{"as_of":"2026-08-20T09:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:7d46d0fe16f38055a32190f7364ca6d92bedca53c8d3030035fa1ce2cb2a64a3","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":55,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":55,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":55,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T18:57:46.035481Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":64,"observed_at":"2026-08-05T02:28:24.338817Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-12T19:11:49.102427Z","title":"Contrastive representation distillation","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2411.10961","last_updated":"2024-11-17T04:50:44Z","snapshot_observed_at":"2026-08-19T20:40:37.839839Z","submitted_at":"2024-11-17T04:50:44Z","title":"Map-Free Trajectory Prediction with Map Distillation and Hierarchical Encoding","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T19:11:49.102427Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2411.10961"},"observation_digest":"sha256:536d21ce2564ea20a91530f79861d4883352c8ee56ec3dbbb7fdd63e99018cb1","observation_id":"986c71c7-237d-4715-b425-bee573ac2d19","resolution":{"observed_at":"2026-08-12T19:11:49.102427Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-12T11:06:36.279545Z","title":"Contrastive representation distillation","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2411.18674","last_updated":"2025-05-05T14:25:01Z","snapshot_observed_at":"2026-08-19T03:42:02.536774Z","submitted_at":"2024-11-27T18:50:15Z","title":"Active Data Curation Effectively Distills Large-Scale Multimodal Models","version":2},"reference_index":149,"source":"pdf_text","source_observed_at":"2026-08-12T11:06:36.279545Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2411.18674"},"observation_digest":"sha256:73016d8b16a338da035431cc01faad948609f76bd38b5c9fcd1ba894b18279e5","observation_id":"d3ca6ccc-cf0b-42f5-a51a-1e734d2b5e80","resolution":{"observed_at":"2026-08-12T11:06:36.279545Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-11T17:24:34.060342Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.08939","last_updated":"2024-12-17T06:30:00Z","snapshot_observed_at":"2026-08-20T07:39:36.948810Z","submitted_at":"2024-12-12T05:01:17Z","title":"Dynamic Contrastive Knowledge Distillation for Efficient Image Restoration","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-11T17:24:34.060342Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2412.08939"},"observation_digest":"sha256:5481d97b735517fb393146b49b6b307b7c322a06c27d44c58790c43357f598d7","observation_id":"aa2cdb0c-0689-4886-be67-a09a6fe9295d","resolution":{"observed_at":"2026-08-11T17:24:34.060342Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-11T17:11:13.073990Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.09388","last_updated":"2025-02-12T10:55:54Z","snapshot_observed_at":"2026-08-14T10:05:48.405500Z","submitted_at":"2024-12-12T15:56:20Z","title":"All You Need in Knowledge Distillation Is a Tailored Coordinate System","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-11T17:11:13.073990Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2412.09388"},"observation_digest":"sha256:9e380c73829a50545f1a63ee690ed7763b4582ccdb4fc73ceed8e169d6f944a2","observation_id":"4896b901-45bb-4d31-8200-89b0cc04240d","resolution":{"observed_at":"2026-08-11T17:11:13.073990Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-11T16:43:59.373084Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.09874","last_updated":"2024-12-13T05:40:20Z","snapshot_observed_at":"2026-08-17T23:30:09.770339Z","submitted_at":"2024-12-13T05:40:20Z","title":"Can Students Beyond The Teacher? Distilling Knowledge from Teacher's Bias","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-11T16:43:59.373084Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2412.09874"},"observation_digest":"sha256:fca767dfaef0a03b2ecd4222f42a1792e990863298818bbb7169a0b1b7aa2ccb","observation_id":"ba358f60-60e0-4056-9811-5d14c85eb750","resolution":{"observed_at":"2026-08-11T16:43:59.373084Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-11T15:12:28.202891Z","title":"Contrastive Representation Distillation , January 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.11276","last_updated":"2025-01-31T17:35:20Z","snapshot_observed_at":"2026-08-17T14:34:21.912298Z","submitted_at":"2024-12-15T18:48:14Z","title":"Wearable Accelerometer Foundation Models for Health via Knowledge Distillation","version":2},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-11T15:12:28.202891Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2412.11276"},"observation_digest":"sha256:0714fa855a1e9f9104db3bf235dc62951875ca29f5c56bcf231a6134cc41cd21","observation_id":"aaceec92-3b3e-4bf3-a77f-a9cfd4ebe8be","resolution":{"observed_at":"2026-08-11T15:12:28.202891Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-11T14:39:27.311891Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.11788","last_updated":"2024-12-16T14:00:30Z","snapshot_observed_at":"2026-08-17T23:26:42.028552Z","submitted_at":"2024-12-16T14:00:30Z","title":"Neural Collapse Inspired Knowledge Distillation","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-11T14:39:27.311891Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2412.11788"},"observation_digest":"sha256:b017952610257a68f26ee61e7e1be253c7db29a41588d9a4e2852a8022c1fd8a","observation_id":"8d8dc1e4-8a32-4b5b-83d0-eaa9c4d2c7ea","resolution":{"observed_at":"2026-08-11T14:39:27.311891Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-10T23:02:14.434087Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.00152","last_updated":"2025-07-18T03:12:59Z","snapshot_observed_at":"2026-08-17T23:27:38.859699Z","submitted_at":"2024-12-30T21:54:33Z","title":"Temporal reasoning for timeline summarisation in social media","version":3},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-10T23:02:14.434087Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2501.00152"},"observation_digest":"sha256:2c1bb3a27671355b5d83ca582874db056e5c2f59e8ec3d40ea86dca34fb947f5","observation_id":"be7e17d0-1e79-49fe-b735-b73e81ba2c45","resolution":{"observed_at":"2026-08-10T23:02:14.434087Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-10T20:55:18.304402Z","title":"Contrastive representation distillation,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2501.07040","last_updated":"2025-01-13T03:43:21Z","snapshot_observed_at":"2026-08-14T13:34:12.908458Z","submitted_at":"2025-01-13T03:43:21Z","title":"Rethinking Knowledge in Distillation: An In-context Sample Retrieval Perspective","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T20:55:18.304402Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2501.07040"},"observation_digest":"sha256:ecf87de99d212f0b62945c95709584db24bd953b56f4a13c03bc491972b6d46f","observation_id":"2c0aa911-4bd8-47f6-ba88-c7f6e5bd88e8","resolution":{"observed_at":"2026-08-10T20:55:18.304402Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-10T20:04:16.376886Z","title":"arXiv preprint arXiv:1910.10699 (2019)","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.09485","last_updated":"2025-01-16T11:44:29Z","snapshot_observed_at":"2026-08-14T13:39:29.400401Z","submitted_at":"2025-01-16T11:44:29Z","title":"The Devil is in the Details: Simple Remedies for Image-to-LiDAR Representation Learning","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-10T20:04:16.376886Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2501.09485"},"observation_digest":"sha256:a36b7c9a92f22dd6b3c093808d32d2a32abbb1c1f7d33e6c83ee37908bc038cb","observation_id":"714ebc1e-b6bb-4223-a203-5bb405818e1c","resolution":{"observed_at":"2026-08-10T20:04:16.376886Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-08T16:30:52.898454Z","title":"Contrastive representation distillation","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2502.06189","last_updated":"2025-02-10T06:41:20Z","snapshot_observed_at":"2026-08-17T23:26:36.164618Z","submitted_at":"2025-02-10T06:41:20Z","title":"Multi-Level Decoupled Relational Distillation for Heterogeneous Architectures","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-08T16:30:52.898454Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2502.06189"},"observation_digest":"sha256:725437004ce226b3fcd22e63520b64d2e7b822100b1252b66865a633afaeced0","observation_id":"c42a3be8-0b94-4590-b6ac-fd1d75b444a0","resolution":{"observed_at":"2026-08-08T16:30:52.898454Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2502.07189","last_updated":"2026-04-29T23:02:03Z","snapshot_observed_at":"2026-08-15T03:17:02.292673Z","submitted_at":"2025-02-11T02:31:04Z","title":"Exploring Vision Neural Network Pruning via Screening Methodology","version":2},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-05-23T03:33:15.015365Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2502.07189"},"observation_digest":"sha256:c0db5649b8099f48dd8b5336dc8aebf2e08486948182931ffc1d22c5e6667893","observation_id":"4ee651c4-02b2-4c3c-81e5-59c11e9bd07b","resolution":{"observed_at":"2026-05-23T03:35:21.015178Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-07T15:27:41.869574Z","title":"Contrastive representation distillation,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2505.15133","last_updated":"2025-05-21T05:38:57Z","snapshot_observed_at":"2026-08-16T03:56:40.187549Z","submitted_at":"2025-05-21T05:38:57Z","title":"DeepKD: A Deeply Decoupled and Denoised Knowledge Distillation Trainer","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T15:27:41.869574Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2505.15133"},"observation_digest":"sha256:e404de3e0e538e3c0505fa99cd1a0226917fcbddb9c8460f34839e8879d2c564","observation_id":"a3818fe6-56fc-416c-b67f-1a76cca1fc33","resolution":{"observed_at":"2026-08-07T15:27:41.869574Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-07T12:45:22.668737Z","title":"Contrastive representation distillation.arXiv preprint arXiv:1910.10699, 2019","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2505.23933","last_updated":"2025-05-29T18:29:40Z","snapshot_observed_at":"2026-08-15T01:15:30.012089Z","submitted_at":"2025-05-29T18:29:40Z","title":"BIRD: Behavior Induction via Representation-structure Distillation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T12:45:22.668737Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2505.23933"},"observation_digest":"sha256:5ffa91dad5fe6024b2302be595090bdc86de827e8192173cf04ba5ee952a11c3","observation_id":"44a44160-8c68-472e-b887-4b695b087a44","resolution":{"observed_at":"2026-08-07T12:45:22.668737Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-07T12:31:51.944258Z","title":"arXiv preprint arXiv:1910.10699 (2019)","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.24310","last_updated":"2025-05-30T07:49:01Z","snapshot_observed_at":"2026-08-13T17:29:16.578848Z","submitted_at":"2025-05-30T07:49:01Z","title":"Progressive Class-level Distillation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T12:31:51.944258Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2505.24310"},"observation_digest":"sha256:546c84cb674cd3a3f45605c228d0c712f0379fbff4a7e9b7b996e61d1abbc6e7","observation_id":"31b5d6b0-a173-4f03-8d4e-f0eef01b9056","resolution":{"observed_at":"2026-08-07T12:31:51.944258Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-07T05:47:32.374283Z","title":"Contrastive representation distilla- tion,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2506.07055","last_updated":"2025-06-08T09:30:48Z","snapshot_observed_at":"2026-08-17T16:58:41.604211Z","submitted_at":"2025-06-08T09:30:48Z","title":"A Layered Self-Supervised Knowledge Distillation Framework for Efficient Multimodal Learning on the Edge","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T05:47:32.374283Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2506.07055"},"observation_digest":"sha256:75ce0b8845874c283abdd0be6695291a61ff6430b1964cbbbc8c71d0300a91a0","observation_id":"5e4647c8-ff2a-4816-9662-03e014e1e093","resolution":{"observed_at":"2026-08-07T05:47:32.374283Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-06T23:57:26.268689Z","title":"arXiv preprint arXiv:1910.10699 (2019)","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.15681","last_updated":"2026-06-25T14:33:27Z","snapshot_observed_at":"2026-08-08T08:54:57.204006Z","submitted_at":"2025-06-18T17:59:49Z","title":"GenRecal: Generation after Recalibration from Large to Small Vision-Language Models","version":4},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-06T23:57:26.268689Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2506.15681"},"observation_digest":"sha256:456b11f148e7d143a9b624e3e8ce902d466a707886e13ff6dd8a36500fb56c78","observation_id":"4f17c8da-2cf8-4af3-9432-f030440f1e44","resolution":{"observed_at":"2026-08-06T23:57:26.268689Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-15T18:57:46.035481Z","title":"Visual prompt tuning,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.18244","last_updated":"2025-06-23T02:22:53Z","snapshot_observed_at":"2026-08-17T19:34:45.595324Z","submitted_at":"2025-06-23T02:22:53Z","title":"Dual-Forward Path Teacher Knowledge Distillation: Bridging the Capacity Gap Between Teacher and Student","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T18:57:46.035481Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2506.18244"},"observation_digest":"sha256:2ec1c9357e072c76d71b51c757dfc00c136cba0a91ab596155cdd143f5fd1b18","observation_id":"b99e6e36-5b47-4484-a4fc-ab7a90a6ece4","resolution":{"observed_at":"2026-08-15T18:57:46.035481Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-15T18:52:31.084211Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.18378","last_updated":"2025-06-23T08:11:24Z","snapshot_observed_at":"2026-08-19T14:53:59.399502Z","submitted_at":"2025-06-23T08:11:24Z","title":"Taming Vision-Language Models for Medical Image Analysis: A Comprehensive Review","version":1},"reference_index":265,"source":"pdf_text","source_observed_at":"2026-08-15T18:52:31.084211Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2506.18378"},"observation_digest":"sha256:0199ba695637f4ae4669714611df26aef40c6cad33b87e841a395e2f2c8947d7","observation_id":"8683758d-aab7-4b86-8ad0-b3fe61bcc3fc","resolution":{"observed_at":"2026-08-15T18:52:31.084211Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-15T18:44:38.575544Z","title":"Contrastive representation distillation","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2506.18999","last_updated":"2025-06-23T18:01:19Z","snapshot_observed_at":"2026-08-19T19:39:10.972681Z","submitted_at":"2025-06-23T18:01:19Z","title":"Diffusion Transformer-to-Mamba Distillation for High-Resolution Image Generation","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-15T18:44:38.575544Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2506.18999"},"observation_digest":"sha256:7382755b0626d21cf9a59d745325639614937c43d90e23cc14859be4d1a0b6fc","observation_id":"5ca8e7e6-b5f4-475e-a456-7a03c604ff49","resolution":{"observed_at":"2026-08-15T18:44:38.575544Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-06T22:41:12.454416Z","title":"Contrastive representation distillation","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2506.21080","last_updated":"2025-06-26T08:09:16Z","snapshot_observed_at":"2026-08-07T17:47:39.726590Z","submitted_at":"2025-06-26T08:09:16Z","title":"EgoAdapt: Adaptive Multisensory Distillation and Policy Learning for Efficient Egocentric Perception","version":1},"reference_index":102,"source":"pdf_text","source_observed_at":"2026-08-06T22:41:12.454416Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2506.21080"},"observation_digest":"sha256:e1a83219d183436d266b4e02325a440ec9270a90c228bdf35668613338e5f5b3","observation_id":"90bf95fb-427f-4a6b-be19-ab6bb273c047","resolution":{"observed_at":"2026-08-06T22:41:12.454416Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-15T16:57:13.629345Z","title":"Contrastive Representation Distillation, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.19498","last_updated":"2025-08-27T00:56:11Z","snapshot_observed_at":"2026-08-17T23:26:37.386808Z","submitted_at":"2025-08-27T00:56:11Z","title":"UNIFORM: Unifying Knowledge from Large-scale and Diverse Pre-trained Models","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-15T16:57:13.629345Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2508.19498"},"observation_digest":"sha256:70b4542f0233e93984fe42479672f4d513ad5ea00c299cebb4816ab63d3069b0","observation_id":"6b244d18-e9fe-450e-b0ca-348faeb6b7f9","resolution":{"observed_at":"2026-08-15T16:57:13.629345Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T15:19:05.929161Z","title":null,"venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2508.20224","last_updated":"2025-08-27T19:04:28Z","snapshot_observed_at":"2026-08-10T18:58:45.920031Z","submitted_at":"2025-08-27T19:04:28Z","title":"The Role of Teacher Calibration in Knowledge Distillation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T15:19:05.929161Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2508.20224"},"observation_digest":"sha256:8cd0c4542cbd19b964be5d183d09ae53cd37b124a7dd004a26b43733744520a5","observation_id":"1716a3ff-d1d1-46f2-ae60-0659a4e0aa1d","resolution":{"observed_at":"2026-08-05T15:19:05.929161Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T15:17:52.397343Z","title":"Contrastive Representation Distillation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.20232","last_updated":"2025-08-27T19:23:54Z","snapshot_observed_at":"2026-08-18T00:58:39.728530Z","submitted_at":"2025-08-27T19:23:54Z","title":"ATMS-KD: Adaptive Temperature and Mixed Sample Knowledge Distillation for a Lightweight Residual CNN in Agricultural Embedded Systems","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T15:17:52.397343Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2508.20232"},"observation_digest":"sha256:1b2fd5e85544832d79c76cb297294c247f1aab1824a2c1ac4622a6229add06b1","observation_id":"a8896591-6ac8-461a-bedb-8e177c14026d","resolution":{"observed_at":"2026-08-05T15:17:52.397343Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-15T16:32:08.601956Z","title":"Contrastive representation distillation","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2509.04442","last_updated":"2025-09-04T17:59:06Z","snapshot_observed_at":"2026-08-18T16:53:16.130640Z","submitted_at":"2025-09-04T17:59:06Z","title":"Delta Activations: A Representation for Finetuned Large Language Models","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-15T16:32:08.601956Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2509.04442"},"observation_digest":"sha256:165fc2f753a033fa8469683455606b8f8543394eb2f66accfc3f94c9ff78012c","observation_id":"4ea137ba-0a3e-4836-aa5f-d5d17b28602e","resolution":{"observed_at":"2026-08-15T16:32:08.601956Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-04T16:45:45.046335Z","title":"Contrastive representation distilla- tion,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2509.11924","last_updated":"2025-09-16T02:04:27Z","snapshot_observed_at":"2026-08-13T17:13:19.483809Z","submitted_at":"2025-09-15T13:38:35Z","title":"Enriched text-guided variational multimodal knowledge distillation network (VMD) for automated diagnosis of plaque vulnerability in 3D carotid artery MRI","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-04T16:45:45.046335Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2509.11924"},"observation_digest":"sha256:87dc8d8119a5c80a927624e5e3a7c7afcdcaa77f5c2992f646477a98e8067562","observation_id":"7b2cec24-7de1-4b2d-a99c-aa27c7e12316","resolution":{"observed_at":"2026-08-04T16:45:45.046335Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2604.03841","last_updated":"2026-04-04T19:45:25Z","snapshot_observed_at":"2026-08-15T16:40:32.796261Z","submitted_at":"2026-04-04T19:45:25Z","title":"Training a Student Expert via Semi-Supervised Foundation Model Distillation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-13T16:50:57.376622Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2604.03841"},"observation_digest":"sha256:1133f2f16a0fb5d23a0f0b2e3cd76f614219d5dc8213147c56fb8e75094b051d","observation_id":"bf78c76c-bf86-4998-be8c-925e6baf85ff","resolution":{"observed_at":"2026-05-13T16:53:00.067163Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2604.04988","last_updated":"2026-04-05T06:13:47Z","snapshot_observed_at":"2026-08-18T20:22:40.524753Z","submitted_at":"2026-04-05T06:13:47Z","title":"Prune-Quantize-Distill: An Ordered Pipeline for Efficient Neural Network Compression","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-13T17:03:48.689643Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2604.04988"},"observation_digest":"sha256:c1ec59a3d1f1943c5f6c3662a53e37bd2c1afc1abf8afb7ec53d483b847d56f9","observation_id":"badc46b1-eabe-4d0a-93f7-8d9595bef815","resolution":{"observed_at":"2026-05-13T17:08:01.011429Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-07-13T10:56:59.609600Z","title":"Contrastive representation distilla- tion,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2604.04995","last_updated":"2026-04-05T17:45:16Z","snapshot_observed_at":"2026-08-16T10:27:32.564547Z","submitted_at":"2026-04-05T17:45:16Z","title":"Streaming Chain","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-13T10:56:59.609600Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2604.04995"},"observation_digest":"sha256:18849314eb5a7e34c8652ef67393a2991e7ae0397fff6600a66312c2dc911c8e","observation_id":"f1490c89-7365-4207-a889-2a3e8aa0d2a6","resolution":{"observed_at":"2026-07-13T10:56:59.609600Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2605.00329","last_updated":"2026-05-01T01:13:50Z","snapshot_observed_at":"2026-08-16T23:48:33.860447Z","submitted_at":"2026-05-01T01:13:50Z","title":"Fast Text-to-Audio Generation with One-Step Sampling via Energy-Scoring and Auxiliary Contextual Representation Distillation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-09T19:17:09.247932Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2605.00329"},"observation_digest":"sha256:34ad21de620abcd24b9e47e1e28896a4df1e93826071204773d1d0226c284ab6","observation_id":"1c96f253-6e4a-4ca4-881f-7f45e0b53fcd","resolution":{"observed_at":"2026-05-11T15:46:45.999848Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2605.04447","last_updated":"2026-05-06T03:22:39Z","snapshot_observed_at":"2026-08-10T22:02:18.040858Z","submitted_at":"2026-05-06T03:22:39Z","title":"Deep Reprogramming Distillation for Medical Foundation Models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-08T18:30:36.882621Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2605.04447"},"observation_digest":"sha256:dc89d66e52a9a82c28f714821518ea9708e0d515bff7b70259491c1723720983","observation_id":"c33c0259-3866-47e5-b8fd-3d5da748fe4d","resolution":{"observed_at":"2026-05-09T06:25:39.286127Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2605.08685","last_updated":"2026-05-09T04:49:56Z","snapshot_observed_at":"2026-08-02T14:44:33.851541Z","submitted_at":"2026-05-09T04:49:56Z","title":"Event Fields: Learning Latent Event Structure for Waveform Foundation Models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-12T01:16:48.039349Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2605.08685"},"observation_digest":"sha256:6e4a30d92658aa6688b0e7a661ead2ef87fda56186864f01ea00795bb5776bf2","observation_id":"9064476e-ffd5-482d-b1d8-8a592787b14e","resolution":{"observed_at":"2026-05-12T01:21:20.110921Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2605.09765","last_updated":"2026-05-10T21:25:41Z","snapshot_observed_at":"2026-08-14T10:24:40.518725Z","submitted_at":"2026-05-10T21:25:41Z","title":"WISTERIA: Learning Clinical Representations from Noisy Supervision via Multi-View Consistency in Electronic Health Records","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-12T02:17:54.498339Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2605.09765"},"observation_digest":"sha256:996e71dad8d9430bd178afa7d9dde3f05200db38eb1c3918a0618d57bc233c60","observation_id":"39e38bc2-e8be-4652-827d-e18dff14b399","resolution":{"observed_at":"2026-05-12T02:21:15.832115Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2605.13143","last_updated":"2026-05-15T03:25:35Z","snapshot_observed_at":"2026-08-13T18:50:34.604945Z","submitted_at":"2026-05-13T08:10:05Z","title":"On the Generalization of Knowledge Distillation: An Information-Theoretic View","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-19T18:03:07.434428Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2605.13143"},"observation_digest":"sha256:a4cddf5e84fd682c5b93c81edfa6c90cbecbecb1023ea9d8f593bbd4445015fa","observation_id":"acf46ce1-a369-418b-ab42-7a9754d3dae1","resolution":{"observed_at":"2026-05-19T18:03:10.055087Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2605.17765","last_updated":"2026-05-18T02:32:50Z","snapshot_observed_at":"2026-08-16T20:09:43.913471Z","submitted_at":"2026-05-18T02:32:50Z","title":"AURORA: Contextual Orthogonalization for Geometric Representation Learning in Healthcare Foundation Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-20T12:06:33.875494Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2605.17765"},"observation_digest":"sha256:846b57b1d958f51b314c3bca2ed443cbdabdb3c0bbe75f440b020fa54eeb787f","observation_id":"026ab7b8-f292-419b-9f42-96b8dd870e6c","resolution":{"observed_at":"2026-05-20T12:08:15.287830Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2605.27409","last_updated":"2026-05-12T11:15:36Z","snapshot_observed_at":"2026-08-12T14:23:49.753635Z","submitted_at":"2026-05-12T11:15:36Z","title":"STARS: Spike Tail-Aware Relational Synthesis for ANN-to-SNN Data-Free Knowledge Distillation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-30T22:28:05.038412Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2605.27409"},"observation_digest":"sha256:89a6649c49532eb5992b85040912658e20f0f39f846f5c92272f48c7fbc863a7","observation_id":"7056d1ac-ecfd-47bf-8763-fce544ddf03a","resolution":{"observed_at":"2026-07-01T14:05:45.732567Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2605.30380","last_updated":"2026-06-01T03:28:35Z","snapshot_observed_at":"2026-08-03T01:38:20.537239Z","submitted_at":"2026-05-27T21:57:28Z","title":"Lightweight SAR Ship Detection via Contrastive Distillation","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-06-29T12:43:14.091975Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2605.30380"},"observation_digest":"sha256:953ae8a9bdfef41a837960b90a22d503468cecf71aab4644ebab5cedd6841340","observation_id":"1a3060c9-900f-4694-850c-e24ef0c7d1f4","resolution":{"observed_at":"2026-06-29T12:43:25.329612Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2606.00771","last_updated":"2026-05-30T15:22:59Z","snapshot_observed_at":"2026-08-15T16:26:22.035897Z","submitted_at":"2026-05-30T15:22:59Z","title":"Logit Distillation on Manifolds: Mapping by Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-28T19:35:41.959457Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2606.00771"},"observation_digest":"sha256:1d9c76aa38a67599d27f45b7e93794bd9a18ccdcf190401207b0553440a29645","observation_id":"156fee49-82a2-4439-892b-a63d490876f2","resolution":{"observed_at":"2026-06-28T19:42:35.813304Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2606.03234","last_updated":"2026-06-02T06:51:15Z","snapshot_observed_at":"2026-08-15T10:07:50.406997Z","submitted_at":"2026-06-02T06:51:15Z","title":"Right Makes Might: Aligning Verified Hidden States Empowers RL Reasoning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-28T11:13:21.565082Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2606.03234"},"observation_digest":"sha256:9692d6ed28a1b51c691de7fd3ab5bf6a7cb0b5b3ff9d259d73b32c20065931c4","observation_id":"17239b58-90e8-4605-80a4-fe3b2a9c386e","resolution":{"observed_at":"2026-07-02T02:06:27.234120Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2606.09881","last_updated":"2026-06-03T05:44:29Z","snapshot_observed_at":"2026-08-12T12:37:31.669797Z","submitted_at":"2026-06-03T05:44:29Z","title":"Toward Calibrated, Fair, and accurate Deepfake Detection","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-06-28T07:05:18.026601Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2606.09881"},"observation_digest":"sha256:0678f06340134becaad669257aca1bb4a549c5188e4d6402f4abb82f3ddcd4ea","observation_id":"98c4298d-3c69-4926-88c6-4a63ee07e2c5","resolution":{"observed_at":"2026-06-28T07:11:45.251048Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2606.12171","last_updated":"2026-06-10T14:59:26Z","snapshot_observed_at":"2026-08-17T03:39:14.539309Z","submitted_at":"2026-06-10T14:59:26Z","title":"Beyond Dark Knowledge: Mixup-Based Distillation for Reliable Predictions","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-06-27T09:52:30.187137Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2606.12171"},"observation_digest":"sha256:e05b2616511825601d41a1c83545ea69c566080f4a3d59579a621e00409cb829","observation_id":"c6705d21-e206-4309-84ab-9da3ddc33a21","resolution":{"observed_at":"2026-07-03T10:48:02.010780Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2606.19195","last_updated":"2026-06-17T15:35:38Z","snapshot_observed_at":"2026-08-14T06:52:50.303487Z","submitted_at":"2026-06-17T15:35:38Z","title":"Moebius: 0.2B Lightweight Image Inpainting Framework with 10B-Level Performance","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-06-26T21:03:43.962738Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2606.19195"},"observation_digest":"sha256:29b50e788a76b7211d6e42192ee31bf7210e3db9e141d614a2f96a6d97c1bb82","observation_id":"40a995ee-0cbb-41a4-8c75-a7a8bca62fa4","resolution":{"observed_at":"2026-07-04T00:39:17.107833Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2606.21982","last_updated":"2026-06-20T10:33:14Z","snapshot_observed_at":"2026-08-04T14:46:13.489000Z","submitted_at":"2026-06-20T10:33:14Z","title":"CoDMD: Copula-aware Distribution Matching Distillation for Fast Video Generation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-06-26T12:52:05.465272Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2606.21982"},"observation_digest":"sha256:3816abaa950f56362dc035f7e788f484e5777c299d9174ecb453d5ac48745934","observation_id":"7e8b780d-7e53-4d70-95b1-f0244eb9329c","resolution":{"observed_at":"2026-07-04T07:49:38.683464Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2606.27527","last_updated":"2026-06-25T20:19:50Z","snapshot_observed_at":"2026-07-07T00:01:44.678954Z","submitted_at":"2026-06-25T20:19:50Z","title":"Large Language Model Teaches Visual Students: Cross-Modality Transfer of Fine-Grained Conceptual Knowledge","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-06-29T02:07:27.600563Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2606.27527"},"observation_digest":"sha256:3aa01b5e7869e8c3342408ac7f5ffb5b1ce00491e559bcd9c0af7f0d0a7adb59","observation_id":"27da4438-69fe-4457-b3c1-5c322a62e502","resolution":{"observed_at":"2026-07-01T18:15:59.164118Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2606.27646","last_updated":"2026-07-07T22:52:29Z","snapshot_observed_at":"2026-08-10T11:00:02.322324Z","submitted_at":"2026-06-26T01:54:22Z","title":"VLM-Aware Meta-Optic Front-End Design for Frozen Vision-Language Models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-06-29T00:28:32.756341Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2606.27646"},"observation_digest":"sha256:44616e44ce6e6f42ff74fe16cce0b9d2f8d4bc39ec87dd9d365c361b36896d52","observation_id":"f34281c7-d162-46eb-839c-26503034a6a1","resolution":{"observed_at":"2026-07-01T19:06:03.546781Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-07-12T11:40:55.995208Z","title":"arXiv preprint arXiv:1910.10699 (2019)","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2606.27646","last_updated":"2026-07-07T22:52:29Z","snapshot_observed_at":"2026-08-10T11:00:02.322324Z","submitted_at":"2026-06-26T01:54:22Z","title":"VLM-Aware Meta-Optic Front-End Design for Frozen Vision-Language Models","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-12T11:40:55.995208Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2606.27646"},"observation_digest":"sha256:e7cc28fe1ce4141f72511bb493952b491f2c5b610eb46b68d8051d7130c6cc69","observation_id":"8feb27c8-ab48-4828-8d2f-1467259c3e35","resolution":{"observed_at":"2026-07-12T11:40:55.995208Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2607.01272","last_updated":"2026-06-30T20:12:27Z","snapshot_observed_at":"2026-07-07T00:06:49.412663Z","submitted_at":"2026-06-30T20:12:27Z","title":"Benchmarking Federated Learning and Knowledge Distillation for Point Cloud Classification","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-03T21:58:30.339002Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2607.01272"},"observation_digest":"sha256:97dce8be4b6f0d46e68a8407201d779580d9520500308f904077ae707af369cb","observation_id":"e4e37f03-2648-4209-bc92-035cd019ff5d","resolution":{"observed_at":"2026-07-03T21:58:58.239074Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2607.01906","last_updated":"2026-07-02T09:05:38Z","snapshot_observed_at":"2026-08-14T21:58:37.053353Z","submitted_at":"2026-07-02T09:05:38Z","title":"SFKD: Spatial--Frequency Joint-Aware Heterogeneous Knowledge Distillation via Multi-Level Wavelet Spectral Interaction","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-03T16:02:36.425762Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2607.01906"},"observation_digest":"sha256:76d7a41a4216d2a1153a73e93eb70911347e09a935d1abd5f29e971bcc79b14b","observation_id":"16b65b5f-e781-4a42-a805-2b65e49fea66","resolution":{"observed_at":"2026-07-03T16:08:36.820290Z","resolver_source":"arxiv_id","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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-07-11T16:38:56.238848Z","title":"arXiv preprint arXiv:1910.10699 (2019)","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2607.04599","last_updated":"2026-07-06T02:01:59Z","snapshot_observed_at":"2026-08-06T04:54:53.317593Z","submitted_at":"2026-07-06T02:01:59Z","title":"Displacement Preserving Relational Distillation for Robust Medical Segmentation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-11T16:38:56.238848Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2607.04599"},"observation_digest":"sha256:32c6257235b41397ce1d817944519d2bde8496cfb8bfb8896a00324c8437ace6","observation_id":"f77638e1-dce9-4503-aca1-1708ed1e1f89","resolution":{"observed_at":"2026-07-11T16:38:56.238848Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":"1910.10699","doi":"10.48550/arxiv.1910.10699","metadata_source":"pith","pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":"cs.LG","work_id":"e0fc4057-ac4f-4c73-b04b-cc944c7701ad","year":2019},"citing_paper":{"arxiv_id":"2607.05175","last_updated":"2026-07-06T14:57:26Z","snapshot_observed_at":"2026-08-20T03:08:06.335162Z","submitted_at":"2026-07-06T14:57:26Z","title":"Platonic Projection Structures: Operator-Induced Observability in Representation Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-08T01:11:35.146386Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2607.05175"},"observation_digest":"sha256:5e6f490b5b4c2ff0ea493b493834f61b8fc0f0f57f20c0a8ce269ff552ff7592","observation_id":"6d16a2ff-9800-443f-919f-58d5ded7f124","resolution":{"observed_at":"2026-07-08T01:14:27.363801Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"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":"2026-07-11T19:50:21.864262+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-11T19:50:21.864262+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-07-14T16:31:09.661787Z","title":"URLhttps://arxiv.org/abs/1910.10699","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2607.09749","last_updated":"2026-07-03T22:00:54Z","snapshot_observed_at":"2026-08-15T15:56:02.579064Z","submitted_at":"2026-07-03T22:00:54Z","title":"MorphologyFM: A Foundation Model for Morphology-Aware Representation Learning from ECG and Pulse Oximetry Waveforms","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-07-14T16:31:09.661787Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2607.09749"},"observation_digest":"sha256:e9c7c403e0ec6311075c728bfe1cfda62adc358aec65e58c6316ed4742c87345","observation_id":"3aec11fb-e28b-43b1-8999-7ddcd4f81843","resolution":{"observed_at":"2026-07-14T16:31:09.661787Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-07-14T04:47:31.919478Z","title":"Contrastive representation distilla- tion,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2607.11557","last_updated":"2026-07-22T08:11:20Z","snapshot_observed_at":"2026-08-19T18:01:03.694968Z","submitted_at":"2026-07-13T13:39:35Z","title":"Single-Teacher View Augmentation: Enhancing Knowledge Distillation with Student-Guided Perturbations","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-14T04:47:31.919478Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2607.11557"},"observation_digest":"sha256:e8da81cbc3c9db9540ddb2a7ea19016e24ff6d0e8b94d96d4f6bb43476875e10","observation_id":"be4d8ba5-a4a1-4bf9-b59c-0e94ff1ed94a","resolution":{"observed_at":"2026-07-14T04:47:31.919478Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-02T06:55:32.584684Z","title":"Contrastive representation distilla- tion,","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2607.11557","last_updated":"2026-07-22T08:11:20Z","snapshot_observed_at":"2026-08-19T18:01:03.694968Z","submitted_at":"2026-07-13T13:39:35Z","title":"Single-Teacher View Augmentation: Enhancing Knowledge Distillation with Student-Guided Perturbations","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-02T06:55:32.584684Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2607.11557"},"observation_digest":"sha256:28ade5681e74acd0ed04c679bdd2819f28958c4aeae91c4e57505d7efd922b71","observation_id":"9afb5f0c-9693-4fdd-8615-31690b634dc2","resolution":{"observed_at":"2026-08-02T06:55:32.584684Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-01T14:42:37.327617Z","title":"Contrastive representation distillation.arXiv preprint arXiv:1910.10699, 2019","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2607.18693","last_updated":"2026-07-21T04:23:14Z","snapshot_observed_at":"2026-08-13T20:36:53.272027Z","submitted_at":"2026-07-21T04:23:14Z","title":"Rationale-Guided Knowledge Distillation for Cross-Lingual Stance Detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-01T14:42:37.327617Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2607.18693"},"observation_digest":"sha256:3516703581c5a7784644ed4e7633a8be84e26569bd0b45fd25fd05ebca69efd2","observation_id":"34288d6b-45d1-4238-8a89-93cdde01dc1e","resolution":{"observed_at":"2026-08-01T14:42:37.327617Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.10699","snapshot_observed_at":"2026-08-15T15:27:42.381895Z","title":"arXiv preprint arXiv:1910.10699 (2019)","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.27357","last_updated":"2026-07-29T18:10:50Z","snapshot_observed_at":"2026-08-20T06:50:19.520876Z","submitted_at":"2026-07-29T18:10:50Z","title":"Shared Semantic Codebook Distillation for Unpaired Cross-Modal Medical Classification","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-15T15:27:42.381895Z"},"links":{"cited_paper":"/paper/1910.10699","citing_paper":"/paper/2607.27357"},"observation_digest":"sha256:6f59b1abf68a92ce672c80db06d0d7b11d81c0f7924c4ac6f1ba560c9585d1e3","observation_id":"5556d388-db29-41f4-b12f-f1dc0eccc305","resolution":{"observed_at":"2026-08-15T15:27:42.381895Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1910.10699/citation-record","integrity":"/paper/1910.10699/integrity","json":"/paper/1910.10699/citation-record.json","paper":"/paper/1910.10699"},"outbound":[],"paper":{"arxiv_id":"1910.10699","last_updated":"2022-01-24T19:12:34Z","latest_version":3,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-10T18:58:30.893017Z","submitted_at":"2019-10-23T17:59:18Z","title":"Contrastive Representation Distillation"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-20T06:33:59.587034+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 0 of 0 outbound references and 55 inbound Pith citation observations for arXiv:1910.10699."}