{"as_of":"2026-08-10T23:15:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:d586a8dfc8b864c326647ec3e9059c4d07fb14c9a3aebaff5976d7a85657e4e1","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":31,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":31,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":31,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":31,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T20:42:25.255477Z","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":"2026-07-09T17:36:25.406188Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2304.07193","last_updated":"2024-02-02T10:24:09Z","snapshot_observed_at":"2026-08-09T18:02:17.307812Z","submitted_at":"2023-04-14T15:12:19Z","title":"DINOv2: Learning Robust Visual Features without Supervision","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-09T04:17:19.878360Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2304.07193"},"observation_digest":"sha256:000a27e130e410484cf16dd9d19c6ea60749679f9dd4cd9f3c44020d6850301e","observation_id":"57ca71f7-d270-4429-9d0d-72c6731cf7dd","resolution":{"observed_at":"2026-05-09T04:17:20.443603Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2311.16867","last_updated":"2023-11-29T19:45:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-11-28T15:12:47Z","title":"The Falcon Series of Open Language Models","version":2},"reference_index":196,"source":"arxiv_source","source_observed_at":"2026-05-16T09:46:09.701440Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2311.16867"},"observation_digest":"sha256:307a2ccfdd1999be16ad7e98f693f7900ca4f5b7dcc41222abbae6f28a2260af","observation_id":"a08b87ba-946b-436b-8725-814045f60a52","resolution":{"observed_at":"2026-05-16T09:46:09.852219Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-10T20:42:25.255477Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.07737","last_updated":"2025-01-13T23:00:40Z","snapshot_observed_at":"2026-08-10T20:34:24.285365Z","submitted_at":"2025-01-13T23:00:40Z","title":"Multi-megabase scale genome interpretation with genetic language models","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-10T20:42:25.255477Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2501.07737"},"observation_digest":"sha256:36801d2557116b3d0746d1c60424782b390442de92bb51689203984de7c5b239","observation_id":"d8c1c68b-d318-4dc0-86c2-21519eedcbae","resolution":{"observed_at":"2026-08-10T20:42:25.255477Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-09T22:05:02.523732Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.18914","last_updated":"2025-01-31T06:32:46Z","snapshot_observed_at":"2026-08-10T09:04:20.044564Z","submitted_at":"2025-01-31T06:32:46Z","title":"Scaling Laws for Differentially Private Language Models","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-09T22:05:02.523732Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2501.18914"},"observation_digest":"sha256:df92eed2833515bcbc5ab64ec7143c3d8de486dfb6d58ced9832e27cd213183e","observation_id":"ca211374-f08d-44f9-80fb-7c41187d1ccf","resolution":{"observed_at":"2026-08-09T22:05:02.523732Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-08T16:15:07.150424Z","title":"Symbolic discovery of optimization algorithms","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.06268","last_updated":"2025-03-28T15:49:41Z","snapshot_observed_at":"2026-08-09T07:29:38.826457Z","submitted_at":"2025-02-10T09:07:04Z","title":"Spectral-factorized Positive-definite Curvature Learning for NN Training","version":3},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-08T16:15:07.150424Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2502.06268"},"observation_digest":"sha256:558968e66b8d1eeff1e1c721ca76db37bfbcf96ada64d7d098a574a29436dc1b","observation_id":"7615c643-16ed-474f-ad7f-04698c8c0a9e","resolution":{"observed_at":"2026-08-08T16:15:07.150424Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-07T15:09:11.308932Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.16363","last_updated":"2025-05-22T08:16:48Z","snapshot_observed_at":"2026-08-07T15:00:34.424850Z","submitted_at":"2025-05-22T08:16:48Z","title":"AdamS: Momentum Itself Can Be A Normalizer for LLM Pretraining and Post-training","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-07T15:09:11.308932Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2505.16363"},"observation_digest":"sha256:3fea9e8679223d69478ffc3201c31fa989d367fb84a5a4e1022780722be68821","observation_id":"60ae8075-1183-4903-ab8c-9dde68c32c9b","resolution":{"observed_at":"2026-08-07T15:09:11.308932Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-06T23:27:09.709503Z","title":"Symbolic discovery of optimization algorithms,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.18297","last_updated":"2025-06-23T05:30:09Z","snapshot_observed_at":"2026-08-06T23:20:35.362032Z","submitted_at":"2025-06-23T05:30:09Z","title":"Comparative Analysis of Lion and AdamW Optimizers for Cross-Encoder Reranking with MiniLM, GTE, and ModernBERT","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T23:27:09.709503Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2506.18297"},"observation_digest":"sha256:e074163028b4e8a29a092ffd8c0c1e12babe46ba27ef925ffc1f90f070975efa","observation_id":"a7918ac2-3f3b-4dc0-ac4f-00962e7aedd4","resolution":{"observed_at":"2026-08-06T23:27:09.709503Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-06T19:25:24.809707Z","title":"Symbolic discovery of optimization algo- rithms.arXiv preprint arXiv:2302.06675, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.05966","last_updated":"2025-07-08T13:19:26Z","snapshot_observed_at":"2026-08-10T01:26:34.269871Z","submitted_at":"2025-07-08T13:19:26Z","title":"Simple Convergence Proof of Adam From a Sign-like Descent Perspective","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T19:25:24.809707Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2507.05966"},"observation_digest":"sha256:d081622cf51f14b67f5d5a5af7801a5fb3c8dd9737421275986c517d9f67b0c6","observation_id":"559654b5-1189-44e8-8fa5-21b20f5338ab","resolution":{"observed_at":"2026-08-06T19:25:24.809707Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-06T19:10:16.490853Z","title":"Symbolic discovery of opti- mization algorithms,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.06464","last_updated":"2025-07-09T00:47:37Z","snapshot_observed_at":"2026-08-07T07:16:30.434582Z","submitted_at":"2025-07-09T00:47:37Z","title":"SoftSignSGD(S3): An Enhanced Optimizer for Practical DNN Training and Loss Spikes Minimization Beyond Adam","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T19:10:16.490853Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2507.06464"},"observation_digest":"sha256:5267e331149ed822077d3048fb4e6e1517babac28fe84dd9158eab7768a55e6c","observation_id":"95fdae10-305a-4e29-92b0-50fbe1e9c141","resolution":{"observed_at":"2026-08-06T19:10:16.490853Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-06T14:48:45.939586Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.17668","last_updated":"2025-09-10T12:25:27Z","snapshot_observed_at":"2026-08-08T15:32:47.481175Z","submitted_at":"2025-07-23T16:31:38Z","title":"How Should We Meta-Learn Reinforcement Learning Algorithms?","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T14:48:45.939586Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2507.17668"},"observation_digest":"sha256:94e567ebb427ebc0ee5acb65656262135e84a62fe762a40069f3f7fae52c4d21","observation_id":"2049f298-757a-4752-a563-7d78d809c499","resolution":{"observed_at":"2026-08-06T14:48:45.939586Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2509.15816","last_updated":"2026-05-10T06:58:46Z","snapshot_observed_at":"2026-07-06T22:30:17.163909Z","submitted_at":"2025-09-19T09:43:37Z","title":"On the Convergence of Muon and Beyond","version":5},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-05-18T15:56:30.602824Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2509.15816"},"observation_digest":"sha256:605f789bf3efb2a619eeb04fe14385540b7e7843e271b2b553bfdbe3a2cbe796","observation_id":"67cd5361-5c72-4d97-b27e-35d706dd1b44","resolution":{"observed_at":"2026-05-18T15:56:34.063247Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-03T17:56:43.676830Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.07540","last_updated":"2026-07-23T03:37:31Z","snapshot_observed_at":"2026-08-09T02:55:11.479898Z","submitted_at":"2025-12-08T13:21:44Z","title":"Minimum Bayes Risk Decoding for Error Span Detection in Reference-Free Automatic Machine Translation Evaluation","version":4},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-03T17:56:43.676830Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2512.07540"},"observation_digest":"sha256:4621aa17d09a5c613f980c412bf8049bec14c7618da3da5842c491d26fd8c0a7","observation_id":"1e792baa-82b0-4293-91ff-89e058da97bb","resolution":{"observed_at":"2026-08-03T17:56:43.676830Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2601.10791","last_updated":"2026-05-04T15:47:57Z","snapshot_observed_at":"2026-07-06T22:41:53.823272Z","submitted_at":"2026-01-15T19:00:04Z","title":"OmniMol: Transferring Particle Physics Knowledge to Molecular Dynamics with Point-Edge Transformers","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-16T13:18:02.842399Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2601.10791"},"observation_digest":"sha256:7a4daf3205a33e7f39b5cd959d6035f6263706ea81f1d8e2ceb3051e09b9c029","observation_id":"49f1e76a-24fe-467f-9e0d-55b87865ff27","resolution":{"observed_at":"2026-05-16T13:20:58.046822Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-02T22:25:58.349439Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2602.16918","last_updated":"2026-07-13T23:32:16Z","snapshot_observed_at":"2026-08-09T21:43:53.346884Z","submitted_at":"2026-02-18T22:22:44Z","title":"Xray-Visual Models: Scaling Vision models on Industry Scale Data","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-02T22:25:58.349439Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2602.16918"},"observation_digest":"sha256:4b9ea5d3da44ff9de379728b34276baaa2d606baa32fb9707eeef2173adc560b","observation_id":"4b508cec-537d-41dd-8a86-794fba215770","resolution":{"observed_at":"2026-08-02T22:25:58.349439Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-03T02:35:37.747095Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2603.08802","last_updated":"2026-07-31T17:08:50Z","snapshot_observed_at":"2026-08-10T02:12:39.266925Z","submitted_at":"2026-03-09T18:03:44Z","title":"Explicit or Implicit? Encoding Physics at the Precision Frontier","version":3},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-03T02:35:37.747095Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2603.08802"},"observation_digest":"sha256:0351deef2c2225d431c63ce5e6c251ae33f4019e409dcf81e447a874eee004b8","observation_id":"b5568fbb-3cfe-4575-9548-88baac1a8b88","resolution":{"observed_at":"2026-08-03T02:35:37.747095Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2604.06458","last_updated":"2026-04-07T20:57:33Z","snapshot_observed_at":"2026-08-01T03:49:10.809718Z","submitted_at":"2026-04-07T20:57:33Z","title":"Diffusion-Based Point-Cloud Generation of Heavy-Ion Events","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-10T18:35:48.056139Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2604.06458"},"observation_digest":"sha256:ea49bb1204edee878c90d07c62376e84f1491bc30d91f2489d22b683b5ae6655","observation_id":"81979b2d-1c39-4b4b-8132-ca30308ab3d3","resolution":{"observed_at":"2026-05-11T00:20:52.819779Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2604.08358","last_updated":"2026-04-09T15:21:41Z","snapshot_observed_at":"2026-07-06T22:57:26.678728Z","submitted_at":"2026-04-09T15:21:41Z","title":"Scalable Neural Decoders for Practical Fault-Tolerant Quantum Computation","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-05-10T18:14:22.026474Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2604.08358"},"observation_digest":"sha256:00244b575787a9e90527be0432d521c33fff6011fb2433f10aab8de1e6259d61","observation_id":"c78ed247-9604-4283-9737-43dc52f1cdd3","resolution":{"observed_at":"2026-05-11T05:16:02.698169Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2604.18556","last_updated":"2026-05-15T09:34:30Z","snapshot_observed_at":"2026-07-06T23:05:21.974248Z","submitted_at":"2026-04-20T17:45:47Z","title":"GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-10T05:29:51.182114Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2604.18556"},"observation_digest":"sha256:d279198d5f9ae2c88500e6b8334eb5008b2c4d9812920bdad0ee7bda493ca014","observation_id":"1dfb98b8-895e-48ea-8d9b-659802aadaa7","resolution":{"observed_at":"2026-05-10T05:36:02.311253Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2604.18556","last_updated":"2026-05-15T09:34:30Z","snapshot_observed_at":"2026-07-06T23:05:21.974248Z","submitted_at":"2026-04-20T17:45:47Z","title":"GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-19T18:01:08.514022Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2604.18556"},"observation_digest":"sha256:2f19f1ea5cb237afe313aba767bc778acf1ec88725c8c3969a4de9cac1d31db6","observation_id":"34c133dd-7700-4a2a-a61a-ce1f55460d33","resolution":{"observed_at":"2026-05-19T18:02:42.232038Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2604.25550","last_updated":"2026-04-28T12:15:55Z","snapshot_observed_at":"2026-07-06T23:11:25.757664Z","submitted_at":"2026-04-28T12:15:55Z","title":"Enhancing SignSGD: Small-Batch Convergence Analysis and a Hybrid Switching Strategy","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-07T16:54:48.823566Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2604.25550"},"observation_digest":"sha256:9f4f85a17b5cdb91fb45d283b489f652719b9051703584d31629397dbae61e5d","observation_id":"cc08a3d8-239e-4a2b-9470-b410a69bff2f","resolution":{"observed_at":"2026-05-11T23:31:14.585652Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2605.02317","last_updated":"2026-05-06T13:42:00Z","snapshot_observed_at":"2026-07-06T23:15:27.816549Z","submitted_at":"2026-05-04T08:14:51Z","title":"Anon: Extrapolating Adaptivity Beyond SGD and Adam","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-09T16:25:36.073417Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2605.02317"},"observation_digest":"sha256:5f215621a4fcafd97558db5bca36043a1a7a84adeb8fc54d5b02228c022672ac","observation_id":"57fee187-37eb-436c-8b2c-0713e868ed86","resolution":{"observed_at":"2026-05-11T16:31:09.576204Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2605.09176","last_updated":"2026-05-09T21:34:28Z","snapshot_observed_at":"2026-08-09T01:35:49.848565Z","submitted_at":"2026-05-09T21:34:28Z","title":"Navigating LLM Valley: From AdamW to Memory-Efficient and Matrix-Based Optimizers","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-12T04:01:32.057022Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2605.09176"},"observation_digest":"sha256:084fbceedb4aed0de094d3b032ae662e237c5a48a44cff8064dac93555a3e949","observation_id":"484cb4e2-d453-4546-a55d-eed293501774","resolution":{"observed_at":"2026-05-12T06:41:45.692719Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2605.17156","last_updated":"2026-05-20T22:01:02Z","snapshot_observed_at":"2026-07-06T23:28:12.114488Z","submitted_at":"2026-05-16T21:01:29Z","title":"Sparse Mamba Decoder for Quantum Error Correction: Efficient Defect-Centric Processing of Surface Code Syndromes","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-20T14:28:37.056214Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2605.17156"},"observation_digest":"sha256:9f735b274a2860f0057c2b692da39d86a037bd89bd938af2bd38af073b50ab04","observation_id":"a2ed7bde-4868-4215-b687-feaa51896a04","resolution":{"observed_at":"2026-05-20T14:33:21.545179Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2605.17156","last_updated":"2026-05-20T22:01:02Z","snapshot_observed_at":"2026-07-06T23:28:12.114488Z","submitted_at":"2026-05-16T21:01:29Z","title":"Sparse Mamba Decoder for Quantum Error Correction: Efficient Defect-Centric Processing of Surface Code Syndromes","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-22T09:40:40.741002Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2605.17156"},"observation_digest":"sha256:2916357ef6484afe1bea3ae172239bbd719e184a4709c5cc0b62cf41a670ec70","observation_id":"5dbf0b22-ae97-45d3-968b-b2d455b01c52","resolution":{"observed_at":"2026-05-22T09:41:21.631001Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2606.25971","last_updated":"2026-07-17T13:42:08Z","snapshot_observed_at":"2026-08-02T10:13:56.529128Z","submitted_at":"2026-06-24T15:40:26Z","title":"Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors","version":1},"reference_index":152,"source":"arxiv_source","source_observed_at":"2026-06-25T20:05:09.179627Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2606.25971"},"observation_digest":"sha256:7ca2e3b190517755b6137e2f779d4a2a324da8121b599a11c091233e07162fec","observation_id":"fc983ebb-95ac-4364-a8c6-fdbd2916168a","resolution":{"observed_at":"2026-07-04T20:30:07.708005Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2606.29554","last_updated":"2026-06-28T18:44:08Z","snapshot_observed_at":"2026-07-07T00:03:31.715960Z","submitted_at":"2026-06-28T18:44:08Z","title":"Optimizer Memory Makes Shuffle Order a First-Order Source of Fine-Tuning Noise","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-06-30T07:15:56.974540Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2606.29554"},"observation_digest":"sha256:37ce44f8a0d3273c55725a9dc4d38a4a432678b4d48dc7d91770331502234f48","observation_id":"59e9cc19-d5c2-4fa8-86c0-60d3adc6a026","resolution":{"observed_at":"2026-06-30T07:24:21.845046Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2607.01455","last_updated":"2026-07-15T02:52:22Z","snapshot_observed_at":"2026-08-06T17:57:36.341425Z","submitted_at":"2026-07-01T20:21:03Z","title":"Token Geometry","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-03T21:08:26.712950Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2607.01455"},"observation_digest":"sha256:add3751cada0ea710496f234bee940eb7b0eab87a9935e642e0d26e03f1d464d","observation_id":"35da35ee-c52e-40c0-a620-776a56160e05","resolution":{"observed_at":"2026-07-03T21:08:57.420888Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-12T08:48:22.161005Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.01455","last_updated":"2026-07-15T02:52:22Z","snapshot_observed_at":"2026-08-06T17:57:36.341425Z","submitted_at":"2026-07-01T20:21:03Z","title":"Token Geometry","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-12T08:48:22.161005Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2607.01455"},"observation_digest":"sha256:8da8c4242f937ac2cd4c98fd7272cfb9a87cdeaff975dee567bed3de1501aaea","observation_id":"5ac20898-c417-4c04-9797-4a2bb3d07a06","resolution":{"observed_at":"2026-07-12T08:48:22.161005Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":"2302.06675","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-07-09T17:36:25.406188Z","title":"Symbolic discovery of optimization algorithms","venue":"cs.LG","work_id":"2151a7b4-dbf0-490e-8582-83731a6bc17c","year":2023},"citing_paper":{"arxiv_id":"2607.07206","last_updated":"2026-07-11T18:06:27Z","snapshot_observed_at":"2026-07-31T02:44:27.308999Z","submitted_at":"2026-07-08T09:40:44Z","title":"Causal Optimizer Interaction Calculus: Hidden Geometric Relaxation and Identifiable Interventions","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-07-09T17:31:09.270342Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2607.07206"},"observation_digest":"sha256:507a97aa9f9f1edf8278aab3838c40ebbb4d597636912c07124b8ae87a473cc3","observation_id":"5f5afe3f-29da-4905-995f-1d00d2663733","resolution":{"observed_at":"2026-07-09T17:36:25.407937Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-01T19:44:28.240194Z","title":"arXiv preprint arXiv:2302.06675 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.16882","last_updated":"2026-07-18T16:51:40Z","snapshot_observed_at":"2026-08-08T03:06:27.280388Z","submitted_at":"2026-07-18T16:51:40Z","title":"HyBDM: Multi-Scale Hybrid Experts for Time Series Forecasting with Bidirectional Dependency Modeling","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-01T19:44:28.240194Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2607.16882"},"observation_digest":"sha256:94a1ef9c96b54e3fcbb792c8693733bcbfa4f2581e68dd59cb49f6b00d78ca34","observation_id":"ab84205d-658e-476d-969b-1d4f3a51ee82","resolution":{"observed_at":"2026-08-01T19:44:28.240194Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.06675","snapshot_observed_at":"2026-08-01T06:30:01.507209Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.21855","last_updated":"2026-07-23T22:49:51Z","snapshot_observed_at":"2026-08-02T08:26:33.254578Z","submitted_at":"2026-07-23T22:49:51Z","title":"Searching the Space of Feed-Forward Neural-Network Weight-Update Rules with Fixed Depth Symbolic Regression","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T06:30:01.507209Z"},"links":{"cited_paper":"/paper/2302.06675","citing_paper":"/paper/2607.21855"},"observation_digest":"sha256:ba98c65f7bf72e23326a4c00ab3c0b59a611e14c8754d08b37e9d973fe620ebf","observation_id":"63a0e92a-972b-46f3-80e7-78c8bc76a5dd","resolution":{"observed_at":"2026-08-01T06:30:01.507209Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2302.06675/citation-record","integrity":"/paper/2302.06675/integrity","json":"/paper/2302.06675/citation-record.json","paper":"/paper/2302.06675"},"outbound":[],"paper":{"arxiv_id":"2302.06675","last_updated":"2023-05-08T21:49:57Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-02T01:29:22.350700Z","submitted_at":"2023-02-13T20:27:30Z","title":"Symbolic Discovery of Optimization Algorithms"},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 31 inbound Pith citation observations for arXiv:2302.06675."}