{"as_of":"2026-08-21T05:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4565d4a27237e2e6549e4ae5f9040e859d18593569f240b3b043bb6916e3d96e","coverage":[{"denominator":7,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T13:54:28.588116Z","state":"measured"},{"denominator":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.19968/citation-record","integrity":"/paper/2507.19968/integrity","json":"/paper/2507.19968/citation-record.json","paper":"/paper/2507.19968"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1406.2572","last_updated":"2014-06-10T14:52:14Z","snapshot_observed_at":"2026-08-14T23:30:53.901574Z","submitted_at":"2014-06-10T14:52:14Z","title":"Identifying and attacking the saddle point problem in high-dimensional non-convex optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1406.2572","snapshot_observed_at":"2026-08-06T13:54:28.563026Z","title":"N., Pascanu, R., Gulcehre, C., Cho, K., Ganguli, S., & Bengio, Y","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.19968","last_updated":"2025-07-26T14:57:32Z","snapshot_observed_at":"2026-08-12T23:56:32.999272Z","submitted_at":"2025-07-26T14:57:32Z","title":"Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T13:54:28.563026Z"},"links":{"cited_paper":"/paper/1406.2572","citing_paper":"/paper/2507.19968"},"observation_digest":"sha256:5e4924bb9044cf554072dd3aa288f435df99963f036a46108ffb00d4705e3e88","observation_id":"3a2ac1b2-7b62-4483-afab-de8fe8c5a599","resolution":{"observed_at":"2026-08-06T13:54:28.563026Z","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":"2026-08-06T13:54:28.567361Z","title":null,"venue":null,"work_id":null,"year":1951},"citing_paper":{"arxiv_id":"2507.19968","last_updated":"2025-07-26T14:57:32Z","snapshot_observed_at":"2026-08-12T23:56:32.999272Z","submitted_at":"2025-07-26T14:57:32Z","title":"Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T13:54:28.567361Z"},"links":{"citing_paper":"/paper/2507.19968"},"observation_digest":"sha256:abde37dfb63f7e6dcd2c77a1a8f8a3662177fe2865915d72a04d55dbb266333b","observation_id":"99e55d54-9d0a-4f34-8030-ad7490fc5161","resolution":{"observed_at":"2026-08-06T13:54:28.567361Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-06T13:54:28.571352Z","title":"P., & Ba, J","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.19968","last_updated":"2025-07-26T14:57:32Z","snapshot_observed_at":"2026-08-12T23:56:32.999272Z","submitted_at":"2025-07-26T14:57:32Z","title":"Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T13:54:28.571352Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2507.19968"},"observation_digest":"sha256:f0ebd4a72cde69caa979dc27aba89b359ca17a781b7bef205c3960833e1b6d16","observation_id":"3207cbcb-0a02-4299-992f-f23813393914","resolution":{"observed_at":"2026-08-06T13:54:28.571352Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1711.05101","last_updated":"2019-01-04T21:01:49Z","snapshot_observed_at":"2026-08-14T20:13:52.872565Z","submitted_at":"2017-11-14T14:24:06Z","title":"Decoupled Weight Decay Regularization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1711.05101","snapshot_observed_at":"2026-08-06T13:54:28.575630Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.19968","last_updated":"2025-07-26T14:57:32Z","snapshot_observed_at":"2026-08-12T23:56:32.999272Z","submitted_at":"2025-07-26T14:57:32Z","title":"Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T13:54:28.575630Z"},"links":{"cited_paper":"/paper/1711.05101","citing_paper":"/paper/2507.19968"},"observation_digest":"sha256:0e998f6c0b7a86543bf30ce79f5819c24b190108743ffaa71f6875f0e25e4181","observation_id":"4d8d8047-05c9-42b0-b178-af2be0488025","resolution":{"observed_at":"2026-08-06T13:54:28.575630Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.12851","last_updated":"2023-07-21T10:22:53Z","snapshot_observed_at":"2026-08-21T02:23:33.314431Z","submitted_at":"2023-05-22T09:20:58Z","title":"Enhancing Coherence of Extractive Summarization with Multitask Learning","version":2},"cited_work":{"arxiv_id":"2305.12851","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.12851","snapshot_observed_at":"2026-08-06T13:54:28.626048Z","title":"Enhancing Coherence of Extractive Summarization with Multitask Learning","venue":"cs.CL","work_id":"fc12ddaa-872e-47a2-919e-dc57834927ce","year":2023},"citing_paper":{"arxiv_id":"2507.19968","last_updated":"2025-07-26T14:57:32Z","snapshot_observed_at":"2026-08-12T23:56:32.999272Z","submitted_at":"2025-07-26T14:57:32Z","title":"Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T13:54:28.579702Z"},"links":{"cited_paper":"/paper/2305.12851","citing_paper":"/paper/2507.19968"},"observation_digest":"sha256:d91ef1296e91087d81f9a1a6a909e6cb6345c61c3f1d007e958e1124ac20ea2b","observation_id":"81e6fe73-e165-4f9f-8212-ef881e49dfac","resolution":{"observed_at":"2026-08-06T13:54:28.631959Z","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":"2026-08-06T13:54:28.583940Z","title":null,"venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"2507.19968","last_updated":"2025-07-26T14:57:32Z","snapshot_observed_at":"2026-08-12T23:56:32.999272Z","submitted_at":"2025-07-26T14:57:32Z","title":"Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T13:54:28.583940Z"},"links":{"citing_paper":"/paper/2507.19968"},"observation_digest":"sha256:d0e33a0ed1dd22762b1b4e7e9c74a47f62d6781f225a6ffa8a11abf2587e21f1","observation_id":"540ea6ac-6fad-4194-935f-1b62f0a5a3a0","resolution":{"observed_at":"2026-08-06T13:54:28.583940Z","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":"2026-08-06T13:54:28.806308Z","title":null,"venue":null,"work_id":"1605fbea-b050-4a7f-85e7-2b26087a93e8","year":2022},"citing_paper":{"arxiv_id":"2507.19968","last_updated":"2025-07-26T14:57:32Z","snapshot_observed_at":"2026-08-12T23:56:32.999272Z","submitted_at":"2025-07-26T14:57:32Z","title":"Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T13:54:28.588116Z"},"links":{"citing_paper":"/paper/2507.19968"},"observation_digest":"sha256:8d441b4b09237e4e83201e2163ad62759ff97447e9991cbbb31cf9a0048be345","observation_id":"8c20d61c-dfe0-46f7-9131-dff48c7cab77","resolution":{"observed_at":"2026-08-06T13:54:28.809982Z","resolver_source":"raw_fallback","status":"unresolved"},"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"}}],"paper":{"arxiv_id":"2507.19968","last_updated":"2025-07-26T14:57:32Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-12T23:56:32.999272Z","submitted_at":"2025-07-26T14:57:32Z","title":"Dimer-Enhanced Optimization: A First-Order Approach to Escaping Saddle Points in Neural Network Training"},"reference_resolution":{"displayed":7,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":1,"verified_fuzzy":0},"total_outbound_references":7},"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 21 August 2026, this Paper Citation Record lists 7 of 7 outbound references and 0 inbound Pith citation observations for arXiv:2507.19968."}