{"as_of":"2026-08-20T12:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b0690e721923da9d55f69c634191b34d49ba384e4f45007127c0713befcd24c7","coverage":[{"denominator":48,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":48,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T16:37:05.962265Z","state":"measured"},{"denominator":49,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":49,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:50:32.424797Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-06T20:50:32.775614Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"cited_work":{"arxiv_id":"2502.06153","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.06153","snapshot_observed_at":"2026-08-06T20:50:32.775614Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","venue":"cs.LG","work_id":"7ee6f918-e8ff-4d76-8416-0f648b324d41","year":2025},"citing_paper":{"arxiv_id":"2507.01841","last_updated":"2025-07-02T15:56:40Z","snapshot_observed_at":"2026-08-18T09:19:15.048963Z","submitted_at":"2025-07-02T15:56:40Z","title":"Automatic Rank Determination for Low-Rank Adaptation via Submodular Function Maximization","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T20:50:32.424797Z"},"links":{"cited_paper":"/paper/2502.06153","citing_paper":"/paper/2507.01841"},"observation_digest":"sha256:f4c21a16f4babcb530c2bc40cd8539ef4ab580e162fd51e95a23d6b97a17caf4","observation_id":"2fa23cd2-d967-41cd-919d-c03bc4818702","resolution":{"observed_at":"2026-08-06T20:50:32.783182Z","resolver_source":"local_arxiv","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"}}],"links":{"evidence":"/evidence","html":"/paper/2502.06153/citation-record","integrity":"/paper/2502.06153/integrity","json":"/paper/2502.06153/citation-record.json","paper":"/paper/2502.06153"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.795239Z","title":"KAN: Kolmogorov–Arnold networks,","venue":null,"work_id":"bf1e4451-ad71-4a3a-9cd9-f5226b1af9d6","year":null},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.776645Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:244112d82eb074aa304da63ede36a29122f508923e1236014308c02d341c392e","observation_id":"8a385476-1a5c-4cb5-afec-5b02e6b4aefc","resolution":{"observed_at":"2026-08-08T16:37:06.799292Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":{"arxiv_id":"2406.02918","last_updated":"2024-08-22T11:55:56Z","snapshot_observed_at":"2026-08-18T09:28:27.526915Z","submitted_at":"2024-06-05T04:13:03Z","title":"U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.02918","snapshot_observed_at":"2026-08-08T16:37:05.784322Z","title":"U-KAN makes strong backbone for medical image segmentation and generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.784322Z"},"links":{"cited_paper":"/paper/2406.02918","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:05aff2d0c7525be51d4277c62322a9e57c4399eeeef4039a1dbc23eb31e38da7","observation_id":"4089551f-6d93-4b2d-bafc-b46bb8589b90","resolution":{"observed_at":"2026-08-08T16:37:05.784322Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.777674Z","title":"Kolmogorov-Arnold networks for online reinforcement learning,","venue":null,"work_id":"0352918f-238d-4991-b185-41428067d7f6","year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.789531Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:37b3f9cdd38e2bf36d3427b19190f189430a5bb2a97a3eee2220e2a3359a34ea","observation_id":"8d425d3a-d64e-4c2e-993b-d5335301ece3","resolution":{"observed_at":"2026-08-08T16:37:06.781322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.766032Z","title":"A physics-informed deep learning framework for solving forward and inverse problems based on Kolmogorov–Arnold Networks,","venue":null,"work_id":"2e76afce-3238-4657-ba9f-fb18f942a1a7","year":2025},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.793428Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:c99ac676d7a49cd8ac454bf2746a9c5397c422ade33f55b92a3e7602c525129f","observation_id":"6bde0278-401a-4b34-bc0d-0aabe3da23a1","resolution":{"observed_at":"2026-08-08T16:37:06.769999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":{"arxiv_id":"2411.06286","last_updated":"2024-11-09T21:10:23Z","snapshot_observed_at":"2026-08-16T13:01:29.976680Z","submitted_at":"2024-11-09T21:10:23Z","title":"SPIKANs: Separable Physics-Informed Kolmogorov-Arnold Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.06286","snapshot_observed_at":"2026-08-08T16:37:05.797193Z","title":"SPIKANs: Separa- ble physics-informed Kolmogorov-Arnold networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.797193Z"},"links":{"cited_paper":"/paper/2411.06286","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:7c4ac915e784ce58c97550870ed109e516ff991c44276a3a5355b285a417bba7","observation_id":"55e55334-1c3e-42b1-94cc-4a1ee9da650d","resolution":{"observed_at":"2026-08-08T16:37:05.797193Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.755301Z","title":"A comprehensive and fair comparison between MLP and KAN repre- sentations for differential equations and operator networks,","venue":null,"work_id":"fed376eb-97a9-4436-b9fc-147c632b082e","year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.801308Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:6418548b4b5ca5574c0f5b363c9605b523035277d71b49e4331da2e615db3767","observation_id":"16418f4a-9dc4-4b09-aa24-f11acbaad907","resolution":{"observed_at":"2026-08-08T16:37:06.759177Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":{"arxiv_id":"2407.11075","last_updated":"2025-09-14T09:09:20Z","snapshot_observed_at":"2026-08-18T11:17:44.545093Z","submitted_at":"2024-07-13T04:29:36Z","title":"Kolmogorov-Arnold Networks: A Critical Assessment of Claims, Performance, and Practical Viability","version":8},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.11075","snapshot_observed_at":"2026-08-08T16:37:05.804843Z","title":"A comprehensive survey on Kolmogorov Arnold networks (KAN),","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.804843Z"},"links":{"cited_paper":"/paper/2407.11075","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:7e4a6598aac078ac32b711c474e1474b6972b5a2a87ef29fce4d48775785af05","observation_id":"3783d5de-c633-415e-bbe8-a20e08afc6d7","resolution":{"observed_at":"2026-08-08T16:37:05.804843Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.06078","last_updated":"2024-11-09T05:54:17Z","snapshot_observed_at":"2026-08-16T13:01:35.457145Z","submitted_at":"2024-11-09T05:54:17Z","title":"A Survey on Kolmogorov-Arnold Network","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.06078","snapshot_observed_at":"2026-08-08T16:37:05.809131Z","title":"A sur- vey on Kolmogorov-Arnold network,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.809131Z"},"links":{"cited_paper":"/paper/2411.06078","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:375fffc7615a951822aa1bd19e28fd88d0de7596942a4b3d5637519c89391a9b","observation_id":"41cd99f5-da04-4565-9165-ff6264cf6065","resolution":{"observed_at":"2026-08-08T16:37:05.809131Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.744167Z","title":"HyperKAN: Kolmogorov– Arnold networks make hyperspectral image classifiers smarter,","venue":null,"work_id":"cddfda6e-7770-43a8-b80b-c9ea6f4e4476","year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.812801Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:b01d87c612a445168a544023bb2a4c8ed2f4cd38f1a0929c01c594167bc46f1c","observation_id":"71a59664-66f6-4fe9-b094-64564a184c18","resolution":{"observed_at":"2026-08-08T16:37:06.748320Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":{"arxiv_id":"2411.00278","last_updated":"2026-05-28T03:45:43Z","snapshot_observed_at":"2026-08-16T13:03:56.426255Z","submitted_at":"2024-11-01T00:24:15Z","title":"KAN-AD: Time Series Anomaly Detection with Kolmogorov-Arnold Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.00278","snapshot_observed_at":"2026-08-08T16:37:05.816426Z","title":"KAN-AD: Time series anomaly detection with Kolmogorov- Arnold networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.816426Z"},"links":{"cited_paper":"/paper/2411.00278","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:f34a9738d2f7974b35abd064b7b3b03a9a8a66b8e2a86373e3df3f89f08877c5","observation_id":"ef694d4b-3929-433d-b7b0-ab82cebed4b6","resolution":{"observed_at":"2026-08-08T16:37:05.816426Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01803","last_updated":"2025-02-06T19:49:32Z","snapshot_observed_at":"2026-08-18T11:14:40.609439Z","submitted_at":"2024-10-02T17:57:38Z","title":"On the expressiveness and spectral bias of KANs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01803","snapshot_observed_at":"2026-08-08T16:37:05.820278Z","title":"On the expressiveness and spectral bias of KANs,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.820278Z"},"links":{"cited_paper":"/paper/2410.01803","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:2a8958301b015c5dd6f7c525c383063e42702564d346e9d6c50cd868b8ce42ba","observation_id":"9e803d1d-6c82-4e8b-be57-9f84c7b63a00","resolution":{"observed_at":"2026-08-08T16:37:05.820278Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.09323","last_updated":"2025-01-14T02:56:00Z","snapshot_observed_at":"2026-08-16T13:18:37.163506Z","submitted_at":"2024-09-14T05:53:33Z","title":"Implicit Neural Representations with Fourier Kolmogorov-Arnold Networks","version":3},"cited_work":{"arxiv_id":"2409.09323","doi":null,"metadata_source":"pith","pith_arxiv_id":"2409.09323","snapshot_observed_at":"2026-08-08T16:37:06.385211Z","title":"Implicit Neural Representations with Fourier Kolmogorov-Arnold Networks","venue":"cs.CV","work_id":"21672e97-af84-46d4-a4ff-a413b96e6e25","year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.825311Z"},"links":{"cited_paper":"/paper/2409.09323","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:c2663a93c6ca7c2633eacb5933556b7a448631670c5bb7050fbdc97aa993f668","observation_id":"29337978-e2f9-40ca-98f0-1939ccd5daf1","resolution":{"observed_at":"2026-08-08T16:37:06.391435Z","resolver_source":"local_arxiv","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":"2026-08-08T16:37:05.829251Z","title":"Finite basis Kolmogorov-Arnold networks: domain decomposi- tion for data-driven and physics-informed problems,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.829251Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:373b80085af2a5caf07ede00c63f17b378a954545e661c181e9f9d010c5b8caf","observation_id":"5ba49a8f-3f5a-4fce-9802-f6e0bc871686","resolution":{"observed_at":"2026-08-08T16:37:05.829251Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.733465Z","title":"Adaptive training of grid-dependent physics-informed Kolmogorov-Arnold networks,","venue":null,"work_id":"7da1d2da-6a8b-431c-add8-2595a07a4d9b","year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.832670Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:9bac0a15230ee7d578fafd1f6cd05f75d29ac23233760907def23f1c281d7395","observation_id":"b5dec433-822f-4ebd-a95a-cf998f274348","resolution":{"observed_at":"2026-08-08T16:37:06.737136Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.722715Z","title":"Kanqas: Kolmogorov-Arnold network for quantum architecture search,","venue":null,"work_id":"5a9a9242-ce02-400b-a7ce-2ffbfbb056af","year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.836296Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:e2e08d5e0a756ec3febfce00ce14d6a00182143111a80e2b82a9d03120b04580","observation_id":"37be1303-ef61-4f44-91c6-02534f39183e","resolution":{"observed_at":"2026-08-08T16:37:06.726555Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":{"arxiv_id":"2406.13155","last_updated":"2025-03-31T12:55:11Z","snapshot_observed_at":"2026-08-18T11:38:40.573177Z","submitted_at":"2024-06-19T02:09:44Z","title":"Convolutional Kolmogorov-Arnold Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.13155","snapshot_observed_at":"2026-08-08T16:37:05.839831Z","title":"Convolu- tional Kolmogorov-Arnold networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.839831Z"},"links":{"cited_paper":"/paper/2406.13155","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:c3583004f0a8d40c06d6b58def5c43898fd1f2490408c0a2f2c0d4b5aac4b5bf","observation_id":"b11dcedd-7654-4e39-80d6-95195c278698","resolution":{"observed_at":"2026-08-08T16:37:05.839831Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.01092","last_updated":"2024-07-01T08:49:33Z","snapshot_observed_at":"2026-08-18T11:17:17.073938Z","submitted_at":"2024-07-01T08:49:33Z","title":"Kolmogorov-Arnold Convolutions: Design Principles and Empirical Studies","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.01092","snapshot_observed_at":"2026-08-08T16:37:05.843531Z","title":"Kolmogorov-Arnold convolutions: Design principles and empirical studies,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.843531Z"},"links":{"cited_paper":"/paper/2407.01092","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:05b1419c969192a881edd461b7a72e685c53c244749859d47db0d635a313eb37","observation_id":"e7bf4585-40a8-43b9-9a55-3273aba4c3dd","resolution":{"observed_at":"2026-08-08T16:37:05.843531Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.07200","last_updated":"2024-06-14T15:46:11Z","snapshot_observed_at":"2026-08-16T13:53:26.708635Z","submitted_at":"2024-05-12T07:55:43Z","title":"Chebyshev Polynomial-Based Kolmogorov-Arnold Networks: An Efficient Architecture for Nonlinear Function Approximation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.07200","snapshot_observed_at":"2026-08-08T16:37:05.847754Z","title":"Chebyshev polynomial-based Kolmogorov- Arnold networks: An efficient architecture for nonlinear function approx- imation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.847754Z"},"links":{"cited_paper":"/paper/2405.07200","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:4382f01c2806e2b4ae288743dc319a056cbfdf83f184dc3d30aa7012820e366e","observation_id":"5b294b80-b252-48fe-a2bd-dd66af121199","resolution":{"observed_at":"2026-08-08T16:37:05.847754Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.710895Z","title":"Legendre-KAN : High accuracy KA network based on Legendre polynomials,","venue":null,"work_id":"0e04d7ce-749e-4bdd-971b-149c9455ac9a","year":2025},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.852217Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:9efb70002538e925686a6092e83e18b6d111c597766612ed73206a063683a955","observation_id":"f553ab80-35eb-4562-bf5f-a3cacd7bd463","resolution":{"observed_at":"2026-08-08T16:37:06.715145Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":{"arxiv_id":"2406.01034","last_updated":"2025-08-14T10:41:49Z","snapshot_observed_at":"2026-08-18T09:20:47.886928Z","submitted_at":"2024-06-03T06:36:04Z","title":"Enhancing Graph Collaborative Filtering with FourierKAN Feature Transformation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.01034","snapshot_observed_at":"2026-08-08T16:37:05.856268Z","title":"FourierKAN-GCF: Fourier Kolmogorov-Arnold network–an effective and efficient feature transformation for graph collaborative filtering,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.856268Z"},"links":{"cited_paper":"/paper/2406.01034","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:0b3a4cb4069514e4319e2b108ddc2797dc7ba4515d222177b516de5293f172ab","observation_id":"fcd5b1e7-58d0-43cb-a458-bb0d0cf469f7","resolution":{"observed_at":"2026-08-08T16:37:05.856268Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.12832","last_updated":"2024-05-27T15:12:55Z","snapshot_observed_at":"2026-08-18T09:10:54.733191Z","submitted_at":"2024-05-21T14:36:16Z","title":"Wav-KAN: Wavelet Kolmogorov-Arnold Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.12832","snapshot_observed_at":"2026-08-08T16:37:05.860077Z","title":"Wav-KAN: Wavelet Kolmogorov-Arnold networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.860077Z"},"links":{"cited_paper":"/paper/2405.12832","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:2285f87726d8ef658d7cc2777710ed2ba422243fde286e2ac278d9d5c86ab9ec","observation_id":"17084041-c487-4cb7-9250-2126334c1906","resolution":{"observed_at":"2026-08-08T16:37:05.860077Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.02583","last_updated":"2024-10-14T01:58:57Z","snapshot_observed_at":"2026-08-16T13:47:34.569733Z","submitted_at":"2024-05-30T20:40:16Z","title":"Exploring the Potential of Polynomial Basis Functions in Kolmogorov-Arnold Networks: A Comparative Study of Different Groups of Polynomials","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.02583","snapshot_observed_at":"2026-08-08T16:37:05.863959Z","title":"Exploring the potential of polynomial basis functions in Kolmogorov-Arnold networks: A comparative study of different groups of polynomials,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.863959Z"},"links":{"cited_paper":"/paper/2406.02583","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:607adbb7cf18d311dc65629255d8a2c39c8bb3310e8942257d7413b3b89a3ee1","observation_id":"d5572f8f-9bb8-4e86-9d33-9e92db0120f0","resolution":{"observed_at":"2026-08-08T16:37:05.863959Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.14495","last_updated":"2024-06-20T16:59:38Z","snapshot_observed_at":"2026-08-16T13:41:01.923825Z","submitted_at":"2024-06-20T16:59:38Z","title":"rKAN: Rational Kolmogorov-Arnold Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.14495","snapshot_observed_at":"2026-08-08T16:37:05.868575Z","title":"rKAN: Rational kolmogorov-arnold networks,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.868575Z"},"links":{"cited_paper":"/paper/2406.14495","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:23c65bc699162c681d5cbec1b0c9fb5822d0da9a0be17f77b09ab6ee5e69a200","observation_id":"528f187f-2b97-44f3-a0d1-97c381d19151","resolution":{"observed_at":"2026-08-08T16:37:05.868575Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.698762Z","title":"fKAN: Fractional Kolmogorov-Arnold networks with trainable Jacobi basis functions,","venue":null,"work_id":"3e03f705-f129-4920-a12a-2dac17d8f4c3","year":2025},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.872281Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:b08232a85e545144e366d2c88119a6a4bb70a313c71afe0434de8f23d7ea0c16","observation_id":"af0dbe1d-6e97-418e-8401-8860b0ab0a2d","resolution":{"observed_at":"2026-08-08T16:37:06.702948Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.686872Z","title":"Hyperspectral image denoising based on global and nonlocal low-rank factorizations,","venue":null,"work_id":"a0db0f30-ce4f-4290-b955-fafd933adf70","year":2021},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.875909Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:b2706be5821f590c79140c17d56a4d8979738d620ad92b3da0277a311e672bf1","observation_id":"c2efd326-c8a8-4267-abad-c7edd72682f7","resolution":{"observed_at":"2026-08-08T16:37:06.690884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.674650Z","title":"Nonlocal low-rank regularized tensor decomposition for hyperspectral image denoising,","venue":null,"work_id":"8a4b5e8f-1d17-48db-992f-c35b0a9a8912","year":2019},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.880107Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:6fba79f5366a101cd133baf0bd6649fb30b128393ff38662d4279d67240b0e23","observation_id":"85d4efc0-05d9-409b-9efe-465dbbbfce7a","resolution":{"observed_at":"2026-08-08T16:37:06.678718Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.663529Z","title":"Smooth PARAFAC decomposi- tion for tensor completion,","venue":null,"work_id":"a2244514-4694-4a50-8096-40e8a508f2ca","year":2016},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.884531Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:bb2f29bba174690386395692a428b979ab60f7299ba609fd37a9aced21b235f6","observation_id":"d26900c9-e758-4eed-8fb7-6933e23f4d0e","resolution":{"observed_at":"2026-08-08T16:37:06.667477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.652346Z","title":"Bayesian temporal factorization for multidimen- sional time series prediction,","venue":null,"work_id":"e62a2873-a02b-4141-bc8e-a2fdcb1b742e","year":2021},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.888229Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:3ac7d338a3721b29d72c71a08a121282ae5dea9336ed8448912f0bdaf2149569","observation_id":"c4ed57ea-9b26-46a4-8882-0128515a7b85","resolution":{"observed_at":"2026-08-08T16:37:06.656256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.640664Z","title":"A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking,","venue":null,"work_id":"6291dafe-9288-472b-a0a8-3ebeb0c0c986","year":2002},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.891701Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:ee96b11dc503461cecc66fa159f0b499314c88eeeeaf11aa94a872356103e936","observation_id":"79cf86b2-8fd6-47cc-b1c1-cec6e29ce219","resolution":{"observed_at":"2026-08-08T16:37:06.644527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-08T16:37:05.895359Z","title":"Tensor decomposition for signal processing and machine learning,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.895359Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:c8ef9beb9896d1cd04611521782c6cad34d7a51a27f38dff72d409e26de7ed63","observation_id":"1aee7e62-055d-40b7-9e43-bd004488d989","resolution":{"observed_at":"2026-08-08T16:37:05.895359Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.621669Z","title":"Tensor decompositions for identifying directed graph topologies and tracking dynamic networks,","venue":null,"work_id":"58987caa-5aec-4966-9d95-6589d4190e9c","year":2017},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.899863Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:4e6af10be8f471af1a008cb35b86f9d1b6920c149ed534a9c5ce15153c444125","observation_id":"a3d6d888-15a7-4c92-8a76-050da8586b68","resolution":{"observed_at":"2026-08-08T16:37:06.625856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.610059Z","title":"Implications of factor analysis of three-way matrices for measurement of change,","venue":null,"work_id":"9beb4b20-a3b8-4602-94e6-172e7c824956","year":1963},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.903528Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:192353eb018982474ef37a0e8c9543751158bbe40f42bab2f79da855c330dc3b","observation_id":"07ba3ced-fbab-4d53-912d-dc2527dfeea2","resolution":{"observed_at":"2026-08-08T16:37:06.614075Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.598426Z","title":"Towards a standardized notation and terminology in multi- way analysis,","venue":null,"work_id":"02bd41d5-5dc7-4ff8-8d0d-74bd685c4569","year":2000},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.907356Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:5a69e02fc59c41cb83c405b3ab350c3a0131662178909c818ab4057c5cb2932f","observation_id":"efd49dc3-6a11-401c-abbc-284b6774ee60","resolution":{"observed_at":"2026-08-08T16:37:06.602404Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.586602Z","title":"Robust tensor completion using transformed tensor singular value decomposition,","venue":null,"work_id":"87bf98fe-9d0b-4615-a335-c3b4ab169017","year":2020},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.911950Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:1cf278d45427acb6aeea4510b397a94d12cde6f443f2bbe42c7381223a0f2470","observation_id":"b4db60a3-f531-45ad-a9d7-f30a58dd9a6f","resolution":{"observed_at":"2026-08-08T16:37:06.590561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-08T16:37:05.915788Z","title":"Factorization strategies for third-order tensors,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.915788Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:fb5227758b35f791e50fa622d508ccde9d6cbcb22a48d6cd9849600e32e251e9","observation_id":"6900d86e-df76-43c8-b42c-532d07d35e0d","resolution":{"observed_at":"2026-08-08T16:37:05.915788Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.568236Z","title":"CANDELINC: A general approach to multidimensional analysis of many-way arrays with linear constraints on parameters,","venue":null,"work_id":"8004411d-432b-4364-84a7-79298d735cd5","year":1980},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.919441Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:6e7eba3da4bed48d76ed43ee9334dc2f2c8a79515871220858124b991404b05f","observation_id":"3215ff6e-4eaf-40f8-a35c-5b6ffd1e98f2","resolution":{"observed_at":"2026-08-08T16:37:06.572142Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.555442Z","title":"PARAFAC2: Mathematical and technical notes,","venue":null,"work_id":"4a6db5ec-8b10-435a-9285-59ce93ca6b7c","year":1972},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.923143Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:e6a47c7265d8c7b80a0662f8aa785caf4389c5db1ec2149c21881093163bd73d","observation_id":"113d1bdd-21cc-43ef-b932-78a79f5700a1","resolution":{"observed_at":"2026-08-08T16:37:06.559790Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.543144Z","title":"A multilinear singular value decomposition,","venue":null,"work_id":"fc2f2a87-c87b-4734-991e-dbabb2e0f6f5","year":2000},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.926832Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:73aadea78af6e4dab46cbe833f1c9e20ff950e65e53cdff942d94cdde7d80d60","observation_id":"79794913-5609-424c-b6e0-10f44f977cbe","resolution":{"observed_at":"2026-08-08T16:37:06.547321Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.531484Z","title":"Multitask learning,","venue":null,"work_id":"11b0e613-7c62-49c2-a360-0d0867766c99","year":1997},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.930369Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:b22576bd391aac9b2a9179bcb83b63fe68cbf905e4923664525f2e8a7991cc19","observation_id":"be270acd-2f0c-4cdf-9e4d-f8071ca74269","resolution":{"observed_at":"2026-08-08T16:37:06.535313Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.519511Z","title":"A survey on multi-task learning,","venue":null,"work_id":"79248319-8e48-42cc-8c67-a6fefed444ba","year":2021},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.933776Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:2b393b02b0f4b39d848101166fc1e6fb718e856b49affec918944dd174df881b","observation_id":"92ebbd98-13bc-4ac6-a5c1-40b9822ea0aa","resolution":{"observed_at":"2026-08-08T16:37:06.524004Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.508258Z","title":"Domain adaptation with multiple sources,","venue":null,"work_id":"4f2193fc-8628-4191-a932-6dc50ce6ae80","year":2008},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.938244Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:8bd1eabfb07b21d4d784d463080b1ef8cf384509ad89ce6e01d4f351ceaf55bf","observation_id":"637c8093-b2b3-4569-9573-884daeccea9a","resolution":{"observed_at":"2026-08-08T16:37:06.511955Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.496061Z","title":"Frustratingly easy domain adaptation,","venue":null,"work_id":"b1e46007-bcc9-41f6-a86f-8b86b6a3d278","year":2007},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.942865Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:539f0f68618cad68a405bb519e7d8c650bc9ca59781f6f5c74794abf45ee6a0e","observation_id":"8b8c89d2-f869-47cf-8719-5d9ada185a11","resolution":{"observed_at":"2026-08-08T16:37:06.500000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2026-08-08T16:37:05.946719Z","title":"LoRA: Low-rank adaptation of large language models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.946719Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:cb13fcdc99bed71ea8e9179eb623fb3c8b65f0bf8a1ed36cb0b2a2684a79fa49","observation_id":"69935727-bf83-4c24-bf44-a80f1c19f63a","resolution":{"observed_at":"2026-08-08T16:37:05.946719Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T16:37:06.476264Z","title":"LoRA+: Efficient low rank adaptation of large models,","venue":null,"work_id":"9b70c2ea-53d4-47d4-b6dd-3768c319ccfc","year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.950439Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:8f459385e1ac7dc5801f2c3d2cd4ac92456d7e209b2da4491c679c6087d8d0d4","observation_id":"064b949d-e561-41a9-a2ac-60dd2977b75e","resolution":{"observed_at":"2026-08-08T16:37:06.481133Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":{"arxiv_id":"2012.13255","last_updated":"2020-12-22T07:42:30Z","snapshot_observed_at":"2026-08-18T15:17:24.628404Z","submitted_at":"2020-12-22T07:42:30Z","title":"Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-Tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.13255","snapshot_observed_at":"2026-08-08T16:37:05.954080Z","title":"Intrinsic dimensionality explains the effectiveness of language model fine-tuning,","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.954080Z"},"links":{"cited_paper":"/paper/2012.13255","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:0e1bc184e93d0d21281fd0c60cfef56649706ecd9c32a14733cae6210ee11628","observation_id":"6d527b2f-bf43-41e5-81b6-596e8173d85a","resolution":{"observed_at":"2026-08-08T16:37:05.954080Z","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":"2026-08-08T16:37:05.958548Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.958548Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:1347327af725a8367d4955041765a1f0a531f11b45e4543028fa1a72750141d4","observation_id":"485a4149-3d27-4e72-93d4-412b8f21533e","resolution":{"observed_at":"2026-08-08T16:37:05.958548Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.16674","last_updated":"2024-08-17T15:20:31Z","snapshot_observed_at":"2026-08-18T11:15:01.687093Z","submitted_at":"2024-07-23T17:43:35Z","title":"KAN or MLP: A Fairer Comparison","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.16674","snapshot_observed_at":"2026-08-08T16:37:05.962265Z","title":"KAN or MLP: A fairer comparison,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.962265Z"},"links":{"cited_paper":"/paper/2407.16674","citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:67103c8d85e8d7faf1b270629efcaf98df239046dd93fb072cd1efb67c9b82d3","observation_id":"d63ee3ec-4128-4175-92be-5e6518d94d06","resolution":{"observed_at":"2026-08-08T16:37:05.962265Z","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":"2026-08-08T16:37:05.780754Z","title":"Available: https://openreview.net/forum?id=Ozo7qJ5vZi","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-08T16:37:05.780754Z"},"links":{"citing_paper":"/paper/2502.06153"},"observation_digest":"sha256:f5e25cf404d0745dbe59f7dffd0ab57159f71b093ec40ec119f52bdffd196c91","observation_id":"04729571-5f5b-498a-a49f-a73530083c6e","resolution":{"observed_at":"2026-08-08T16:37:05.780754Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.06153","last_updated":"2025-02-14T01:43:07Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T13:41:37.083063Z","submitted_at":"2025-02-10T04:57:07Z","title":"Low Tensor-Rank Adaptation of Kolmogorov--Arnold Networks"},"reference_resolution":{"displayed":48,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":21,"verified_exact":1,"verified_fuzzy":26},"total_outbound_references":48},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-20T06:33:59.587034+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 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2502.06153."}