{"as_of":"2026-08-10T09:46:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9456062fd92cc5bebfc8b4c37367dcc75aed6de7cb5403b18a68fa25cd2e9c82","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":12,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":12,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+00:00","state":"measured"},{"denominator":12,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T19:15:54.827258Z","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":"2026-07-10T16:57:24.480526Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1910.05929","last_updated":"2019-10-14T06:23:38Z","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05929","snapshot_observed_at":"2026-08-08T19:15:54.827258Z","title":"and Ganguli, S","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.05475","last_updated":"2025-02-08T07:24:04Z","snapshot_observed_at":"2026-08-09T02:15:12.668653Z","submitted_at":"2025-02-08T07:24:04Z","title":"You Are What You Eat -- AI Alignment Requires Understanding How Data Shapes Structure and Generalisation","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-08T19:15:54.827258Z"},"links":{"cited_paper":"/paper/1910.05929","citing_paper":"/paper/2502.05475"},"observation_digest":"sha256:c99df701cfa9f168790fc767eced799e5e4889ceddda9f9579a9723b0bab1c4a","observation_id":"2fed587c-cbae-4111-80ca-94fc8cad950a","resolution":{"observed_at":"2026-08-08T19:15:54.827258Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05929","last_updated":"2019-10-14T06:23:38Z","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05929","snapshot_observed_at":"2026-08-07T05:45:27.856171Z","title":"and Ganguli, S","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2506.07247","last_updated":"2025-06-08T18:05:31Z","snapshot_observed_at":"2026-08-09T04:45:47.081357Z","submitted_at":"2025-06-08T18:05:31Z","title":"Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T05:45:27.856171Z"},"links":{"cited_paper":"/paper/1910.05929","citing_paper":"/paper/2506.07247"},"observation_digest":"sha256:9788d9102c5c6c4b2150a5c853e98897b51477aa2d00a1d3c29784f8253cc3b9","observation_id":"a56633bb-5f6a-4993-a68f-7905f02e0769","resolution":{"observed_at":"2026-08-07T05:45:27.856171Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05929","last_updated":"2019-10-14T06:23:38Z","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes","version":1},"cited_work":{"arxiv_id":"1910.05929","doi":null,"metadata_source":"pith","pith_arxiv_id":"1910.05929","snapshot_observed_at":"2026-07-10T16:57:24.480526Z","title":"Fort and S","venue":"cs.LG","work_id":"4853cdad-6035-4f93-9f54-1adbaeacf22d","year":2019},"citing_paper":{"arxiv_id":"2604.04655","last_updated":"2026-04-06T13:05:27Z","snapshot_observed_at":"2026-07-06T22:53:33.177713Z","submitted_at":"2026-04-06T13:05:27Z","title":"Grokking as Dimensional Phase Transition in Neural Networks","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-10T19:34:03.055921Z"},"links":{"cited_paper":"/paper/1910.05929","citing_paper":"/paper/2604.04655"},"observation_digest":"sha256:f57f107181a253185da48e81a5b662d87c4ff07ed1c2b00af43304dd4b00b848","observation_id":"bcf15b41-4805-40ff-a453-913eb974f0df","resolution":{"observed_at":"2026-05-10T22:45:51.176265Z","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":"1910.05929","last_updated":"2019-10-14T06:23:38Z","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes","version":1},"cited_work":{"arxiv_id":"1910.05929","doi":null,"metadata_source":"pith","pith_arxiv_id":"1910.05929","snapshot_observed_at":"2026-07-10T16:57:24.480526Z","title":"Fort and S","venue":"cs.LG","work_id":"4853cdad-6035-4f93-9f54-1adbaeacf22d","year":2019},"citing_paper":{"arxiv_id":"2604.16431","last_updated":"2026-04-06T13:43:20Z","snapshot_observed_at":"2026-07-06T23:03:43.854612Z","submitted_at":"2026-04-06T13:43:20Z","title":"Dimensional Criticality at Grokking Across MLPs and Transformers","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T19:23:20.777796Z"},"links":{"cited_paper":"/paper/1910.05929","citing_paper":"/paper/2604.16431"},"observation_digest":"sha256:3fcea863e453b632e18251a9d36a75f5b4a1359544919510073a1ffae6880b62","observation_id":"8f4c7ec9-0729-49e4-ac3f-61fc23847565","resolution":{"observed_at":"2026-05-10T23:00:50.619745Z","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":"1910.05929","last_updated":"2019-10-14T06:23:38Z","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes","version":1},"cited_work":{"arxiv_id":"1910.05929","doi":null,"metadata_source":"pith","pith_arxiv_id":"1910.05929","snapshot_observed_at":"2026-07-10T16:57:24.480526Z","title":"Fort and S","venue":"cs.LG","work_id":"4853cdad-6035-4f93-9f54-1adbaeacf22d","year":2019},"citing_paper":{"arxiv_id":"2605.07790","last_updated":"2026-05-17T21:44:43Z","snapshot_observed_at":"2026-07-31T05:29:21.572748Z","submitted_at":"2026-05-08T14:27:41Z","title":"Hessian Surgery: Class-Targeted Post-Hoc Rebalancing via Hessian Spike Perturbation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-11T03:35:50.729818Z"},"links":{"cited_paper":"/paper/1910.05929","citing_paper":"/paper/2605.07790"},"observation_digest":"sha256:5a504d14c276724446e6e51f4665f53c1c7bf0b1559f8e605bd5588c4213c47c","observation_id":"968c09e5-ccb2-42da-92d6-f5ba27f646a4","resolution":{"observed_at":"2026-05-11T03:40:53.828143Z","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":"1910.05929","last_updated":"2019-10-14T06:23:38Z","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes","version":1},"cited_work":{"arxiv_id":"1910.05929","doi":null,"metadata_source":"pith","pith_arxiv_id":"1910.05929","snapshot_observed_at":"2026-07-10T16:57:24.480526Z","title":"Fort and S","venue":"cs.LG","work_id":"4853cdad-6035-4f93-9f54-1adbaeacf22d","year":2019},"citing_paper":{"arxiv_id":"2605.07790","last_updated":"2026-05-17T21:44:43Z","snapshot_observed_at":"2026-07-31T05:29:21.572748Z","submitted_at":"2026-05-08T14:27:41Z","title":"Hessian Surgery: Class-Targeted Post-Hoc Rebalancing via Hessian Spike Perturbation","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-20T22:54:53.975746Z"},"links":{"cited_paper":"/paper/1910.05929","citing_paper":"/paper/2605.07790"},"observation_digest":"sha256:7870927dc58ee3c90179283fe32b41697a8161f229e2634bf631bb680778674f","observation_id":"4afdaee2-c6e0-4e35-9d32-3c8ee9ba47b5","resolution":{"observed_at":"2026-05-20T22:59:11.904609Z","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":"1910.05929","last_updated":"2019-10-14T06:23:38Z","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes","version":1},"cited_work":{"arxiv_id":"1910.05929","doi":null,"metadata_source":"pith","pith_arxiv_id":"1910.05929","snapshot_observed_at":"2026-07-10T16:57:24.480526Z","title":"Fort and S","venue":"cs.LG","work_id":"4853cdad-6035-4f93-9f54-1adbaeacf22d","year":2019},"citing_paper":{"arxiv_id":"2605.28986","last_updated":"2026-07-21T19:53:26Z","snapshot_observed_at":"2026-08-05T20:19:39.988720Z","submitted_at":"2026-05-27T18:44:36Z","title":"Comparing Classical Simulation and Sample-Based Learning of Quantum Systems","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-29T11:13:54.702077Z"},"links":{"cited_paper":"/paper/1910.05929","citing_paper":"/paper/2605.28986"},"observation_digest":"sha256:52d53fb56ebded6d67460ce7cc68020db18e14673aea91a335aa5bd38f383e59","observation_id":"71820abe-ddf8-4d94-8168-d32009de5d7a","resolution":{"observed_at":"2026-06-29T11:23:21.841533Z","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":"1910.05929","last_updated":"2019-10-14T06:23:38Z","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.05929","snapshot_observed_at":"2026-08-02T12:58:10.753603Z","title":"Fort and S","venue":null,"work_id":null,"year":1910},"citing_paper":{"arxiv_id":"2605.28986","last_updated":"2026-07-21T19:53:26Z","snapshot_observed_at":"2026-08-05T20:19:39.988720Z","submitted_at":"2026-05-27T18:44:36Z","title":"Comparing Classical Simulation and Sample-Based Learning of Quantum Systems","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-02T12:58:10.753603Z"},"links":{"cited_paper":"/paper/1910.05929","citing_paper":"/paper/2605.28986"},"observation_digest":"sha256:1013071c66f239cc310307240bb0904cfae8430d58ac9ef81c205d9371a7613c","observation_id":"a2971a6f-271f-421f-b7a0-fb176de8a2bf","resolution":{"observed_at":"2026-08-02T12:58:10.753603Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.05929","last_updated":"2019-10-14T06:23:38Z","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes","version":1},"cited_work":{"arxiv_id":"1910.05929","doi":null,"metadata_source":"pith","pith_arxiv_id":"1910.05929","snapshot_observed_at":"2026-07-10T16:57:24.480526Z","title":"Fort and S","venue":"cs.LG","work_id":"4853cdad-6035-4f93-9f54-1adbaeacf22d","year":2019},"citing_paper":{"arxiv_id":"2606.04662","last_updated":"2026-06-03T09:40:30Z","snapshot_observed_at":"2026-07-06T23:44:42.700120Z","submitted_at":"2026-06-03T09:40:30Z","title":"Why Muon Outperforms Adam: A Curvature Perspective","version":1},"reference_index":141,"source":"arxiv_source","source_observed_at":"2026-06-28T07:04:21.012269Z"},"links":{"cited_paper":"/paper/1910.05929","citing_paper":"/paper/2606.04662"},"observation_digest":"sha256:13bafe3c9e041feb1a2ddeaef387a4d7ecd6ba7fcd15c590f7f9146a4749a6cd","observation_id":"bb4c78ab-fee9-41ce-9164-9d4f051c6884","resolution":{"observed_at":"2026-07-02T07:06:44.958570Z","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":"1910.05929","last_updated":"2019-10-14T06:23:38Z","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes","version":1},"cited_work":{"arxiv_id":"1910.05929","doi":null,"metadata_source":"pith","pith_arxiv_id":"1910.05929","snapshot_observed_at":"2026-07-10T16:57:24.480526Z","title":"Fort and S","venue":"cs.LG","work_id":"4853cdad-6035-4f93-9f54-1adbaeacf22d","year":2019},"citing_paper":{"arxiv_id":"2606.13637","last_updated":"2026-06-11T17:45:41Z","snapshot_observed_at":"2026-08-07T06:58:57.108668Z","submitted_at":"2026-06-11T17:45:41Z","title":"The Stable Recovery Manifold: Geometric Principles Governing Recoverability in Continual Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-27T07:15:03.905388Z"},"links":{"cited_paper":"/paper/1910.05929","citing_paper":"/paper/2606.13637"},"observation_digest":"sha256:0847d8c94f577753958d0ba78b1466dffb183f2fb9937acc42f7d61bf3076581","observation_id":"32271986-c7de-444b-ac7c-078201942b5c","resolution":{"observed_at":"2026-07-03T14:08:21.622705Z","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":"1910.05929","last_updated":"2019-10-14T06:23:38Z","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes","version":1},"cited_work":{"arxiv_id":"1910.05929","doi":null,"metadata_source":"pith","pith_arxiv_id":"1910.05929","snapshot_observed_at":"2026-07-10T16:57:24.480526Z","title":"Fort and S","venue":"cs.LG","work_id":"4853cdad-6035-4f93-9f54-1adbaeacf22d","year":2019},"citing_paper":{"arxiv_id":"2606.30226","last_updated":"2026-06-29T12:39:39Z","snapshot_observed_at":"2026-08-08T11:23:32.965690Z","submitted_at":"2026-06-29T12:39:39Z","title":"Characterizing Optimizer-Dependent Training Dynamics Through Hessian Eigenvector Displacement and Localization","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-06-30T07:53:59.861734Z"},"links":{"cited_paper":"/paper/1910.05929","citing_paper":"/paper/2606.30226"},"observation_digest":"sha256:8b68797870054fefd1473d94d2c32055d5952fafec5705dcb770f036d1b3d54d","observation_id":"4d6c98d9-f6e5-4f25-b058-b835bb2a73f6","resolution":{"observed_at":"2026-06-30T07:54:21.732763Z","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":"1910.05929","last_updated":"2019-10-14T06:23:38Z","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes","version":1},"cited_work":{"arxiv_id":"1910.05929","doi":null,"metadata_source":"pith","pith_arxiv_id":"1910.05929","snapshot_observed_at":"2026-07-10T16:57:24.480526Z","title":"Fort and S","venue":"cs.LG","work_id":"4853cdad-6035-4f93-9f54-1adbaeacf22d","year":2019},"citing_paper":{"arxiv_id":"2607.07845","last_updated":"2026-07-08T18:27:16Z","snapshot_observed_at":"2026-08-08T15:36:46.470151Z","submitted_at":"2026-07-08T18:27:16Z","title":"Explaining Near-Zero Hessian Eigenvalues Through Approximate Symmetries in Neural Networks","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-10T16:51:04.235933Z"},"links":{"cited_paper":"/paper/1910.05929","citing_paper":"/paper/2607.07845"},"observation_digest":"sha256:c2b5a4b1411fc027e75f9a13aa9943bbb59c2f151b8b8477f942aa7753a056ac","observation_id":"e572933c-cd91-44a7-bdc8-b982538b572a","resolution":{"observed_at":"2026-07-10T16:57:24.481933Z","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"}}],"links":{"evidence":"/evidence","html":"/paper/1910.05929/citation-record","integrity":"/paper/1910.05929/integrity","json":"/paper/1910.05929/citation-record.json","paper":"/paper/1910.05929"},"outbound":[],"paper":{"arxiv_id":"1910.05929","last_updated":"2019-10-14T06:23:38Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-08T12:38:41.800285Z","submitted_at":"2019-10-14T06:23:38Z","title":"Emergent properties of the local geometry of neural loss landscapes"},"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 12 inbound Pith citation observations for arXiv:1910.05929."}