{"as_of":"2026-08-20T16:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0cf094df9deadc048654d5fd4b112fb888ba5695ae0072aee91e3213d78e9d6a","coverage":[{"denominator":44,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":44,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T09:10:45.572292Z","state":"measured"},{"denominator":44,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":44,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.20874/citation-record","integrity":"/paper/2607.20874/integrity","json":"/paper/2607.20874/citation-record.json","paper":"/paper/2607.20874"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T09:10:40.144916Z","title":"Cdul: Clip-driven unsupervised learning for multi-label image classification, in: Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pp","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:40.144916Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:6f9c389432026fba9706f010fdcbda29a3046e44a8c19702ae193a565fdfaf2a","observation_id":"bcfb8ce5-b2b3-4eb4-91ec-54480b013a91","resolution":{"observed_at":"2026-08-01T09:10:40.144916Z","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":"2026-08-01T09:10:40.208302Z","title":"Laso: Label-set operations networks for multi-label few-shot learning, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:40.208302Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:843a7f95d4fe4bc520fcc1c1d32349ecc7031c932f72e66ace6bf6d8972280ac","observation_id":"65a8c91d-4b06-48e6-8da4-f08f3200f692","resolution":{"observed_at":"2026-08-01T09:10:40.208302Z","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":"2026-08-01T09:10:40.380493Z","title":"Multi-label image recognition with two-stream dynamic graph convolution networks","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:40.380493Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:07758684bb6c85cebd3d5f36de9b682ca9cbdc9dfe0d0b62adbaa5f3eb0b4aaa","observation_id":"c3e66cd5-2e9b-4c06-9a83-1ecbf2baaff8","resolution":{"observed_at":"2026-08-01T09:10:40.380493Z","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":"2026-08-01T09:10:40.534619Z","title":"Learning spatial-temporal coherent correlations for speech-preserving facial expression manipulation","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:40.534619Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:da7cb9e5713d2fc072ff6fffd4b7ea5c231f13f9df2996f80125d6d6296dfe1b","observation_id":"d0b76b04-bd16-4ad6-afa9-008aff53bdde","resolution":{"observed_at":"2026-08-01T09:10:40.534619Z","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":"2026-08-01T09:10:40.623285Z","title":"Knowledge-guided multi-label few-shot learning for general image recognition","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:40.623285Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:545073bff1798357b7bc7dd89216c83ec2924c30b74d42c41de551b5722b2342","observation_id":"5a30b941-012e-479a-813e-5e1b1450aa05","resolution":{"observed_at":"2026-08-01T09:10:40.623285Z","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":"2026-08-01T09:10:40.770722Z","title":"Heterogeneous semantic transfer for multi-label recognition with partial labels","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:40.770722Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:007a2542d8fb6f1fe853d794c0e1c77a78ac8685aa9530a1e3437ca6f9327003","observation_id":"0ff7e480-50b4-402c-8227-1a73117d8cfd","resolution":{"observed_at":"2026-08-01T09:10:40.770722Z","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":"10.1609/aaai.v36i1.19910","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Structured semantic transfer for multi-label recognition with partial labels, in: Proceedings of the AAAI Conference on Artificial Intelligence, pp","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","work_id":"bc886515-f9a2-4d5d-88b9-fcccd600feb4","year":null},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:40.963207Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:451805c00f0d8ac860cb2d544ad86f1085b36998dde315596f88b49cf87c8565","observation_id":"8817d8b3-50a8-4fa7-b7a4-2b6e45f5171d","resolution":{"observed_at":"2026-08-01T09:13:28.471269Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-01T09:10:41.151442Z","title":"Cross-domain facial expression recognition: A unified evaluation benchmark and adversarial graph learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:41.151442Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:2e8ccf56bc55e57bddf67d217864ee4841c0577e87380db4ca8c56b54a727863","observation_id":"d25d2d47-1446-4dbc-b03b-4297c6c252d5","resolution":{"observed_at":"2026-08-01T09:10:41.151442Z","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":"2026-08-01T09:10:41.335751Z","title":"Dynamiccorrelationlearningandregularizationformulti-labelconfidence calibration","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:41.335751Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:b78bac207fdd2d5cfb71616aa34c6e1a40d16a01f369fd8726c2d4b08d6e96e6","observation_id":"35f033f7-9a3d-40a4-80b4-3fcb9cedc554","resolution":{"observed_at":"2026-08-01T09:10:41.335751Z","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":"2026-08-01T09:10:41.490161Z","title":"Learning semantic-specific graph representation for multi-label image recognition, in: Proceedings of the IEEE International Conference on Computer Vision, pp","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:41.490161Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:bfe2e7b917cb83722902020387fe20818e50ca4e14d85e76d88dd3b0fdb6441d","observation_id":"021a5afa-8f47-4423-98fb-c0ba5ea64f69","resolution":{"observed_at":"2026-08-01T09:10:41.490161Z","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":"2026-08-01T09:10:41.638874Z","title":"Webly supervised learning of convolutional networks, in: Proceedings of the IEEE international conference on computer vision, pp","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:41.638874Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:baf84daebe10d4c5ffac63789c2b386f4494310ae453b1880e8855f3f01f04d8","observation_id":"774cd0d4-4f6e-484e-9dd9-542a49e49763","resolution":{"observed_at":"2026-08-01T09:10:41.638874Z","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":"2026-08-01T09:10:41.787738Z","title":"Learning graph convolutional networks for multi-label recognition and applications","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:41.787738Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:6177f95f217d1bfe1d66034330a27fe12ac8ed30407fd4e4254d8284cb280917","observation_id":"bab59a8d-c1c8-4e39-b6dd-3c5be986a316","resolution":{"observed_at":"2026-08-01T09:10:41.787738Z","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":"2026-08-01T09:10:41.941139Z","title":"Multi-label image recognition with graph convolutional networks, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:41.941139Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:f4b64d43747e56a9c8c45b03be0285ca9dd6a895cd3d524b29f1dbea2c31db8c","observation_id":"95de0af0-e311-410f-aac4-3e1420817fd1","resolution":{"observed_at":"2026-08-01T09:10:41.941139Z","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":"2026-08-01T09:10:42.153572Z","title":"Imagenet: A large-scale hierarchical image database, in: Computer Vision and Pattern Recognition, 2009","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:42.153572Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:2318de30fdbc390b837cf8de6581ebfd922b0b7c3492791597973c9169d208da","observation_id":"24abf0cf-924a-48f1-ba96-0c12156be71a","resolution":{"observed_at":"2026-08-01T09:10:42.153572Z","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":"2026-08-01T09:10:42.313690Z","title":"A multi-label classification method based on transformer for deepfake detection","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:42.313690Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:44b0b4146d4bb2a2a225e8dbe0771ba8a87552cb1f93534d569bf1e9e261f1a6","observation_id":"5e5c1685-56b4-49f9-ac2d-efcbbaf929e4","resolution":{"observed_at":"2026-08-01T09:10:42.313690Z","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":"2026-08-01T09:10:42.440227Z","title":"Learning a deep convnet for multi-label classification with partial labels, in: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:42.440227Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:8b7969b04a30875978c68111b7014ca8ada667d739c769d7f01d6996adbc94ae","observation_id":"71ee6bc9-a6d2-4924-b255-9e7f1d18af44","resolution":{"observed_at":"2026-08-01T09:10:42.440227Z","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":"2026-08-01T09:10:42.568020Z","title":"Thepascalvisualobjectclasses(voc)challenge","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:42.568020Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:b58f166791e37d3237d5b6831bcb20a439d7967124f789a4c0055b0df7619fce","observation_id":"edc671d8-55bd-4f10-bf81-458808df38e1","resolution":{"observed_at":"2026-08-01T09:10:42.568020Z","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":"2026-08-01T09:10:42.699141Z","title":"Deep residual learning for image recognition, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:42.699141Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:48030664dcb1473334dc76455407b8f3372e07a4991bc55dae6c382e6c61b21d","observation_id":"c5ee992b-0a93-41ab-aff5-813892fdb457","resolution":{"observed_at":"2026-08-01T09:10:42.699141Z","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":"2026-08-01T09:10:42.768601Z","title":"Noisy multi-label learning through co-occurrence-aware diffusion","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:42.768601Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:7aa3edc4e82d5a3caec6114428ebcdfe8c6e88f4be5533ccb203d0f1a481dc18","observation_id":"d1755696-f487-4ced-9449-cb6c77ec9621","resolution":{"observed_at":"2026-08-01T09:10:42.768601Z","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":"2026-08-01T09:10:42.895074Z","title":"Interactive multi-label cnn learning with partial labels, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:42.895074Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:10951ee17c863865015b8132a3f776d79be1190293d66594edb3e694bb26b3cf","observation_id":"f63b7b65-2690-42be-abf9-1d1ce7526f3e","resolution":{"observed_at":"2026-08-01T09:10:42.895074Z","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":"2026-08-01T09:10:42.990168Z","title":"Classifier-guided clip distillation for unsupervised multi-label classification, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:42.990168Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:0c042ee7e4ef43d986a41dd31c505929577ade0c8026fcb5951eaf522ef92113","observation_id":"0ad6b7ad-4971-4ae3-b398-29409b55a1ca","resolution":{"observed_at":"2026-08-01T09:10:42.990168Z","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":"2026-08-01T09:10:43.091751Z","title":"Large loss matters in weakly supervised multi-label classification, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:43.091751Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:4a9c9b5767217907a69727612506282564ead67e7b9ebe9d711e2c0c542482b9","observation_id":"efa1dc5d-edb3-4c3b-a679-5aa6149213f4","resolution":{"observed_at":"2026-08-01T09:10:43.091751Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-01T09:10:43.194082Z","title":"Adam: A method for stochastic optimization","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:43.194082Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:3e83b08a08f9ad576e11dfb9c64e7181b39c8780715ed9247dd50e7d3f327d3f","observation_id":"94b1803b-c301-435c-834c-d088d4c0ea04","resolution":{"observed_at":"2026-08-01T09:10:43.194082Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2009.07995","last_updated":"2020-09-17T00:59:59Z","snapshot_observed_at":"2026-08-18T08:19:24.542096Z","submitted_at":"2020-09-17T00:59:59Z","title":"MoPro: Webly Supervised Learning with Momentum Prototypes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2009.07995","snapshot_observed_at":"2026-08-01T09:10:43.288317Z","title":"Mopro: Webly supervised learning with momentum prototypes","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:43.288317Z"},"links":{"cited_paper":"/paper/2009.07995","citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:42003df50f52d24b8b612913d8175f938ba80d3e7563b8be23332497e477cb0f","observation_id":"34a92adc-1de4-42fd-b941-9dd709e15138","resolution":{"observed_at":"2026-08-01T09:10:43.288317Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1708.02862","last_updated":"2017-08-09T14:59:30Z","snapshot_observed_at":"2026-08-14T20:42:20.095725Z","submitted_at":"2017-08-09T14:59:30Z","title":"WebVision Database: Visual Learning and Understanding from Web Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.02862","snapshot_observed_at":"2026-08-01T09:10:43.354131Z","title":"Webvision database: Visual learning and understanding from web data","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:43.354131Z"},"links":{"cited_paper":"/paper/1708.02862","citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:1f0ebe05e424139b863ab00ab2a4996d9bf36449c310d8c4b67bacff06277539","observation_id":"c8e932be-4c61-4cbd-99b7-511c0994df6e","resolution":{"observed_at":"2026-08-01T09:10:43.354131Z","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":"2026-08-01T09:10:43.484250Z","title":"Microsoft coco: Common objects in context, in: European Conference on Computer Vision, Springer","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:43.484250Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:f0711dfd0b006bd1e1013ca2d3602dad9976c9aadb49fcdc5ecf312c83159b8f","observation_id":"dacf5231-9f17-4e37-b12d-8f78d612d234","resolution":{"observed_at":"2026-08-01T09:10:43.484250Z","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":"2026-08-01T09:10:43.551439Z","title":"Joint multi-label learning and feature extraction for temporal link prediction","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:43.551439Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:76ad929056200486a6fd6cf976438e059fb7bef21964cad84a0dd8f160deb2cf","observation_id":"1e946248-b65e-45d7-8795-e772be5f396a","resolution":{"observed_at":"2026-08-01T09:10:43.551439Z","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":"2026-08-01T09:10:43.635458Z","title":"Exploringthelimitsofweakly supervised pretraining, in: Proceedings of the European conference on computer vision (ECCV), pp","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:43.635458Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:29534eeb655e7cbc43d90b0cf3d661f2bcd444c28b98283679a814c00d5a902d","observation_id":"0f0e8feb-9126-4c43-a15e-b154a9b2fec5","resolution":{"observed_at":"2026-08-01T09:10:43.635458Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.13237","last_updated":"2023-12-15T08:42:04Z","snapshot_observed_at":"2026-08-16T14:58:17.591468Z","submitted_at":"2023-09-23T02:40:28Z","title":"Spatial-Temporal Knowledge-Embedded Transformer for Video Scene Graph Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.13237","snapshot_observed_at":"2026-08-01T09:10:43.706374Z","title":"Spatial-temporal knowledge-embedded transformer for video scene graph generation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:43.706374Z"},"links":{"cited_paper":"/paper/2309.13237","citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:f62c137fc87046499b96626da219fc094b45e3557eae916ae510718c126d9360","observation_id":"874e70d5-f69a-4756-b592-2875542b30e7","resolution":{"observed_at":"2026-08-01T09:10:43.706374Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2204.03795","last_updated":"2023-01-09T15:28:41Z","snapshot_observed_at":"2026-08-16T17:08:25.275327Z","submitted_at":"2022-04-08T00:55:15Z","title":"Semantic Representation and Dependency Learning for Multi-Label Image Recognition","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.03795","snapshot_observed_at":"2026-08-01T09:10:43.798764Z","title":"Semanticrepresentationanddependencylearningformulti-labelimagerecognition","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:43.798764Z"},"links":{"cited_paper":"/paper/2204.03795","citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:7eca8a3f586d70be491944cc8b251928a50f2d3714beffae52ee0374c08e16b2","observation_id":"a3e6d427-d09e-4d15-8d24-3fef7e402867","resolution":{"observed_at":"2026-08-01T09:10:43.798764Z","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":"2026-08-01T09:10:43.879940Z","title":"Learning transferable visual models from natural language supervision, in: Meila, M., Zhang, T","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:43.879940Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:2ddf725abab5c4cba1a7e585dd390433a0fb1557bf5cf4765e0f4f31a5441363","observation_id":"340fd1e1-c539-4b8f-b421-04478b886a8b","resolution":{"observed_at":"2026-08-01T09:10:43.879940Z","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":"2026-08-01T09:10:43.944688Z","title":"Asymmetric loss for multi-label classification, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:43.944688Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:7eb36f68ccfd0fd89590b2453d35230c70b2df06bebc6de2fdb36aa14e4d872a","observation_id":"62d5ae41-3f92-4c7b-9b14-4a9ed8d8d815","resolution":{"observed_at":"2026-08-01T09:10:43.944688Z","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":"2026-08-01T09:10:43.995767Z","title":"Deep co-image-label hashing for multi-label image retrieval","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:43.995767Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:bb7bf173ae9169e262bd53f411b36a7086dbd3aee67910adb6e590852ac8c7bd","observation_id":"bd7a62b8-1e1b-4768-a37a-f464de96fd24","resolution":{"observed_at":"2026-08-01T09:10:43.995767Z","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":"2026-08-01T09:10:44.075423Z","title":"Meta-learning for multi-label few-shot classification, in: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), pp","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:44.075423Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:ebfacfebafb6ac190988f1a3ffdc5f3e0cc33e17c93ef718fde1069ed08b6230","observation_id":"90481b7e-f668-4d4c-ba4e-22ac8e552f1d","resolution":{"observed_at":"2026-08-01T09:10:44.075423Z","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":"2026-08-01T09:10:44.243551Z","title":"Very deep convolutional networks for large-scale image recognition, in: Bengio, Y., Le- Cun, Y","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:44.243551Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:f3a3e491de6e5731217f9c598991e32f5977d826a029bc5fadcab3ee5329c98a","observation_id":"1091d578-ec41-43b1-b722-2d1700c1fdcd","resolution":{"observed_at":"2026-08-01T09:10:44.243551Z","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":"2026-08-01T09:10:44.392317Z","title":"Webly supervised fine-grained recognition: Benchmark datasets and an approach, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:44.392317Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:8a54f82d07f7257cc774683aad582d5e1224be4f1235556cd49c78dd646f9ca3","observation_id":"445dda15-b6d2-4bb1-b7be-8646ad3b1d8d","resolution":{"observed_at":"2026-08-01T09:10:44.392317Z","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":"2026-08-01T09:10:44.550893Z","title":"Multi-labelout-of-distributiondetectionviaexploitingsparsityandco-occurrence of labels","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:44.550893Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:a9fe615d3be2184366ba1fd47f146af16040c2fd600cfe55cd0fbbb1202ad296","observation_id":"3faff087-6aac-48d8-b098-00c68d29caee","resolution":{"observed_at":"2026-08-01T09:10:44.550893Z","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":"2026-08-01T09:10:44.715385Z","title":"Hcp: A flexible cnn framework for multi-label image classification","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:44.715385Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:b7120fae7ad6abc4a7bc2a711d6ac266a5993a148321e1ace577d08850c187b8","observation_id":"b82c5c9a-be2a-4fcc-902b-64523feb5d5f","resolution":{"observed_at":"2026-08-01T09:10:44.715385Z","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":"2026-08-01T09:10:44.878835Z","title":"Adahgnn: Adaptive hypergraph neural networks for multi-label image classification, in: Proceedings of the 28th ACM International Conference on Multimedia (ACMMM), pp","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:44.878835Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:48887c189f8022d8490314554020ed36285a168b486966db4c60d8d98e9ddf54","observation_id":"81557247-9311-41b8-bafb-5c19380bef46","resolution":{"observed_at":"2026-08-01T09:10:44.878835Z","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":"2026-08-01T09:10:44.988181Z","title":"Multi-labelrecognitioninopendrivingscenariosbasedonbipartite-drivensuperimposeddynamicgraph","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:44.988181Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:36b07bd68c78f49d4889fd9b9fd32a58d03a5ebaeddf10a7affb5321f817cac8","observation_id":"0e11bd6b-a4f7-4502-94c6-1fdf2f54b61b","resolution":{"observed_at":"2026-08-01T09:10:44.988181Z","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":"2026-08-01T09:10:45.152458Z","title":"Attention-drivendynamicgraphconvolutionalnetworkformulti-labelimagerecognition,in: European Conference on Computer Vision, Springer","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:45.152458Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:0fa768b4d0132e7af6c264c78feb1efac5c074736c692e1bb25c719246bd9c9a","observation_id":"af60e561-6baa-4143-888e-25e08d516c59","resolution":{"observed_at":"2026-08-01T09:10:45.152458Z","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":"2026-08-01T09:10:45.316279Z","title":"Deep semantic ranking based hashing for multi-label image retrieval, in: Proceedings of the IEEE conference on computer vision and pattern recognition, pp","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:45.316279Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:fb87f2c5620071be6f59755641bba5c10da22823448e0e1136c4e3c6f0a0cd86","observation_id":"5aa14706-5893-441b-bfee-6bc2300687ce","resolution":{"observed_at":"2026-08-01T09:10:45.316279Z","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":"10.24963/ijcai.2024/617","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Towards robust multi-label learning against dirty label noise, in: Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, pp","venue":null,"work_id":"976d2054-7c34-4694-8738-14cd5d687e63","year":2024},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:45.482396Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:9ae1f3c9bdfa974c1f35d7873ea284c0fcb5b6905980ec9fb77cb2947728d96f","observation_id":"94419678-f7bf-4932-b825-6b24df41fc73","resolution":{"observed_at":"2026-08-01T09:13:28.313770Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-01T09:10:45.572292Z","title":"Residual attention: A simple but effective method for multi-label recognition, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:45.572292Z"},"links":{"citing_paper":"/paper/2607.20874"},"observation_digest":"sha256:8cdb060ee1ebd7e3acf318d16f035533bffbf5eba220f460c2c80b90314a762f","observation_id":"c98cd271-3dab-4c6e-a0f2-be0574353a70","resolution":{"observed_at":"2026-08-01T09:10:45.572292Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.20874","last_updated":"2026-07-23T02:54:01Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T23:36:16.642823Z","submitted_at":"2026-07-23T02:54:01Z","title":"Webly Supervised Multi-Label Recognition: Evaluation Benchmark and Dual-Branch Multi-Label Contrastive Learning"},"reference_resolution":{"displayed":44,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":42,"verified_exact":2,"verified_fuzzy":0},"total_outbound_references":44},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2607.20874."}