053209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:52.032763Z","title":"Rareplanes: Synthetic data takes flight","venue":null,"work_id":"21771600-1cdb-4b32-95ba-dd6bea18d3bd","year":2021},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.318318Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:d03b490351a48e6a1bc689899b3cea702f9d77e2373cd3963143df2a7fcd7fa5","observation_id":"f2c3834a-8121-4a4f-91fb-ad4cb0062703","resolution":{"observed_at":"2026-08-07T05:27:52.037567Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.322851Z","title":"Domain adaptive faster r-cnn for object detection in the wild","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.322851Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:12401f070862c27a02a1345c1057dbeec20a3b78d50ade09e995c4dfb49ec128","observation_id":"c3b771ab-4936-41b4-bdbd-b4eb74a0e7a8","resolution":{"observed_at":"2026-08-07T05:27:51.322851Z","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":"2026-08-07T05:27:52.007224Z","title":"@bench: Benchmarking vision-language models for human-centered assistive technology","venue":null,"work_id":"d2cf6dc0-38ea-4a66-a532-e8462e2bf8f8","year":2025},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.327451Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:6321d3bdcaccd46748b17f92922e11af8eba7990336c8f41a80baa348c4d518a","observation_id":"c11891e0-944f-485a-be24-71d5a783d8ea","resolution":{"observed_at":"2026-08-07T05:27:52.012300Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.991740Z","title":"Open scene un- derstanding: Grounded situation recognition meets segment anything for helping people with visual impairments","venue":null,"work_id":"299b805e-3f37-4479-8ed5-fda32d954951","year":2023},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.332125Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:c4ef419fcd6e729a80fd602e07d4eb17ef177430e25d7c1e572e7a8693759616","observation_id":"a829ae98-74d6-4102-93d5-38514eeec373","resolution":{"observed_at":"2026-08-07T05:27:51.996995Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.976851Z","title":"Materobot: Material recognition in wearable robotics for people with visual impairments","venue":null,"work_id":"af28e62e-b718-49dd-aa01-83e2bf92a28b","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.336699Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:31e86d7c046d4e44296bbc7834e30e11d508b6b5daf2b20ad118f37e7163bd5b","observation_id":"36baec43-0114-43c1-a640-2d3d24065c75","resolution":{"observed_at":"2026-08-07T05:27:51.981622Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.03118","last_updated":"2025-04-30T17:42:40Z","snapshot_observed_at":"2026-08-20T10:09:42.125433Z","submitted_at":"2024-12-04T08:38:45Z","title":"ObjectFinder: An Open-Vocabulary Assistive System for Interactive Object Search by Blind People","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.03118","snapshot_observed_at":"2026-08-07T05:27:51.341282Z","title":"Ob- jectfinder: Open-vocabulary assistive system for interactive object search by blind people.arXiv preprint arXiv:2412.03118, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.341282Z"},"links":{"cited_paper":"/paper/2412.03118","citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:af8d6cd5a51d5654d43d97a7404330fc8d02988551d6961d28997f79d7622c03","observation_id":"ab394f69-ede0-4ab3-9df8-2a8aaf93321c","resolution":{"observed_at":"2026-08-07T05:27:51.341282Z","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":"2026-08-07T05:27:51.960514Z","title":"Enhanced yolo-and wearable- based inspection system for automotive wire harness assembly.Ap- plied Sciences, 14(7):2942, 2024","venue":null,"work_id":"9b5aa979-5e77-4167-835a-041116a5ab7c","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.346645Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:bc8ce7a56a008c06951081860c1ea2b9df8dacc06161ab14703d6978f713f0fa","observation_id":"897feb98-eba4-4410-97c2-4a7df8e966e3","resolution":{"observed_at":"2026-08-07T05:27:51.966086Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.945883Z","title":"Redundant object detection method for civil aircraft assembly based on machine vision and smart glasses.Measurement Science and Technology, 33(10):105011, 2022","venue":null,"work_id":"b6d94fca-4653-45ba-9507-bd8395126ab5","year":2022},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.351260Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:37a0796027688aec8be2f0b8da79c598daa8385cb8232df529e2f8965d15374e","observation_id":"428c1188-89bf-4b20-a663-bcc818e919c3","resolution":{"observed_at":"2026-08-07T05:27:51.950620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.930216Z","title":"Validating the use of smart glasses in industrial quality control: a case study.Applied Sciences, 14(5):1850, 2024","venue":null,"work_id":"1deabf74-5f6d-4f76-a46c-ee8bae32956e","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.355895Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:677e99d4bbe9d7292c27414c388c4d8f01ff3f079e502e4563425e599dc2bf57","observation_id":"95907e53-2f00-4d18-9058-980cf3c019fd","resolution":{"observed_at":"2026-08-07T05:27:51.935632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.914393Z","title":"Augmented reality for enhanced visual inspection through knowledge-based deep learning.Structural Health Monitoring, 20(1):426–442, 2021","venue":null,"work_id":"ac23d7df-90fb-47a0-b3b1-a7d2dab80d7b","year":2021},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.360415Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:2f4465c08cc9a01ad9ebb3c1aea827a17733b29bb5d2d034228b892dd12d974e","observation_id":"752ac1a8-3440-4e15-bff1-d1d734add480","resolution":{"observed_at":"2026-08-07T05:27:51.920148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.899080Z","title":"An ar-assisted deep learning- based approach for automatic inspection of aviation connectors.IEEE Transactions on Industrial Informatics, 17(3):1721–1731, 2020","venue":null,"work_id":"cd5f0b8d-2445-4670-8d1f-23141d7da883","year":2020},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.365714Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:9cd38076e0a3973c88a1471306fa11bcc27000f675913213895fc23e287ea0bd","observation_id":"1b6079d1-acf1-42fc-90bb-a15b5a0af01f","resolution":{"observed_at":"2026-08-07T05:27:51.904452Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.883379Z","title":"Augmented reality maintenance assistant using yolov5.Applied Sciences, 11(11):4758, 2021","venue":null,"work_id":"349a2b6b-4c0f-4416-a906-a570d4b4a29f","year":2021},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.370192Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:a53530f733f1e107338e05318086e5d7b36f0c712a25127088c9f4043c232ea9","observation_id":"768fc76b-5609-4659-add6-8818fa5b3f1d","resolution":{"observed_at":"2026-08-07T05:27:51.888899Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.867782Z","title":"Deep learning-based smart task assistance in wearable augmented reality.Robotics and Computer-Integrated Manufacturing, 63:101887, 2020","venue":null,"work_id":"07616ddc-4d0a-4dc9-96cf-ba1aced05b6a","year":2020},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.374481Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:9bf8b812edf0d5bbb5d178616c6ac58761eb8cef4104168449ab41c17d2a1ca1","observation_id":"e193daa4-93b3-4215-aa57-358452b0a43b","resolution":{"observed_at":"2026-08-07T05:27:51.872715Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.852346Z","title":"A compatible detector based on improved yolov5 for hydropower device detection in ar inspection system.Expert Systems with Applications, 225:120065, 2023","venue":null,"work_id":"bcc4aa2c-a743-49b5-a0a2-f411a1ce1f17","year":2023},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.379194Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:ffcb483c68289ce2fec75e57eb2b269620964f63c1d97402612fc3d3fc5b3bcf","observation_id":"bea60c76-4046-4e15-9a63-30d1b8489b8a","resolution":{"observed_at":"2026-08-07T05:27:51.857326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.836018Z","title":"Real-time object detection and tracking in mixed reality using microsoft hololens","venue":null,"work_id":"118aadff-e72b-4337-a5d4-119f4668a1af","year":2020},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.383320Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:71c60879150e62d4f5072d3ecd1e0229866c74cb2ba9a539bc57c1205a969c7a","observation_id":"93324d3a-3274-4a02-99f0-09fca90bd717","resolution":{"observed_at":"2026-08-07T05:27:51.841735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.818852Z","title":"A real-time wearable ar system for egocentric vision on the edge","venue":null,"work_id":"5553c15c-43e2-4e2c-ac3a-8167b9128cc5","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.387438Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:b91181db98e67ba01d0ff8b8ca15d871cfaf0eb50bf6d06b7cf181a33ca25251","observation_id":"56f89993-4f4e-452c-a2ad-c1468818c120","resolution":{"observed_at":"2026-08-07T05:27:51.824341Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.802880Z","title":"Tracking multiple deformable objects in egocentric videos","venue":null,"work_id":"08c018c5-958e-481f-a47b-4bf6db1aa55e","year":2023},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.391802Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:24c3d27e279493bca0026377d0fa506ad89d9183d6514c4e757c4bf3713a0c71","observation_id":"2959fc0f-3c35-48ce-98d4-39abd764f845","resolution":{"observed_at":"2026-08-07T05:27:51.807698Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.786594Z","title":"Joint hand motion and interaction hotspots prediction from egocentric videos","venue":null,"work_id":"7b6f82b1-34f9-417b-9d04-85b934da3dd0","year":2022},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.396879Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:dc607a9d2ef92cf396f27420ddb7273439a925acb236846c1f001a597ed8e28b","observation_id":"e47ad907-881f-4d1c-82ca-5fd4dfcb5884","resolution":{"observed_at":"2026-08-07T05:27:51.792042Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.769712Z","title":"A wearable assistive system for the visually impaired using object detection, distance measurement and tactile presentation.Intell","venue":null,"work_id":"0230cb79-381a-4ec5-9be2-b29dfd50057e","year":2023},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.401837Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:857e2bb0fae51dbfb2c0b642ffc116fc8bcaa025fd6c1dfe19f896b6fad9c171","observation_id":"6291519b-fbe6-4557-970b-5e8669a649b5","resolution":{"observed_at":"2026-08-07T05:27:51.775577Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.754157Z","title":"A google glass based real-time scene analysis for the visually impaired.IEEE Access, 9:166351–166369, 2021","venue":null,"work_id":"02b9e7b5-8d16-4fe5-8ffd-9389caf816eb","year":2021},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.406260Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:a4c2f7c62e02ba9058cc5833986de86ba72b6f7f4fd794b5572116bda0931df2","observation_id":"943450f1-a706-4649-883f-531037962d9a","resolution":{"observed_at":"2026-08-07T05:27:51.759073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.738731Z","title":"Underwater smart glasses: A visual-tactile fusion hazard detection system.Iscience, 27(4), 2024","venue":null,"work_id":"14cc79ca-9f48-447d-81a3-f1fd5aa99666","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.410426Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:9571c650730091328fa4fa754d4c00fab02aa898fc237753815f316e7ae05718","observation_id":"9709b8e3-2d23-47f7-9c22-f276db90be3d","resolution":{"observed_at":"2026-08-07T05:27:51.743599Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.415691Z","title":"Egocentric video-language pretraining.Advances in Neural Information Processing Systems, 35:7575–7586, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.415691Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:94d60d5a76bf58b461760e7241ee77a44a86a46fb4beabf3f3f93527c09c5965","observation_id":"f0ed710e-b2b8-4742-9e6c-5b0da6f0ddd6","resolution":{"observed_at":"2026-08-07T05:27:51.415691Z","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":"2026-08-07T05:27:51.712935Z","title":"Self-adapting large visual-language models to edge devices across visual modalities","venue":null,"work_id":"90c6fa6d-f63a-44be-88c1-d17870474679","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.420109Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:e006f01195462aa113ee5afecbe70513c91cef7b7b4d166caaee5788e44024b6","observation_id":"4b052d9a-b312-4661-8ef4-39dc33bfe8b9","resolution":{"observed_at":"2026-08-07T05:27:51.718206Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.04250","last_updated":"2025-03-06T09:33:46Z","snapshot_observed_at":"2026-08-16T12:52:34.840229Z","submitted_at":"2025-03-06T09:33:46Z","title":"An Egocentric Vision-Language Model based Portable Real-time Smart Assistant","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.04250","snapshot_observed_at":"2026-08-07T05:27:51.424586Z","title":"An egocentric vision-language model based portable real-time smart assistant.arXiv preprint arXiv:2503.04250, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.424586Z"},"links":{"cited_paper":"/paper/2503.04250","citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:4198905e5afad0ba23ae605037b5c2cb3fd4824b492d8da9f8e10962c5bc43f3","observation_id":"2da05770-ffb4-4171-a636-809a6e8fb624","resolution":{"observed_at":"2026-08-07T05:27:51.424586Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.17725","last_updated":"2024-10-23T09:55:22Z","snapshot_observed_at":"2026-08-13T01:57:27.555320Z","submitted_at":"2024-10-23T09:55:22Z","title":"YOLOv11: An Overview of the Key Architectural Enhancements","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.17725","snapshot_observed_at":"2026-08-07T05:27:51.429662Z","title":"Yolov11: An overview of the key architectural enhancements.arXiv preprint arXiv:2410.17725, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.429662Z"},"links":{"cited_paper":"/paper/2410.17725","citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:bea581aa03e826f357736609b34ac6e5201d398657b4691a88192041124934b5","observation_id":"42fed762-b8b8-46a8-8ec9-d9c84fbcd856","resolution":{"observed_at":"2026-08-07T05:27:51.429662Z","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":"2026-08-07T05:27:51.434311Z","title":"Sentence-bert: Sentence embed- dings using siamese bert-networks","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.434311Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:ac2a9b6ecb8e87a279fa8534fa748292ca38ba5fd5a7ddb73a85f6e91fade9b6","observation_id":"00602ea8-38dc-4392-a6a4-3ffbc90334d7","resolution":{"observed_at":"2026-08-07T05:27:51.434311Z","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":"2026-08-07T05:27:51.438479Z","title":"The faiss library","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.438479Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:c8d9a00181c6835009ccf856f147fc3d3f209afbac9c35cce626f87ed5b6d463","observation_id":"6b347b0c-2979-4842-9b68-1205de56b782","resolution":{"observed_at":"2026-08-07T05:27:51.438479Z","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":"2026-08-07T05:27:51.676412Z","title":"Depth anything: Unleashing the power of large-scale unlabeled data","venue":null,"work_id":"e54ea6ee-88ef-4f20-952c-350052152b84","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.443824Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:d7522cb3d2518df9e7c898501d98f0c99a8021fc98ba6042747cd35883d97000","observation_id":"52e7dce8-0007-4c0b-8489-f5e15cb5d6de","resolution":{"observed_at":"2026-08-07T05:27:51.682081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.14219","last_updated":"2024-08-30T21:17:17Z","snapshot_observed_at":"2026-08-17T03:25:04.404839Z","submitted_at":"2024-04-22T14:32:33Z","title":"Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.14219","snapshot_observed_at":"2026-08-07T05:27:51.448766Z","title":"Phi-3 technical report: A highly capable language model locally on your phone.arXiv preprint arXiv:2404.14219, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.448766Z"},"links":{"cited_paper":"/paper/2404.14219","citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:2e647d7f61ee1c0263bff80401d111055e568921e2bad22d8586167fe176c583","observation_id":"7f3201c5-f750-41e3-813c-ea4113a6ef9e","resolution":{"observed_at":"2026-08-07T05:27:51.448766Z","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":"2026-08-07T05:27:51.659716Z","title":"Robust speech recognition via large- scale weak supervision","venue":null,"work_id":"dc35148e-0624-4f74-afdf-2e90c0da8660","year":2023},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.453789Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:4d7b84f5846368ba0c6904cf276bf3e70a81123a8231e96af08f7df7544029e9","observation_id":"c1bce553-e710-4dc5-8dfe-6428dbf66f2b","resolution":{"observed_at":"2026-08-07T05:27:51.664648Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.643792Z","title":"pyttsx3.https://github.com/nateshmbhat/ pyttsx3, 2024","venue":null,"work_id":"ee83d553-d894-4e1b-8d14-deac6d633a2b","year":2024},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.458298Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:8cde08fde1ee188ffdd3c5c77f6fcfd781429b3099795369387f1a8fcfe55492","observation_id":"a93d0dba-2182-4ab4-be89-4cfcaec3ad46","resolution":{"observed_at":"2026-08-07T05:27:51.649066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.628265Z","title":"Slic- ing aided hyper inference and fine-tuning for small object detection","venue":null,"work_id":"c5c4b298-239e-4af2-b142-a336570a8ffb","year":2022},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.462691Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:8093af8db9310fe4333ef9d0705f659e6e3f5c5f2d34ad53897b0492dabe5a67","observation_id":"68cd7fe9-8d7a-4260-9c62-a728342263c1","resolution":{"observed_at":"2026-08-07T05:27:51.633049Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.612739Z","title":"Development of nasa-tlx (task load index): Results of empirical and theoretical research","venue":null,"work_id":"006224ce-f614-477d-922f-3392d19f218c","year":1988},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.467323Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:9cbd0eb3c8065d7c8d27a490ec862669e554305346ff0f3b905ad8ea4d80f130","observation_id":"55341d70-bdb2-44ff-ab49-49b02f15632c","resolution":{"observed_at":"2026-08-07T05:27:51.617777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+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":"2026-08-07T05:27:51.595341Z","title":"How high is high? a meta-analysis of nasa-tlx global workload scores","venue":null,"work_id":"0fdd6090-ef45-4f70-9849-380d457a9849","year":2015},"citing_paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T05:27:51.471755Z"},"links":{"citing_paper":"/paper/2507.21072"},"observation_digest":"sha256:11b902db3c91d027290cf7d081af9ace9a540b6ea364f6e58dfb462afcd757ac","observation_id":"40e9cdd7-156b-439b-be46-6d88c8e9b8f4","resolution":{"observed_at":"2026-08-07T05:27:51.601931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.21072","last_updated":"2025-06-09T15:40:14Z","latest_version":1,"primary_category":"cs.HC","snapshot_observed_at":"2026-08-18T16:23:49.020052Z","submitted_at":"2025-06-09T15:40:14Z","title":"Snap, Segment, Deploy: A Visual Data and Detection Pipeline for Wearable Industrial Assistants"},"reference_resolution":{"displayed":57,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":0,"verified_fuzzy":40},"total_outbound_references":57},"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":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 2 inbound Pith citation observations for arXiv:2507.21072."}