{"as_of":"2026-08-08T17:55:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f7b2b19da3b9cb36dd5a36ba7d7c84fa21a3e605412f277f2afc86d5370fff0a","coverage":[{"denominator":12,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T08:19:21.040100Z","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":"2026-08-08T06:32:00.761636+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/2607.27389/citation-record","integrity":"/paper/2607.27389/integrity","json":"/paper/2607.27389/citation-record.json","paper":"/paper/2607.27389"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T08:19:21.040100Z","title":"Table 11: Simplex-oriented host results, averaged over three independent, seed-paired repetitions","venue":null,"work_id":null,"year":1947},"citing_paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-01T08:19:21.040100Z"},"links":{"citing_paper":"/paper/2607.27389"},"observation_digest":"sha256:f70c5c2151402f4084eddcb4f56e3b22c4fbec17ddd60d9df88d757ca2c5f0ca","observation_id":"d085b85d-e156-4628-873f-8d07cb166f36","resolution":{"observed_at":"2026-08-01T08:19:21.040100Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.07515","last_updated":"2026-07-29T17:02:19Z","snapshot_observed_at":"2026-08-05T22:04:56.135296Z","submitted_at":"2025-08-11T00:13:36Z","title":"Domain-Aware Machine Learning for Accelerating MILP-Based Motion Planning with Temporal Logic and Chance Constraints","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.07515","snapshot_observed_at":"2026-08-01T08:19:20.308277Z","title":"InInternationalConferenceontheIntegrationofConstraint Programming, Artificial Intelligence, and Operations Re- search, 134–151","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-01T08:19:20.308277Z"},"links":{"cited_paper":"/paper/2508.07515","citing_paper":"/paper/2607.27389"},"observation_digest":"sha256:4ee1ae369dbe97109b3fd4948a6e8f82b1b5203889cd430c3d944437947da353","observation_id":"ff80655f-07de-4c17-9b0b-c2df770e7a7f","resolution":{"observed_at":"2026-08-01T08:19:20.308277Z","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":"2026-08-01T08:19:20.599332Z","title":"InForty-first International Conference on Machine Learning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-01T08:19:20.599332Z"},"links":{"citing_paper":"/paper/2607.27389"},"observation_digest":"sha256:058e50d4201925012c01fbc768a8b17f99362e9e6f4b265f4f10f28ed202a2c0","observation_id":"87da2600-03e3-4c8f-9f5a-42b2140032ce","resolution":{"observed_at":"2026-08-01T08:19:20.599332Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.13131","last_updated":"2025-06-16T06:37:18Z","snapshot_observed_at":"2026-08-07T04:21:43.190472Z","submitted_at":"2025-06-16T06:37:18Z","title":"AlphaEvolve: A coding agent for scientific and algorithmic discovery","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.13131","snapshot_observed_at":"2026-08-01T08:19:20.791111Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-01T08:19:20.791111Z"},"links":{"cited_paper":"/paper/2506.13131","citing_paper":"/paper/2607.27389"},"observation_digest":"sha256:467f83b44ef41b7ca12a9d0fcb77db0ea80bceed185de74c37ed98363f40c432","observation_id":"7b12320a-a88f-44ca-8bb8-c682cb66f6fc","resolution":{"observed_at":"2026-08-01T08:19:20.791111Z","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":"2026-08-01T08:19:20.890592Z","title":"Sun,J.;Zhang,L.;Chen,G.;Xu,P.;Zhang,K.;andYang,Y","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-01T08:19:20.890592Z"},"links":{"citing_paper":"/paper/2607.27389"},"observation_digest":"sha256:b92e5e9766c32059a578d5e9e8b3ce424864c2c31e7ada827f5c88549a3f21e7","observation_id":"55e08ec9-198b-45a3-8d2b-c61907b0248c","resolution":{"observed_at":"2026-08-01T08:19:20.890592Z","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":"2026-08-01T08:19:20.147565Z","title":"anthropic.com/news/claude-opus-4-8","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T08:19:20.147565Z"},"links":{"citing_paper":"/paper/2607.27389"},"observation_digest":"sha256:1a7adfc70a666a41ad83ce9ce1546dd962dca272788fe93a7a6469c3fd4d1ff6","observation_id":"a5465cc0-2d50-45f3-b013-bad375208658","resolution":{"observed_at":"2026-08-01T08:19:20.147565Z","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":"2026-08-01T08:19:20.470938Z","title":"Gemini3.1Pro","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-01T08:19:20.470938Z"},"links":{"citing_paper":"/paper/2607.27389"},"observation_digest":"sha256:1d190d862ec47f812761203dda482958571410e56e496c305c6fe5bf573fe173","observation_id":"5dd5b8d3-a212-4bd4-b15b-e1921e98222a","resolution":{"observed_at":"2026-08-01T08:19:20.470938Z","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":"2026-08-01T08:19:20.680711Z","title":"Version, 12(1987-2018):","venue":null,"work_id":null,"year":1987},"citing_paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","version":1},"reference_index":1987,"source":"pdf_text","source_observed_at":"2026-08-01T08:19:20.680711Z"},"links":{"citing_paper":"/paper/2607.27389"},"observation_digest":"sha256:dd23aa14c39fc2fb8dc772fad3029d929987d5e6afc5b0e5998aab42a2dd2ae6","observation_id":"4bfd7d54-760a-4b7c-837f-f3577d33526e","resolution":{"observed_at":"2026-08-01T08:19:20.680711Z","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":"2026-08-01T08:19:20.375188Z","title":"Chen,T.;Zhang,W.;Jingyang,Z.;Chang,S.;Liu,S.;Amini, L.;andWang,Z.2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-01T08:19:20.375188Z"},"links":{"citing_paper":"/paper/2607.27389"},"observation_digest":"sha256:9bee7eef2679faa06a8dabdcca85e05b2fa81558c8485478223ad5300f9f1d89","observation_id":"735e0c8c-32b2-4f41-84a4-0417af0f821e","resolution":{"observed_at":"2026-08-01T08:19:20.375188Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.00039","last_updated":"2023-02-28T19:23:20Z","snapshot_observed_at":"2026-08-02T18:56:14.654043Z","submitted_at":"2023-02-28T19:23:20Z","title":"M-L2O: Towards Generalizable Learning-to-Optimize by Test-Time Fast Self-Adaptation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.00039","snapshot_observed_at":"2026-08-01T08:19:20.989431Z","title":"Ye, H.; Wang, J.; Cao, Z.; Berto, F.; Hua, C.; Kim, H.; Park, J.; and Song, G","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-01T08:19:20.989431Z"},"links":{"cited_paper":"/paper/2303.00039","citing_paper":"/paper/2607.27389"},"observation_digest":"sha256:e9f4c5b4b529a93ed6498632adad50ebe7d72a0527b946d514bb2c06b76a682c","observation_id":"07e70c77-9a1f-44dc-9a8f-0db102a4bdab","resolution":{"observed_at":"2026-08-01T08:19:20.989431Z","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":"2026-08-01T08:19:20.212537Z","title":"InECAI 2024, 2418–2425","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-01T08:19:20.212537Z"},"links":{"citing_paper":"/paper/2607.27389"},"observation_digest":"sha256:32d12a6fff9486e6ad9d678131f6c11df88974128d5ab7da0cb6c007d6924edb","observation_id":"bf98b73f-7bf8-4e5f-ad25-b5b4daf27153","resolution":{"observed_at":"2026-08-01T08:19:20.212537Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.14434","last_updated":"2026-05-10T22:59:47Z","snapshot_observed_at":"2026-07-06T20:54:50.337775Z","submitted_at":"2025-03-18T17:11:24Z","title":"LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.14434","snapshot_observed_at":"2026-08-01T08:19:20.053963Z","title":"Andrychowicz, M.; Denil, M.; Gomez, S.; Hoffman, M","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-01T08:19:20.053963Z"},"links":{"cited_paper":"/paper/2503.14434","citing_paper":"/paper/2607.27389"},"observation_digest":"sha256:26b674ead5a477d7d6947d070685857cad5a737f6178735ea736a7651f78007f","observation_id":"68e48dd4-46d0-48fc-894b-0319a8384b65","resolution":{"observed_at":"2026-08-01T08:19:20.053963Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.27389","last_updated":"2026-07-29T18:52:44Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-08T05:45:46.164557Z","submitted_at":"2026-07-29T18:52:44Z","title":"FunL2O: LLM-Guided Feature Function Design for Learning to Optimize"},"reference_resolution":{"displayed":12,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":11,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":12},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2607.27389."}