{"as_of":"2026-08-08T08:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:09892421dc3b0b28104a9e47f4588a8c1235e12aa23f740da963119fddbc2f29","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":10,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":10,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":10,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":10,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:26:01.278862Z","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":"2026-05-22T11:41:29.623621Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.06533","last_updated":"2025-02-10T14:56:25Z","snapshot_observed_at":"2026-07-06T20:34:02.031605Z","submitted_at":"2025-02-10T14:56:25Z","title":"Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning","version":1},"cited_work":{"arxiv_id":"2502.06533","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.06533","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Vassoyan, J., Beau, N., and Plaud, R","venue":null,"work_id":"085cbb78-7060-495d-85d0-e20cc389840b","year":2025},"citing_paper":{"arxiv_id":"2506.01939","last_updated":"2025-11-13T10:08:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-02T17:54:39Z","title":"Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-12T12:12:08.724844Z"},"links":{"cited_paper":"/paper/2502.06533","citing_paper":"/paper/2506.01939"},"observation_digest":"sha256:522690db162af0c1526e7a2a4698950b84c43588460d389fd28140d739159fd4","observation_id":"7674cb9a-22f7-4bfd-b688-55d4dd1f049a","resolution":{"observed_at":"2026-05-12T12:12:08.960644Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06533","last_updated":"2025-02-10T14:56:25Z","snapshot_observed_at":"2026-07-06T20:34:02.031605Z","submitted_at":"2025-02-10T14:56:25Z","title":"Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.06533","snapshot_observed_at":"2026-08-06T20:26:01.278862Z","title":"Vassoyan, N","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.03190","last_updated":"2025-07-11T16:55:14Z","snapshot_observed_at":"2026-08-06T20:13:48.510141Z","submitted_at":"2025-07-03T21:45:17Z","title":"Discovering Algorithms with Computational Language Processing","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T20:26:01.278862Z"},"links":{"cited_paper":"/paper/2502.06533","citing_paper":"/paper/2507.03190"},"observation_digest":"sha256:4b2d090f7ebc6aa7f367c1553a334f82bb1874b3dcadb55b0f37df88a99c7f7c","observation_id":"44b0d37e-a9a3-4184-9cb0-6a9915ea55e8","resolution":{"observed_at":"2026-08-06T20:26:01.278862Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06533","last_updated":"2025-02-10T14:56:25Z","snapshot_observed_at":"2026-07-06T20:34:02.031605Z","submitted_at":"2025-02-10T14:56:25Z","title":"Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.06533","snapshot_observed_at":"2026-08-06T19:18:38.761833Z","title":"Ignore the kl penalty! boosting exploration on critical tokens to enhance rl fine-tuning.arXiv preprint arXiv:2502.06533, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.06013","last_updated":"2025-07-08T14:17:07Z","snapshot_observed_at":"2026-08-07T22:57:58.555368Z","submitted_at":"2025-07-08T14:17:07Z","title":"CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T19:18:38.761833Z"},"links":{"cited_paper":"/paper/2502.06533","citing_paper":"/paper/2507.06013"},"observation_digest":"sha256:6f02f28b098e743c7b85c9e43c00706c44b712daf2b4ef17a35f24d763012618","observation_id":"6a1c392c-5e2c-4a08-a44c-b3dcb06b6e52","resolution":{"observed_at":"2026-08-06T19:18:38.761833Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06533","last_updated":"2025-02-10T14:56:25Z","snapshot_observed_at":"2026-07-06T20:34:02.031605Z","submitted_at":"2025-02-10T14:56:25Z","title":"Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning","version":1},"cited_work":{"arxiv_id":"2502.06533","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.06533","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Vassoyan, J., Beau, N., and Plaud, R","venue":null,"work_id":"085cbb78-7060-495d-85d0-e20cc389840b","year":2025},"citing_paper":{"arxiv_id":"2507.15778","last_updated":"2026-05-15T04:36:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-21T16:34:01Z","title":"Stabilizing Knowledge, Promoting Reasoning: Dual-Token Constraints for RLVR","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-05-21T23:20:45.685446Z"},"links":{"cited_paper":"/paper/2502.06533","citing_paper":"/paper/2507.15778"},"observation_digest":"sha256:4baf17ea2a7c455a2d9e47c351fe507c103b8ba426a3c3bff6ecb07ea47e1f56","observation_id":"1eab7712-b1b2-44ff-98fa-4910f7e8c24c","resolution":{"observed_at":"2026-05-21T23:24:26.241888Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06533","last_updated":"2025-02-10T14:56:25Z","snapshot_observed_at":"2026-07-06T20:34:02.031605Z","submitted_at":"2025-02-10T14:56:25Z","title":"Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.06533","snapshot_observed_at":"2026-08-04T12:41:43.057152Z","title":"Ignore the kl penalty! boosting exploration on critical tokens to enhance rl fine-tuning.arXiv preprint arXiv:2502.06533,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.02919","last_updated":"2026-05-29T16:16:27Z","snapshot_observed_at":"2026-08-07T08:42:12.238625Z","submitted_at":"2025-10-03T11:46:04Z","title":"Self-Reflective Generation at Test Time","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-04T12:41:43.057152Z"},"links":{"cited_paper":"/paper/2502.06533","citing_paper":"/paper/2510.02919"},"observation_digest":"sha256:92c0e60faa409bd31e42f0b3b785aedbb7130f7fb696565324172346e5e12d1b","observation_id":"376af9d9-ebde-4618-9197-5700c26f2387","resolution":{"observed_at":"2026-08-04T12:41:43.057152Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06533","last_updated":"2025-02-10T14:56:25Z","snapshot_observed_at":"2026-07-06T20:34:02.031605Z","submitted_at":"2025-02-10T14:56:25Z","title":"Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.06533","snapshot_observed_at":"2026-08-04T09:48:09.263325Z","title":"Ignore the kl penalty! boosting exploration on critical tokens to enhance rl fine-tuning","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.13554","last_updated":"2026-06-08T06:02:10Z","snapshot_observed_at":"2026-08-04T09:47:55.188440Z","submitted_at":"2025-10-15T13:49:51Z","title":"Attention Illuminates LLM Reasoning: The Preplan-and-Anchor Rhythm Enables Fine-Grained Policy Optimization","version":2},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-04T09:48:09.263325Z"},"links":{"cited_paper":"/paper/2502.06533","citing_paper":"/paper/2510.13554"},"observation_digest":"sha256:a7cdbac4543d523bbdd15c57ae69a27229b63c0a56a738e993ad4194c7b5e610","observation_id":"0b57fbfe-e87d-4eb8-bf7b-53889a8b50a3","resolution":{"observed_at":"2026-08-04T09:48:09.263325Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06533","last_updated":"2025-02-10T14:56:25Z","snapshot_observed_at":"2026-07-06T20:34:02.031605Z","submitted_at":"2025-02-10T14:56:25Z","title":"Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning","version":1},"cited_work":{"arxiv_id":"2502.06533","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.06533","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Vassoyan, J., Beau, N., and Plaud, R","venue":null,"work_id":"085cbb78-7060-495d-85d0-e20cc389840b","year":2025},"citing_paper":{"arxiv_id":"2601.10348","last_updated":"2026-05-21T06:29:24Z","snapshot_observed_at":"2026-08-03T01:57:39.427752Z","submitted_at":"2026-01-15T12:45:05Z","title":"Training-Trajectory-Aware Token Selection","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-22T11:41:21.275802Z"},"links":{"cited_paper":"/paper/2502.06533","citing_paper":"/paper/2601.10348"},"observation_digest":"sha256:5fd878f6aec8368c64b1f7d41f9c853c450a8d8ae8789a71089e9e311cfa1a43","observation_id":"68e48558-ca96-4c19-b535-78a32c01ac09","resolution":{"observed_at":"2026-05-22T11:41:29.626509Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06533","last_updated":"2025-02-10T14:56:25Z","snapshot_observed_at":"2026-07-06T20:34:02.031605Z","submitted_at":"2025-02-10T14:56:25Z","title":"Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.06533","snapshot_observed_at":"2026-07-13T14:33:35.834383Z","title":"Ignore the KL Penalty! Boosting Exploration on Critical T okens to Enhance RL Fine-T uning.CoRR, abs/2502.06533,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2604.01193","last_updated":"2026-06-24T22:44:36Z","snapshot_observed_at":"2026-08-02T16:28:38.685624Z","submitted_at":"2026-04-01T17:39:50Z","title":"Embarrassingly Simple Self-Distillation Improves Code Generation","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-13T14:33:35.834383Z"},"links":{"cited_paper":"/paper/2502.06533","citing_paper":"/paper/2604.01193"},"observation_digest":"sha256:a4666bf481bdb2f5ad7cae234629fe9e4f77f011e8adbbe960f6c444d93c7472","observation_id":"713e4f03-97af-4015-a2a7-e47620c85e4b","resolution":{"observed_at":"2026-07-13T14:33:35.834383Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06533","last_updated":"2025-02-10T14:56:25Z","snapshot_observed_at":"2026-07-06T20:34:02.031605Z","submitted_at":"2025-02-10T14:56:25Z","title":"Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning","version":1},"cited_work":{"arxiv_id":"2502.06533","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.06533","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Vassoyan, J., Beau, N., and Plaud, R","venue":null,"work_id":"085cbb78-7060-495d-85d0-e20cc389840b","year":2025},"citing_paper":{"arxiv_id":"2604.16158","last_updated":"2026-04-17T15:27:35Z","snapshot_observed_at":"2026-08-02T08:13:50.306987Z","submitted_at":"2026-04-17T15:27:35Z","title":"AtManRL: Towards Faithful Reasoning via Differentiable Attention Saliency","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T08:08:50.330857Z"},"links":{"cited_paper":"/paper/2502.06533","citing_paper":"/paper/2604.16158"},"observation_digest":"sha256:bfc5f24fb2c48c2825cc5994d9bde36d23728439612cf8d4bbdc7620ffb88191","observation_id":"9ccb437f-a756-4f65-9150-38507645632c","resolution":{"observed_at":"2026-05-10T08:22:37.709068Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.06533","last_updated":"2025-02-10T14:56:25Z","snapshot_observed_at":"2026-07-06T20:34:02.031605Z","submitted_at":"2025-02-10T14:56:25Z","title":"Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning","version":1},"cited_work":{"arxiv_id":"2502.06533","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2502.06533","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Vassoyan, J., Beau, N., and Plaud, R","venue":null,"work_id":"085cbb78-7060-495d-85d0-e20cc389840b","year":2025},"citing_paper":{"arxiv_id":"2605.08283","last_updated":"2026-05-08T07:38:35Z","snapshot_observed_at":"2026-08-03T16:22:22.745568Z","submitted_at":"2026-05-08T07:38:35Z","title":"HTPO: Towards Exploration-Exploitation Balanced Policy Optimization via Hierarchical Token-level Objective Control","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-12T00:50:42.836549Z"},"links":{"cited_paper":"/paper/2502.06533","citing_paper":"/paper/2605.08283"},"observation_digest":"sha256:9cd5f840540686569ebfd1a713db7fb389d000668d87f389b34b2c1682ee4933","observation_id":"3164a8ee-072f-4e86-80d7-3c6c4139884a","resolution":{"observed_at":"2026-05-12T00:51:14.645501Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"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"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.06533/citation-record","integrity":"/paper/2502.06533/integrity","json":"/paper/2502.06533/citation-record.json","paper":"/paper/2502.06533"},"outbound":[],"paper":{"arxiv_id":"2502.06533","last_updated":"2025-02-10T14:56:25Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T20:34:02.031605Z","submitted_at":"2025-02-10T14:56:25Z","title":"Ignore the KL Penalty! Boosting Exploration on Critical Tokens to Enhance RL Fine-Tuning"},"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":"2026-08-08T06:32:00.761636+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 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2502.06533."}