{"as_of":"2026-08-07T04:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1eb5259ffdaf7926e73df3d17ee4499c23bc659221fb8278b985f800e2c2ead0","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T15:32:16.186676Z","state":"measured"},{"denominator":49,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":49,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-06T06:34:29.942622+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-12T05:11:47.211896Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-12T08:21:23.910379Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"cited_work":{"arxiv_id":"2507.15615","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.15615","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dhevo: Data-algorithm based heuristic evolution for generalizable milp solving","venue":null,"work_id":"0bc37b1c-35c9-4dce-ab94-4dbc52092708","year":2025},"citing_paper":{"arxiv_id":"2605.08756","last_updated":"2026-05-09T07:36:45Z","snapshot_observed_at":"2026-07-06T23:20:57.084438Z","submitted_at":"2026-05-09T07:36:45Z","title":"AHD Agent: Agentic Reinforcement Learning for Automatic Heuristic Design","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-12T01:14:39.643357Z"},"links":{"cited_paper":"/paper/2507.15615","citing_paper":"/paper/2605.08756"},"observation_digest":"sha256:a44fe88cdd800a33dee9a8fbba7ce7f5f706b9d784603c9e09493d27e763be9d","observation_id":"6617a185-5ffb-4ba0-87a9-65d9c9805553","resolution":{"observed_at":"2026-05-12T08:21:23.914336Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"cited_work":{"arxiv_id":"2507.15615","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2507.15615","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dhevo: Data-algorithm based heuristic evolution for generalizable milp solving","venue":null,"work_id":"0bc37b1c-35c9-4dce-ab94-4dbc52092708","year":2025},"citing_paper":{"arxiv_id":"2605.10401","last_updated":"2026-05-11T11:41:54Z","snapshot_observed_at":"2026-07-06T23:22:23.287792Z","submitted_at":"2026-05-11T11:41:54Z","title":"LLM4Branch: Large Language Model for Discovering Efficient Branching Policies of Integer Programs","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-05-12T05:11:47.211896Z"},"links":{"cited_paper":"/paper/2507.15615","citing_paper":"/paper/2605.10401"},"observation_digest":"sha256:7923dc02338fff3bd86361db8444002baf74322cf6508d4cefc02bdf1f015c6c","observation_id":"2d71a172-cf0f-4496-8cc6-599bf1732890","resolution":{"observed_at":"2026-05-12T05:31:25.503647Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2507.15615/citation-record","integrity":"/paper/2507.15615/integrity","json":"/paper/2507.15615/citation-record.json","paper":"/paper/2507.15615"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T15:32:17.110601Z","title":"A tsp-based milp model for medium-term planning of single-stage continuous multiproduct plants.Industrial & Engineering Chemistry Research, 47(20):7733–7743, 2008","venue":null,"work_id":"9864f5d3-6885-47aa-a66d-d08cef317229","year":2008},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:15.966259Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:cb77796aea364e5db564797408f6ae7f9c36cea9bcf394ecb19277f53372450b","observation_id":"f296dd94-6e7c-4927-9c3f-a6a7e82d02ab","resolution":{"observed_at":"2026-08-06T15:32:17.116514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:17.093279Z","title":"Biodiesel supply chain optimization modeled with geographical information system (gis) and mixed-integer linear programming (milp) for the northern great plains region","venue":null,"work_id":"698045c1-ec68-45dd-a472-47196a838897","year":2019},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:15.971468Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:c12981f064d1c1872779d6c9be8fd4c9a5e25c88ae3b90d6559a35dd78e37f29","observation_id":"8525ed85-e95b-41fc-ba19-3a24645108d2","resolution":{"observed_at":"2026-08-06T15:32:17.098559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:17.076263Z","title":"An milp model for optimization of a small-scale lng supply chain along a coastline","venue":null,"work_id":"1cf47d55-63be-4d0b-a895-2c14b2b63208","year":2015},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:15.975998Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:d9aa020d4854ef7ec68d5e853aeb9fc8480f4ca982d05331e96d5c818ba5e66e","observation_id":"d278cdcc-b6ae-4192-a0f7-ea4a8e3585c6","resolution":{"observed_at":"2026-08-06T15:32:17.081916Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:17.056549Z","title":"Accelerating an fpga-based sat solver by software and hardware co-design","venue":null,"work_id":"420c1176-b85b-4998-96fb-b278919ab538","year":2019},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:15.980723Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:5b75c6935934cefa5ddd6a84d1347c7e98f90c9c45e626f24083fb8acd340c86","observation_id":"6fa5db7e-7db3-496b-a572-d521e037ab67","resolution":{"observed_at":"2026-08-06T15:32:17.062645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:17.039861Z","title":"Constraint improvements for milp-based hardware synthesis","venue":null,"work_id":"9e062ca5-d95d-4a22-b070-70f8f1d7b251","year":1991},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:15.985541Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:be313e6d37d62064a33397c32f3f052b4105b5135fcb621e65204f4fbd787f38","observation_id":"99d34c64-e6cf-4ae3-b526-93dbcfd7d5dd","resolution":{"observed_at":"2026-08-06T15:32:17.044591Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:17.024797Z","title":"Integrated production and outbound distribution scheduling: review and extensions","venue":null,"work_id":"acf9fe0d-20b7-4580-b96d-f152ed6c5d28","year":2010},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:15.991144Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:08729748f3b6703c795232c8c0e602a78fd2abf29ff9519095ecaec09bd8f5c5","observation_id":"2b082efb-94ba-49f0-b3fc-7dcac5c8d31c","resolution":{"observed_at":"2026-08-06T15:32:17.029413Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:17.009662Z","title":"An milp for scheduling problems in an fms with one vehicle","venue":null,"work_id":"c3fd98c2-e7b3-4a8c-9dff-f69546664e0b","year":2009},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:15.997103Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:24f3970fe39a01293d2b9260f449dd07a0d7bf5fd9ad6bf52329640bf64a86eb","observation_id":"7513fca8-e70e-41a9-bfbb-a9d56aa90b3f","resolution":{"observed_at":"2026-08-06T15:32:17.014455Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.994816Z","title":"Optimization of the power output scheduling of a renewables-based hybrid power station using milp approach: The case of tilos island","venue":null,"work_id":"c0999800-4237-4ed8-b6f1-bf5e272657c3","year":2024},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.002348Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:8a259d047e3d08d75b586c101a39bfe9ffd9e0470244bcc8b41efb322a3526c0","observation_id":"aa922624-994a-489f-a98f-b83bf2b860a8","resolution":{"observed_at":"2026-08-06T15:32:16.999586Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.979911Z","title":"A practical mixed integer linear programming based approach for unit commitment","venue":null,"work_id":"ac5793b9-745c-43fa-b8e4-a58fd2ce0c07","year":2004},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.006694Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:ce4b165798fab00c7515537a5101d89603e93f69f84e47727d4085686d6d79ec","observation_id":"2c223a19-6a63-4131-baa5-31e78dc4471a","resolution":{"observed_at":"2026-08-06T15:32:16.984500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.964583Z","title":"Optimal sizing and energy management of a microgrid: A joint milp approach for minimization of energy cost and carbon emission","venue":null,"work_id":"8c41533f-bbe0-41e4-9c65-7859aef723c6","year":2024},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.011232Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:637bbb8d7e3862e77b1382a87acbd1e0aac5e2aeb9c283b683ca1e89bb6bb3f8","observation_id":"7430e0b4-845d-47fe-a89b-3eb97e24d1af","resolution":{"observed_at":"2026-08-06T15:32:16.969188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.948760Z","title":"Efficient expansion planning of modern multi-energy distribution networks with electric vehicle charging stations: A stochastic milp model","venue":null,"work_id":"caf668a0-00b9-4d0c-b3a3-6542bb5f0e48","year":2024},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.016205Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:7ca5fec9200b08b492729350e68bc3648c85761288415a08ec4a07d0ef6bd319","observation_id":"9fc9691c-601b-4b6d-bdd1-13f5d69a6660","resolution":{"observed_at":"2026-08-06T15:32:16.953892Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.926990Z","title":"Worst-case analysis of two travelling salesman heuristics","venue":null,"work_id":"66788458-a617-4989-bdbf-b9f095c83d2f","year":1984},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.021278Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:25fc42b2a9f2846a8984ecc41f187e51abc350d078d47455be6a05411383d946","observation_id":"408df426-4104-47d8-b6c3-67df61a90773","resolution":{"observed_at":"2026-08-06T15:32:16.933383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.910377Z","title":"Pivot and shift—a mixed integer programming heuristic","venue":null,"work_id":"ac162431-30e2-4080-b086-1b5cbbcf98c7","year":2004},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.025750Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:ad7c0aba228a9a30a42b350708d7def60bfb273968b9495e73c4b41816602e17","observation_id":"700cb8d3-93ed-4f48-b4ac-8c0ca7a954f2","resolution":{"observed_at":"2026-08-06T15:32:16.915139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.895735Z","title":"Primal heuristics for mixed integer programs","venue":null,"work_id":"3aeb7067-ff31-45f7-80c3-f86560e5a03b","year":2006},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.029828Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:1ae90795b0133e87769ffd8af5721274b6467f1b0b575d3c5006200cd5bac92e","observation_id":"9517d2d9-2f9b-4758-9e15-d187366655a3","resolution":{"observed_at":"2026-08-06T15:32:16.900100Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.880250Z","title":"Zi round, a mip rounding heuristic","venue":null,"work_id":"d8c0d963-a9aa-4ca1-9d74-df782819c912","year":2010},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.033784Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:00d80e7954b86f8bae9e4a277525a279ff2fcaccdbc2a2b17ce004fd912948fd","observation_id":"96007d57-ea11-4d71-aae7-4c593c5a685b","resolution":{"observed_at":"2026-08-06T15:32:16.884745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.864830Z","title":"Conflict-driven heuristics for mixed integer programming","venue":null,"work_id":"9ed4668d-734c-473a-9385-fcc97f46479f","year":2021},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.038243Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:f1b368fdbffcc313feba117d65e82dda2b18fbb1b057d110b5f81a4c6e2ca62c","observation_id":"396d248c-e5cc-4e49-bb72-bd9fb0605c23","resolution":{"observed_at":"2026-08-06T15:32:16.869396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.848877Z","title":"The scip optimization suite 5.0","venue":null,"work_id":"be4f2896-9095-45ae-ab0e-3e9e4fa12c6b","year":2017},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.042724Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:39b318f12038d7cd741bef2ba904d4ca36f21240f5f07650e2c5ab37948cd952","observation_id":"3663539a-cada-41a8-999a-e56a0a61178d","resolution":{"observed_at":"2026-08-06T15:32:16.854390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.046757Z","title":"Gurobi Optimizer Reference Manual, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.046757Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:a2888b32b10e339f281d56a2d05e70e05861ebedcca58e347f358505bf30d91b","observation_id":"8375cef7-4608-44da-aa9f-7c914d7a77e0","resolution":{"observed_at":"2026-08-06T15:32:16.046757Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.03409","last_updated":"2024-04-15T07:50:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-07T00:07:15Z","title":"Large Language Models as Optimizers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.03409","snapshot_observed_at":"2026-08-06T15:32:16.051058Z","title":"Large language models as optimizers","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.051058Z"},"links":{"cited_paper":"/paper/2309.03409","citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:8de87c3d8197a3c6cfc0d1d755c7441402693f87b3a27dc68413cadcdbb33d75","observation_id":"1a69a72e-50f3-44c6-a619-6ebca5502b95","resolution":{"observed_at":"2026-08-06T15:32:16.051058Z","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":"2026-08-06T15:32:16.055552Z","title":"Language model crossover: Variation through few-shot prompting","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.055552Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:b2285a8d60fca85d6c5e6e4332a78e283bdd8291a8e77c2e05ace69f49aa1ea8","observation_id":"d8aa186e-f36f-47f8-824a-e4dd4ac8f205","resolution":{"observed_at":"2026-08-06T15:32:16.055552Z","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":"2026-08-06T15:32:16.810646Z","title":"Evoprompting: Language models for code-level neural architecture search","venue":null,"work_id":"76d77e2a-8f3d-4b66-ac8b-f082f9602933","year":2023},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.059608Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:e8727a3efab6c86011bf5093894677cb2799b6bbb088137c2919c7ad70ba5a2c","observation_id":"9cb68ff4-01d9-493e-a864-634771afa60b","resolution":{"observed_at":"2026-08-06T15:32:16.815851Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.063845Z","title":"Mathematical discoveries from program search with large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.063845Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:a1a0c03ff4a0e9649ac5f5ef5ffdf80833474a0bb6fdd907e7596d0ea5f622d4","observation_id":"bae242d6-5c5f-4a6b-bad0-715094bcb3e0","resolution":{"observed_at":"2026-08-06T15:32:16.063845Z","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":"2026-08-06T15:32:16.068507Z","title":"A systematic survey on large language models for algorithm design","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.068507Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:abbef64f2208f49ff7b479a7dc7d0992126355a8d7609f337aa8e8472beeec7f","observation_id":"16026da1-2f88-4ff3-aefd-eb3e5d738dd3","resolution":{"observed_at":"2026-08-06T15:32:16.068507Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.02051","last_updated":"2024-06-01T16:48:37Z","snapshot_observed_at":"2026-08-06T00:20:28.197923Z","submitted_at":"2024-01-04T04:11:59Z","title":"Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02051","snapshot_observed_at":"2026-08-06T15:32:16.072771Z","title":"Evolution of heuristics: Towards efficient automatic algorithm design using large language model","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.072771Z"},"links":{"cited_paper":"/paper/2401.02051","citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:7bfcd1fdf10965101b561903ed07ada8664b695b8acc5e704abde3ff62a27454","observation_id":"1e9ba9f0-4d97-483d-8ed2-d36a2b423ff8","resolution":{"observed_at":"2026-08-06T15:32:16.072771Z","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":"2026-08-06T15:32:16.783621Z","title":"Llm4solver: Large language model for efficient algorithm design of combinatorial optimization solver","venue":null,"work_id":"1d5360e5-4a7b-4ce2-b76d-bbba0e1efd99","year":2024},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.077429Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:63e4a8233f8fa4dbda4a7a5910ad3dc0e244bb34fbe956604697ea6e35aa3294","observation_id":"3ee763af-7a45-4e03-9a2c-a312602447b2","resolution":{"observed_at":"2026-08-06T15:32:16.788813Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.767390Z","title":"Self-paced cur- riculum learning","venue":null,"work_id":"ecb080d5-4adb-40fd-ac3b-c09c402cd2b0","year":2015},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.081853Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:8af193c4b9204e255062f897f1f1a3f3ab0bfca74801010c51bf3c7c67ed2b44","observation_id":"df65d598-ed4d-443a-8cb5-fe6e2f0e5247","resolution":{"observed_at":"2026-08-06T15:32:16.772623Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1803.00676","last_updated":"2018-03-02T01:07:49Z","snapshot_observed_at":"2026-07-30T13:13:21.420845Z","submitted_at":"2018-03-02T01:07:49Z","title":"Meta-Learning for Semi-Supervised Few-Shot Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1803.00676","snapshot_observed_at":"2026-08-06T15:32:16.086278Z","title":"Meta-learning for semi-supervised few-shot classification","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.086278Z"},"links":{"cited_paper":"/paper/1803.00676","citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:bd376e7fb076f7bb1a484f005884202a4acee741fd2a294fdb4c0ea7221a379d","observation_id":"4ed69d21-37cb-4912-a5e5-a377767e7e32","resolution":{"observed_at":"2026-08-06T15:32:16.086278Z","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":"2026-08-06T15:32:16.751169Z","title":"Learning to sample hard instances for graph algorithms","venue":null,"work_id":"c873d928-efc3-4afa-9c6c-3459f7144011","year":2019},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.090850Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:ea9c62a52064948ba66ceaf2a3f4cd667718baaaefe49ae27cb2120f90bb49c1","observation_id":"744516e5-75dc-4537-9b91-2758a912336a","resolution":{"observed_at":"2026-08-06T15:32:16.755774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.734734Z","title":"Curriculum learning","venue":null,"work_id":"ef3e13f5-ed41-47fb-b6f5-6e6cf7b9ed9b","year":2009},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.095140Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:22b5ad7b3e2189db36e44ce94738de299171f9fb90ac84d0e7d340bf6acce3ee","observation_id":"8c909714-be18-4613-9175-3b6d51c13e11","resolution":{"observed_at":"2026-08-06T15:32:16.739490Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.719160Z","title":"An automatic method for solving discrete programming problems","venue":null,"work_id":"acc9db35-c2ff-45af-baf9-267a53abeaab","year":1958},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.099498Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:c8ce5ba22d437b39d572cef01014f812e04d4d3f7eacf3e81c9ad3f8913eed31","observation_id":"f55b6b50-4b53-48df-a00e-6bb332b4c4e0","resolution":{"observed_at":"2026-08-06T15:32:16.723870Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.703196Z","title":"Handbook of evolutionary computa- tion","venue":null,"work_id":"1256a5d5-cd02-45be-9651-5bc3d74a2911","year":1997},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.103648Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:bbf28c44cfcfbf4cd6e8c144c55380d62a48e53f81f754602dcf194510ff22a0","observation_id":"9132b463-4127-4bb8-a73c-ec2d6b51d0fd","resolution":{"observed_at":"2026-08-06T15:32:16.707955Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.686060Z","title":"Evolutionary learning: Advances in theories and algorithms","venue":null,"work_id":"250f8815-8d85-4eaf-88ab-f52d365c2888","year":2019},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.108350Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:a617bb8f45089b19b4284f452e07d6dc3d8db908770e9b50fb06ace4388ec994","observation_id":"ffc33594-fd61-46ef-8c32-37b8a0e0e5b9","resolution":{"observed_at":"2026-08-06T15:32:16.691624Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.112996Z","title":"From evolutionary computation to the evolution of things","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.112996Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:2584c68370a98d77cb715b8d2f7744bc65ec2fbad8d06f68fb396074acedd682","observation_id":"ad0ce0cb-a6bf-43fe-92be-e7b036e56113","resolution":{"observed_at":"2026-08-06T15:32:16.112996Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.06435","last_updated":"2024-10-17T01:10:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-07-12T20:01:52Z","title":"A Comprehensive Overview of Large Language Models","version":10},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.06435","snapshot_observed_at":"2026-08-06T15:32:16.117603Z","title":"A comprehensive overview of large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.117603Z"},"links":{"cited_paper":"/paper/2307.06435","citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:3182701485110a34f58c60b525d080669ee11ae99317861639958683505b6d6a","observation_id":"510fb190-0e27-4425-a7bd-db38ec496c5e","resolution":{"observed_at":"2026-08-06T15:32:16.117603Z","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":"2026-08-06T15:32:16.643927Z","title":"Evolutionary com- putation in the era of large language model: Survey and roadmap","venue":null,"work_id":"b92debc3-2df0-4ca3-9ec0-f790a59bb215","year":2024},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.126996Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:da60b9bfc0b8f722ae8dcddc8915971cd86c2be40d9e6ef3f53f33ce79a1d6b2","observation_id":"6cbdb323-00fb-4a7a-84d0-f6be3c99812b","resolution":{"observed_at":"2026-08-06T15:32:16.649266Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1706.10239","last_updated":"2017-11-28T02:40:04Z","snapshot_observed_at":"2026-07-06T05:49:15.272401Z","submitted_at":"2017-06-30T15:30:21Z","title":"Towards Understanding Generalization of Deep Learning: Perspective of Loss Landscapes","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.10239","snapshot_observed_at":"2026-08-06T15:32:16.132794Z","title":"Towards understanding generalization of deep learning: Perspec- tive of loss landscapes","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.132794Z"},"links":{"cited_paper":"/paper/1706.10239","citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:ddea911c1aaabe72325d674169e65526ba39e9bfc10de515fde766613822db8d","observation_id":"1bcd6e7a-8448-4bf9-8b10-40797317d917","resolution":{"observed_at":"2026-08-06T15:32:16.132794Z","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":"2026-08-06T15:32:16.627363Z","title":"How does loss function affect generalization performance of deep learning? application to human age estimation","venue":null,"work_id":"108affcf-e2ab-46fb-ac21-3c4f49c7473d","year":2021},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.138782Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:7d071c9700e74f2ba94cf0219ed453a2d925566d30d09de635ea2812e8a558f3","observation_id":"334418a7-5a74-4b65-b08b-a662a30eb5c0","resolution":{"observed_at":"2026-08-06T15:32:16.632355Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02178","last_updated":"2019-12-04T18:58:26Z","snapshot_observed_at":"2026-07-06T08:42:06.688732Z","submitted_at":"2019-12-04T18:58:26Z","title":"Fantastic Generalization Measures and Where to Find Them","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02178","snapshot_observed_at":"2026-08-06T15:32:16.144803Z","title":"Fantastic generalization measures and where to find them","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.144803Z"},"links":{"cited_paper":"/paper/1912.02178","citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:4d4b7cbd72be5e3194fb3bb90e051cfe926872e5c97584d9c1de8ffd6f3c00b2","observation_id":"45ed7778-fedb-45a1-9e6f-f15c81dd3504","resolution":{"observed_at":"2026-08-06T15:32:16.144803Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.19118","last_updated":"2024-10-09T02:41:21Z","snapshot_observed_at":"2026-08-01T16:20:31.337598Z","submitted_at":"2023-05-30T15:25:45Z","title":"Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.19118","snapshot_observed_at":"2026-08-06T15:32:16.149903Z","title":"Encouraging divergent thinking in large language models through multi- agent debate","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.149903Z"},"links":{"cited_paper":"/paper/2305.19118","citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:ab8a52f9038cfa1956f4c86882fb0fba04ecfc604fd10c1a4ef8c8f268467f81","observation_id":"da7e3b64-564a-4165-a412-93f5151de1a0","resolution":{"observed_at":"2026-08-06T15:32:16.149903Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.07201","last_updated":"2023-08-14T15:13:04Z","snapshot_observed_at":"2026-08-02T01:34:38.978920Z","submitted_at":"2023-08-14T15:13:04Z","title":"ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.07201","snapshot_observed_at":"2026-08-06T15:32:16.154504Z","title":"Chateval: Towards better llm-based evaluators through multi-agent debate","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.154504Z"},"links":{"cited_paper":"/paper/2308.07201","citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:30f221631800576f2fce6d0cd0b70b0461fc808dabe9c2f3a4c7152e76cfc840","observation_id":"9b37f6d1-730d-4f09-9d8e-f41b96c54a9d","resolution":{"observed_at":"2026-08-06T15:32:16.154504Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.10762","last_updated":"2025-04-15T02:44:55Z","snapshot_observed_at":"2026-07-06T19:33:12.610676Z","submitted_at":"2024-10-14T17:40:40Z","title":"AFlow: Automating Agentic Workflow Generation","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.10762","snapshot_observed_at":"2026-08-06T15:32:16.159572Z","title":"Aflow: Automating agentic workflow generation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.159572Z"},"links":{"cited_paper":"/paper/2410.10762","citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:0ebcd2f2bd7b96eb5feaa7d9d15432d4aa7362556c03448cecd1ceb6cc4ed1e2","observation_id":"a5693d01-33ea-44ed-82dc-0293fc60cdc7","resolution":{"observed_at":"2026-08-06T15:32:16.159572Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.11776","last_updated":"2024-06-17T17:33:09Z","snapshot_observed_at":"2026-07-06T18:32:23.999019Z","submitted_at":"2024-06-17T17:33:09Z","title":"Improving Multi-Agent Debate with Sparse Communication Topology","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.11776","snapshot_observed_at":"2026-08-06T15:32:16.164452Z","title":"Improving multi-agent debate with sparse communication topology","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.164452Z"},"links":{"cited_paper":"/paper/2406.11776","citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:2d3b0ef2e8a80b55e1779fa405be01fda3315d071978e0e40f87df838f9d45f1","observation_id":"f10aff24-71f5-41f4-973d-61fa9c361324","resolution":{"observed_at":"2026-08-06T15:32:16.164452Z","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":"2026-08-06T15:32:16.611590Z","title":"Constraint integer programming","venue":null,"work_id":"ab2e78b6-5d56-4646-bc28-00550665dce1","year":2007},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.168913Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:b870ea3caff818044f6c2a5f4b0dba1bf505b30fd8eb47444ed8a082ba103fcb","observation_id":"59aa7d7a-403c-4a99-a3e6-a230a7b6bf74","resolution":{"observed_at":"2026-08-06T15:32:16.616771Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.593979Z","title":"Learning to dive in branch and bound","venue":null,"work_id":"03e61a89-303e-414c-96fa-02b019e643af","year":2023},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.173316Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:5aa6f05a4ab534467eecf0f47af522d7d87804debb46972bb805da0344ae040f","observation_id":"b2953374-278a-44ae-9152-86bbbb59f510","resolution":{"observed_at":"2026-08-06T15:32:16.598440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.660102Z","title":"Understanding the importance of evolutionary search in automated heuristic design with large language models","venue":null,"work_id":"e1235107-d0e4-4445-8024-6dd9d47b9c50","year":2024},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.177672Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:7666d82a52f380b36af0e44215a0263bd0aa695b6d6e322ec3f6f41eaed5d72a","observation_id":"ee38c73e-9197-468e-8d9b-79103b85b9f2","resolution":{"observed_at":"2026-08-06T15:32:16.664875Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.578209Z","title":"The underlying similarity of diversity measures used in evolutionary computation","venue":null,"work_id":"1f624063-f4ab-47cc-839c-f0994175e021","year":2003},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.182227Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:97d355067ec831d27c2765c496d437798fdb304937c5a98d17add795d84d7900","observation_id":"db6bf6ea-ec1b-4044-af53-66505fb900c9","resolution":{"observed_at":"2026-08-06T15:32:16.583430Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+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":"2026-08-06T15:32:16.560691Z","title":"and \"mayroundup","venue":null,"work_id":"dea76b03-c248-4d21-98a5-a2315519feb1","year":2021},"citing_paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T15:32:16.186676Z"},"links":{"citing_paper":"/paper/2507.15615"},"observation_digest":"sha256:80d55d7e84d9eb41594b23065a37c9008047970b88237db455e8b0f51c572b41","observation_id":"c54e1cf1-613a-4e9e-aaf4-df1d2cf50a77","resolution":{"observed_at":"2026-08-06T15:32:16.566351Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.15615","last_updated":"2025-07-21T13:40:19Z","latest_version":1,"primary_category":"cs.NE","snapshot_observed_at":"2026-08-06T15:25:07.337898Z","submitted_at":"2025-07-21T13:40:19Z","title":"DHEvo: Data-Algorithm Based Heuristic Evolution for Generalizable MILP Solving"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":15,"verified_exact":0,"verified_fuzzy":31},"total_outbound_references":47},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 2 inbound Pith citation observations for arXiv:2507.15615."}