{"as_of":"2026-08-15T07:48:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a2ff39f1e57eb6af0c30c82d0fac2956dfa3e32da7bfdc76b231ca8a553f1392","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":5,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":5,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":5,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":5,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T10:13:19.750837Z","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":"2026-07-04T09:59:44.448427Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.12822","last_updated":"2025-06-15T12:05:08Z","snapshot_observed_at":"2026-08-14T11:10:41.680292Z","submitted_at":"2025-06-15T12:05:08Z","title":"Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.12822","snapshot_observed_at":"2026-08-06T10:13:19.750837Z","title":"Enhancing rating- based reinforcement learning to effectively leverage feed- back from large vision-language models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.00398","last_updated":"2025-08-01T07:52:07Z","snapshot_observed_at":"2026-08-14T21:02:11.271647Z","submitted_at":"2025-08-01T07:52:07Z","title":"Occlusion-robust Stylization for Drawing-based 3D Animation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T10:13:19.750837Z"},"links":{"cited_paper":"/paper/2506.12822","citing_paper":"/paper/2508.00398"},"observation_digest":"sha256:e3ecd28a9d8007e81b18584dc264b69bba3003de72e0ce1ce0b8049f5ecc4f0f","observation_id":"8674e6ba-bf86-4071-b0a2-26340077f810","resolution":{"observed_at":"2026-08-06T10:13:19.750837Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.12822","last_updated":"2025-06-15T12:05:08Z","snapshot_observed_at":"2026-08-14T11:10:41.680292Z","submitted_at":"2025-06-15T12:05:08Z","title":"Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models","version":1},"cited_work":{"arxiv_id":"2506.12822","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.12822","snapshot_observed_at":"2026-07-04T09:59:44.448427Z","title":"Hao Peng, Yunjia Qi, Xiaozhi Wang, Zijun Yao, Bin Xu, Lei Hou, and Juanzi Li","venue":null,"work_id":"11577eb7-4459-4c05-a117-f82c0c80a920","year":2025},"citing_paper":{"arxiv_id":"2508.19652","last_updated":"2026-04-27T16:28:37Z","snapshot_observed_at":"2026-08-10T21:29:25.180272Z","submitted_at":"2025-08-27T08:01:03Z","title":"Self-Rewarding Vision-Language Model via Reasoning Decomposition","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-18T21:03:31.606674Z"},"links":{"cited_paper":"/paper/2506.12822","citing_paper":"/paper/2508.19652"},"observation_digest":"sha256:086342133c990b8166fd329553f0cd113ee4ff60ac19cde7b9f85f4cf31566d4","observation_id":"5b704c8c-fc4a-4656-9aa9-60b8aa3f330d","resolution":{"observed_at":"2026-05-18T21:06:50.849423Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.12822","last_updated":"2025-06-15T12:05:08Z","snapshot_observed_at":"2026-08-14T11:10:41.680292Z","submitted_at":"2025-06-15T12:05:08Z","title":"Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.12822","snapshot_observed_at":"2026-07-13T16:10:12.689957Z","title":"M., Lee, Y ., Lee, D., Kim, S., Kim, M","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.28730","last_updated":"2026-05-26T17:56:39Z","snapshot_observed_at":"2026-08-14T18:54:01.033350Z","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":33,"source":"pdf_text","source_observed_at":"2026-07-13T16:10:12.689957Z"},"links":{"cited_paper":"/paper/2506.12822","citing_paper":"/paper/2603.28730"},"observation_digest":"sha256:8dca6987ff476486b0c0b3814c435c82496df16987118ebfb5a4164637dc419c","observation_id":"0e9d3458-f541-44cc-bb1f-2ae14dbf8d0c","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":"2506.12822","last_updated":"2025-06-15T12:05:08Z","snapshot_observed_at":"2026-08-14T11:10:41.680292Z","submitted_at":"2025-06-15T12:05:08Z","title":"Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models","version":1},"cited_work":{"arxiv_id":"2506.12822","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.12822","snapshot_observed_at":"2026-07-04T09:59:44.448427Z","title":"Hao Peng, Yunjia Qi, Xiaozhi Wang, Zijun Yao, Bin Xu, Lei Hou, and Juanzi Li","venue":null,"work_id":"11577eb7-4459-4c05-a117-f82c0c80a920","year":2025},"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":51,"source":"pdf_text","source_observed_at":"2026-06-26T09:20:35.062060Z"},"links":{"cited_paper":"/paper/2506.12822","citing_paper":"/paper/2606.23640"},"observation_digest":"sha256:91180bfe14ceae452306aba2c0cd441506b44a6700e261db84e871b25cb274c7","observation_id":"97bc0aea-a88f-49e0-9bdf-0e44fc281504","resolution":{"observed_at":"2026-07-04T09:59:44.450686Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.12822","last_updated":"2025-06-15T12:05:08Z","snapshot_observed_at":"2026-08-14T11:10:41.680292Z","submitted_at":"2025-06-15T12:05:08Z","title":"Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.12822","snapshot_observed_at":"2026-08-04T00:49:36.677298Z","title":"arXiv preprint arXiv:2506.12822 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.00315","last_updated":"2026-07-31T22:00:35Z","snapshot_observed_at":"2026-08-07T01:30:24.546411Z","submitted_at":"2026-07-31T22:00:35Z","title":"Towards General Language-Conditioned Latent Safety Filters","version":1},"reference_index":213,"source":"arxiv_source","source_observed_at":"2026-08-04T00:49:36.677298Z"},"links":{"cited_paper":"/paper/2506.12822","citing_paper":"/paper/2608.00315"},"observation_digest":"sha256:47f91d54f8670a47266eab06738f44fc3efa7033a314fc113dc5ed3b56762cf2","observation_id":"38e1e6d2-6dc9-4c28-bcfd-3ae2414ab0c7","resolution":{"observed_at":"2026-08-04T00:49:36.677298Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.12822/citation-record","integrity":"/paper/2506.12822/integrity","json":"/paper/2506.12822/citation-record.json","paper":"/paper/2506.12822"},"outbound":[],"paper":{"arxiv_id":"2506.12822","last_updated":"2025-06-15T12:05:08Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-14T11:10:41.680292Z","submitted_at":"2025-06-15T12:05:08Z","title":"Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models"},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2506.12822."}