{"as_of":"2026-08-18T00:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b37f33f458a7fa36958e25909064ee4a0d71b24266404454a843582772017656","coverage":[{"denominator":6,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-09T00:52:14.197771Z","state":"measured"},{"denominator":6,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":6,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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/2502.03787/citation-record","integrity":"/paper/2502.03787/integrity","json":"/paper/2502.03787/citation-record.json","paper":"/paper/2502.03787"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-09T00:52:14.172417Z","title":"Mirror descent and nonlinear projected subgradient methods for convex optimization","venue":null,"work_id":null,"year":2003},"citing_paper":{"arxiv_id":"2502.03787","last_updated":"2025-02-06T05:24:35Z","snapshot_observed_at":"2026-08-17T17:38:40.225954Z","submitted_at":"2025-02-06T05:24:35Z","title":"Iterate to Accelerate: A Unified Framework for Iterative Reasoning and Feedback Convergence","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-09T00:52:14.172417Z"},"links":{"citing_paper":"/paper/2502.03787"},"observation_digest":"sha256:4f1e9e7055d73f2621351b9a05716ec81e935181bcdfeba68d41f532cfdb7d53","observation_id":"bf869ad0-a2b3-4d08-a970-3cb6cabe026d","resolution":{"observed_at":"2026-08-09T00:52:14.172417Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1512.03965","last_updated":"2016-05-09T02:16:54Z","snapshot_observed_at":"2026-08-14T22:18:49.793506Z","submitted_at":"2015-12-12T21:41:24Z","title":"The Power of Depth for Feedforward Neural Networks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1512.03965","snapshot_observed_at":"2026-08-09T00:52:14.177600Z","title":"The power of depth for feedforward neural networks, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.03787","last_updated":"2025-02-06T05:24:35Z","snapshot_observed_at":"2026-08-17T17:38:40.225954Z","submitted_at":"2025-02-06T05:24:35Z","title":"Iterate to Accelerate: A Unified Framework for Iterative Reasoning and Feedback Convergence","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-09T00:52:14.177600Z"},"links":{"cited_paper":"/paper/1512.03965","citing_paper":"/paper/2502.03787"},"observation_digest":"sha256:f23c0a862b81360925ddbc3082fd9ddc2ceafc11631dead18c4d415b352410d7","observation_id":"4854e5db-2fda-4b73-8e08-f32e01157fa1","resolution":{"observed_at":"2026-08-09T00:52:14.177600Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.17737","last_updated":"2025-04-28T19:29:34Z","snapshot_observed_at":"2026-08-17T11:51:08.518402Z","submitted_at":"2024-12-23T17:36:51Z","title":"Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback","version":6},"cited_work":{"arxiv_id":"2412.17737","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.17737","snapshot_observed_at":"2026-08-09T00:52:14.275313Z","title":"Contextual Feedback Loops: Amplifying Deep Reasoning with Iterative Top-Down Feedback","venue":"cs.LG","work_id":"2d62fbd0-8fb6-4a4b-b19d-9d691564feae","year":2024},"citing_paper":{"arxiv_id":"2502.03787","last_updated":"2025-02-06T05:24:35Z","snapshot_observed_at":"2026-08-17T17:38:40.225954Z","submitted_at":"2025-02-06T05:24:35Z","title":"Iterate to Accelerate: A Unified Framework for Iterative Reasoning and Feedback Convergence","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-09T00:52:14.182478Z"},"links":{"cited_paper":"/paper/2412.17737","citing_paper":"/paper/2502.03787"},"observation_digest":"sha256:19f8b6396d0cbd292aced44395d1418cd7c0d19a0b7145fa4df852bcfce59628","observation_id":"ddd7fc60-926a-4024-ae36-a7e25be86da6","resolution":{"observed_at":"2026-08-09T00:52:14.280057Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-09T00:52:14.299108Z","title":"A method for solving the convex programming problem with convergence rate o(1/k2)","venue":null,"work_id":"13dd658f-8576-4f18-9950-1d3431eb9b20","year":1983},"citing_paper":{"arxiv_id":"2502.03787","last_updated":"2025-02-06T05:24:35Z","snapshot_observed_at":"2026-08-17T17:38:40.225954Z","submitted_at":"2025-02-06T05:24:35Z","title":"Iterate to Accelerate: A Unified Framework for Iterative Reasoning and Feedback Convergence","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-09T00:52:14.187649Z"},"links":{"citing_paper":"/paper/2502.03787"},"observation_digest":"sha256:0376a7ada09455d87388137d0a1ed700dbbc2509dee3df3107a6162d7957e4d2","observation_id":"2f04596f-9058-4e05-9a1b-0d3f84d28d57","resolution":{"observed_at":"2026-08-09T00:52:14.302822Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1602.04485","last_updated":"2016-05-27T22:11:26Z","snapshot_observed_at":"2026-08-16T17:04:23.592147Z","submitted_at":"2016-02-14T18:36:59Z","title":"Benefits of depth in neural networks","version":2},"cited_work":{"arxiv_id":"1602.04485","doi":null,"metadata_source":"pith","pith_arxiv_id":"1602.04485","snapshot_observed_at":"2026-08-09T00:52:14.254349Z","title":"Benefits of depth in neural networks","venue":"cs.LG","work_id":"e6e79b73-8e1b-47a1-8793-ed06510f05ff","year":2016},"citing_paper":{"arxiv_id":"2502.03787","last_updated":"2025-02-06T05:24:35Z","snapshot_observed_at":"2026-08-17T17:38:40.225954Z","submitted_at":"2025-02-06T05:24:35Z","title":"Iterate to Accelerate: A Unified Framework for Iterative Reasoning and Feedback Convergence","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-09T00:52:14.192888Z"},"links":{"cited_paper":"/paper/1602.04485","citing_paper":"/paper/2502.03787"},"observation_digest":"sha256:a86d4a3d91af63f12c04401a54ecaa720512bf726c79c5d13ebdad632a817987","observation_id":"4b2127da-97ec-4295-bbfe-d755e5174519","resolution":{"observed_at":"2026-08-09T00:52:14.260841Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.11903","last_updated":"2023-01-10T23:07:57Z","snapshot_observed_at":"2026-08-13T07:04:41.220509Z","submitted_at":"2022-01-28T02:33:07Z","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2201.11903","snapshot_observed_at":"2026-08-09T00:52:14.197771Z","title":"Chain-of-thought prompting elicits reasoning in large language models, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2502.03787","last_updated":"2025-02-06T05:24:35Z","snapshot_observed_at":"2026-08-17T17:38:40.225954Z","submitted_at":"2025-02-06T05:24:35Z","title":"Iterate to Accelerate: A Unified Framework for Iterative Reasoning and Feedback Convergence","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-09T00:52:14.197771Z"},"links":{"cited_paper":"/paper/2201.11903","citing_paper":"/paper/2502.03787"},"observation_digest":"sha256:e65cb276265299caf1da290d65798801a2cc2f655e492049fe8f48df227c32ae","observation_id":"cf56fcad-8814-43af-9c4e-f6c285cc7354","resolution":{"observed_at":"2026-08-09T00:52:14.197771Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2502.03787","last_updated":"2025-02-06T05:24:35Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-17T17:38:40.225954Z","submitted_at":"2025-02-06T05:24:35Z","title":"Iterate to Accelerate: A Unified Framework for Iterative Reasoning and Feedback Convergence"},"reference_resolution":{"displayed":6,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":3,"verified_exact":2,"verified_fuzzy":1},"total_outbound_references":6},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 6 of 6 outbound references and 0 inbound Pith citation observations for arXiv:2502.03787."}