{"as_of":"2026-08-06T14:38:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3197c96d8175407120ba3cb43d677858d2f2db7da6c3b7a134e3c5b77c0498aa","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":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":"2026-08-06T06:34:29.942622+00:00","state":"measured"},{"denominator":6,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":6,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T12:24:02.379856Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":1,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.04764","last_updated":"2024-02-07T11:27:45Z","snapshot_observed_at":"2026-08-05T18:35:49.744409Z","submitted_at":"2024-02-07T11:27:45Z","title":"Code as Reward: Empowering Reinforcement Learning with VLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.04764","snapshot_observed_at":"2026-08-05T12:24:02.379856Z","title":"Code as reward: Empowering reinforcement learning with vlms","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01684","last_updated":"2025-09-01T18:04:10Z","snapshot_observed_at":"2026-08-05T12:24:00.598679Z","submitted_at":"2025-09-01T18:04:10Z","title":"Reinforcement Learning for Machine Learning Engineering Agents","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-05T12:24:02.379856Z"},"links":{"cited_paper":"/paper/2402.04764","citing_paper":"/paper/2509.01684"},"observation_digest":"sha256:c71ab02371a1468036cd62d9c93bc58ebaaf32bdc5a5a0e7eacb9120fea83b76","observation_id":"5ef0f259-b734-480b-83f0-32aa46ffb8de","resolution":{"observed_at":"2026-08-05T12:24:02.379856Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04764","last_updated":"2024-02-07T11:27:45Z","snapshot_observed_at":"2026-08-05T18:35:49.744409Z","submitted_at":"2024-02-07T11:27:45Z","title":"Code as Reward: Empowering Reinforcement Learning with VLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.04764","snapshot_observed_at":"2026-07-13T16:10:12.689957Z","title":"N., Klissarov, M., Precup, D., Yang, S., and Anand, A","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2603.28730","last_updated":"2026-05-26T17:56:39Z","snapshot_observed_at":"2026-08-06T10:59:04.687049Z","submitted_at":"2026-03-30T17:46:31Z","title":"SOLE-R1: Video-Language Reasoning as the Sole Reward for On-Robot Reinforcement Learning","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-07-13T16:10:12.689957Z"},"links":{"cited_paper":"/paper/2402.04764","citing_paper":"/paper/2603.28730"},"observation_digest":"sha256:01d9b3afe29c11f9bfe879a7f0baca6ef04117a4fb4885400a63c78eb6e46c46","observation_id":"8e582b40-d12d-421b-8bb9-ac4cc3893c17","resolution":{"observed_at":"2026-07-13T16:10:12.689957Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04764","last_updated":"2024-02-07T11:27:45Z","snapshot_observed_at":"2026-08-05T18:35:49.744409Z","submitted_at":"2024-02-07T11:27:45Z","title":"Code as Reward: Empowering Reinforcement Learning with VLMs","version":1},"cited_work":{"arxiv_id":"2402.04764","doi":"10.48550/arxiv.2402.04764","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.04764","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Code as reward: Empowering reinforcement learning with vlms.arXiv preprint arXiv:2402.04764, 2024","venue":"arXiv (Cornell University)","work_id":"5004569e-47ae-4516-a3ec-ddccfc79e2b1","year":2024},"citing_paper":{"arxiv_id":"2606.15932","last_updated":"2026-06-16T15:28:03Z","snapshot_observed_at":"2026-07-06T23:52:37.922109Z","submitted_at":"2026-06-14T17:21:43Z","title":"Beyond NL2Code: A Structured Survey of Multimodal Code Intelligence","version":2},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-06-27T03:57:19.028507Z"},"links":{"cited_paper":"/paper/2402.04764","citing_paper":"/paper/2606.15932"},"observation_digest":"sha256:2d2781372a6a92d55741a06ab836b04cfae3d72c03fd48e4742ded42a40a0af6","observation_id":"71bedf21-e11d-47d6-abf7-0821cf3432ae","resolution":{"observed_at":"2026-07-03T17:38:44.083013Z","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":"2402.04764","last_updated":"2024-02-07T11:27:45Z","snapshot_observed_at":"2026-08-05T18:35:49.744409Z","submitted_at":"2024-02-07T11:27:45Z","title":"Code as Reward: Empowering Reinforcement Learning with VLMs","version":1},"cited_work":{"arxiv_id":"2402.04764","doi":"10.48550/arxiv.2402.04764","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.04764","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Code as reward: Empowering reinforcement learning with vlms.arXiv preprint arXiv:2402.04764, 2024","venue":"arXiv (Cornell University)","work_id":"5004569e-47ae-4516-a3ec-ddccfc79e2b1","year":2024},"citing_paper":{"arxiv_id":"2606.23640","last_updated":"2026-06-22T17:30:24Z","snapshot_observed_at":"2026-08-02T09:22:48.099895Z","submitted_at":"2026-06-22T17:30:24Z","title":"Learning Process Rewards via Success Visitation Matching for Efficient RL","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-06-26T09:20:35.062060Z"},"links":{"cited_paper":"/paper/2402.04764","citing_paper":"/paper/2606.23640"},"observation_digest":"sha256:68c4a5c75e469acc08dfb9f6628c4159c6755de29fd89ca37a6820819caa3dd3","observation_id":"6e83b4c1-aca7-4359-b8df-6992451c2968","resolution":{"observed_at":"2026-07-04T09:59:44.529491Z","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":"2402.04764","last_updated":"2024-02-07T11:27:45Z","snapshot_observed_at":"2026-08-05T18:35:49.744409Z","submitted_at":"2024-02-07T11:27:45Z","title":"Code as Reward: Empowering Reinforcement Learning with VLMs","version":1},"cited_work":{"arxiv_id":"2402.04764","doi":"10.48550/arxiv.2402.04764","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.04764","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Code as reward: Empowering reinforcement learning with vlms.arXiv preprint arXiv:2402.04764, 2024","venue":"arXiv (Cornell University)","work_id":"5004569e-47ae-4516-a3ec-ddccfc79e2b1","year":2024},"citing_paper":{"arxiv_id":"2606.32034","last_updated":"2026-06-30T17:58:23Z","snapshot_observed_at":"2026-07-07T00:05:41.920778Z","submitted_at":"2026-06-30T17:58:23Z","title":"QVal: Cheaply Evaluating Dense Supervision Signals for Long-Horizon LLM Agents","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-07-01T05:59:13.631078Z"},"links":{"cited_paper":"/paper/2402.04764","citing_paper":"/paper/2606.32034"},"observation_digest":"sha256:560e7e8f3c58a2e1f2590958c499264245bec2d2dba6019ce35eda14bd1876cd","observation_id":"d7d7e84b-5cbe-4546-be36-ed692400209a","resolution":{"observed_at":"2026-07-01T06:05:28.982000Z","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":"2402.04764","last_updated":"2024-02-07T11:27:45Z","snapshot_observed_at":"2026-08-05T18:35:49.744409Z","submitted_at":"2024-02-07T11:27:45Z","title":"Code as Reward: Empowering Reinforcement Learning with VLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.04764","snapshot_observed_at":"2026-08-04T19:45:35.270452Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.01851","last_updated":"2026-08-03T07:58:35Z","snapshot_observed_at":"2026-08-06T14:25:31.842966Z","submitted_at":"2026-08-03T07:58:35Z","title":"Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills","version":1},"reference_index":245,"source":"pdf_text","source_observed_at":"2026-08-04T19:45:35.270452Z"},"links":{"cited_paper":"/paper/2402.04764","citing_paper":"/paper/2608.01851"},"observation_digest":"sha256:f2b2da90ade9c5703a56603f8b58a9c7347afe0af92b5ea3e1f33b815bfac2e7","observation_id":"fd35c397-5693-4c02-86b2-8a0975e6cef4","resolution":{"observed_at":"2026-08-04T19:45:35.270452Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2402.04764/citation-record","integrity":"/paper/2402.04764/integrity","json":"/paper/2402.04764/citation-record.json","paper":"/paper/2402.04764"},"outbound":[],"paper":{"arxiv_id":"2402.04764","last_updated":"2024-02-07T11:27:45Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-05T18:35:49.744409Z","submitted_at":"2024-02-07T11:27:45Z","title":"Code as Reward: Empowering Reinforcement Learning with VLMs"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.04764."}