{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:SODMVGEULLXYL6NLYJ7RMP6TRJ","short_pith_number":"pith:SODMVGEU","canonical_record":{"source":{"id":"2602.10894","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-11T14:25:38Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"0e99f88961f75e13dee7138345ee3b9d9d4c5cac9a8989e744683f2f5f4f5630","abstract_canon_sha256":"8bfefb7991d44f485d672f5eafa151aa34d575868c15fcfc9c503bfe293539a1"},"schema_version":"1.0"},"canonical_sha256":"9386ca98945aef85f9abc27f163fd38a7de49b2760ff4df8555cbf1d8bb5fcc5","source":{"kind":"arxiv","id":"2602.10894","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.10894","created_at":"2026-05-22T01:03:57Z"},{"alias_kind":"arxiv_version","alias_value":"2602.10894v2","created_at":"2026-05-22T01:03:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.10894","created_at":"2026-05-22T01:03:57Z"},{"alias_kind":"pith_short_12","alias_value":"SODMVGEULLXY","created_at":"2026-05-22T01:03:57Z"},{"alias_kind":"pith_short_16","alias_value":"SODMVGEULLXYL6NL","created_at":"2026-05-22T01:03:57Z"},{"alias_kind":"pith_short_8","alias_value":"SODMVGEU","created_at":"2026-05-22T01:03:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:SODMVGEULLXYL6NLYJ7RMP6TRJ","target":"record","payload":{"canonical_record":{"source":{"id":"2602.10894","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-11T14:25:38Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"0e99f88961f75e13dee7138345ee3b9d9d4c5cac9a8989e744683f2f5f4f5630","abstract_canon_sha256":"8bfefb7991d44f485d672f5eafa151aa34d575868c15fcfc9c503bfe293539a1"},"schema_version":"1.0"},"canonical_sha256":"9386ca98945aef85f9abc27f163fd38a7de49b2760ff4df8555cbf1d8bb5fcc5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-22T01:03:57.299159Z","signature_b64":"0nyoC25UBemJxXap6fjA2dtNzAw4LDpbC28tod3kFVgb5Y8Ms+Q53HU7pwLzG/sZjxo9ij1iSc/xtL+6qKjFDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9386ca98945aef85f9abc27f163fd38a7de49b2760ff4df8555cbf1d8bb5fcc5","last_reissued_at":"2026-05-22T01:03:57.298517Z","signature_status":"signed_v1","first_computed_at":"2026-05-22T01:03:57.298517Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2602.10894","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-22T01:03:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l5GF3ccu1faMoAJQAhoAX8m/IoN081P0agvQLkIROa1w1mYIAKMF7knjX6UY7dD4Fr7DdvFKOQfcxDCBG7pjDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T19:31:55.519758Z"},"content_sha256":"8c27ed14efd469404fdfbafffd9440276b126f1ffa9eacd4e8eb1bab8be9f61c","schema_version":"1.0","event_id":"sha256:8c27ed14efd469404fdfbafffd9440276b126f1ffa9eacd4e8eb1bab8be9f61c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:SODMVGEULLXYL6NLYJ7RMP6TRJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Revisiting Regularized Policy Optimization for Stable and Efficient Reinforcement Learning in Two-Player Games","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Kazuki Ota, Motoki Omura, Takayuki Osa, Tatsuya Harada","submitted_at":"2026-02-11T14:25:38Z","abstract_excerpt":"Two-player games such as board games have long been used as traditional benchmarks for reinforcement learning. This work revisits a policy optimization method with reverse Kullback-Leibler regularization and entropy regularization and analyzes this combination in two-player zero-sum settings from theoretical and empirical perspectives. From a theoretical perspective, we investigate the stability of the policy update rule in two theoretical settings: game-theoretic normal-form games and finite-length games. We provide novel convergence guarantees and verify our theoretical results through numer"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.10894","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2602.10894/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-22T01:03:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lk7md/Sje5iRH9iKT+u91AIS9A2AZdXaXlFwtZ1d64MtO2oloE1FObKPd8A9I/RTbrcnRtBETbZ7DThWbcSCDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T19:31:55.520148Z"},"content_sha256":"1b737012ae86f670c7c32fea7e53dd21a98ce8e130e4dac54ad191e76c973c31","schema_version":"1.0","event_id":"sha256:1b737012ae86f670c7c32fea7e53dd21a98ce8e130e4dac54ad191e76c973c31"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SODMVGEULLXYL6NLYJ7RMP6TRJ/bundle.json","state_url":"https://pith.science/pith/SODMVGEULLXYL6NLYJ7RMP6TRJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SODMVGEULLXYL6NLYJ7RMP6TRJ/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-26T19:31:55Z","links":{"resolver":"https://pith.science/pith/SODMVGEULLXYL6NLYJ7RMP6TRJ","bundle":"https://pith.science/pith/SODMVGEULLXYL6NLYJ7RMP6TRJ/bundle.json","state":"https://pith.science/pith/SODMVGEULLXYL6NLYJ7RMP6TRJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SODMVGEULLXYL6NLYJ7RMP6TRJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:SODMVGEULLXYL6NLYJ7RMP6TRJ","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"8bfefb7991d44f485d672f5eafa151aa34d575868c15fcfc9c503bfe293539a1","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-11T14:25:38Z","title_canon_sha256":"0e99f88961f75e13dee7138345ee3b9d9d4c5cac9a8989e744683f2f5f4f5630"},"schema_version":"1.0","source":{"id":"2602.10894","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2602.10894","created_at":"2026-05-22T01:03:57Z"},{"alias_kind":"arxiv_version","alias_value":"2602.10894v2","created_at":"2026-05-22T01:03:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2602.10894","created_at":"2026-05-22T01:03:57Z"},{"alias_kind":"pith_short_12","alias_value":"SODMVGEULLXY","created_at":"2026-05-22T01:03:57Z"},{"alias_kind":"pith_short_16","alias_value":"SODMVGEULLXYL6NL","created_at":"2026-05-22T01:03:57Z"},{"alias_kind":"pith_short_8","alias_value":"SODMVGEU","created_at":"2026-05-22T01:03:57Z"}],"graph_snapshots":[{"event_id":"sha256:1b737012ae86f670c7c32fea7e53dd21a98ce8e130e4dac54ad191e76c973c31","target":"graph","created_at":"2026-05-22T01:03:57Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2602.10894/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Two-player games such as board games have long been used as traditional benchmarks for reinforcement learning. This work revisits a policy optimization method with reverse Kullback-Leibler regularization and entropy regularization and analyzes this combination in two-player zero-sum settings from theoretical and empirical perspectives. From a theoretical perspective, we investigate the stability of the policy update rule in two theoretical settings: game-theoretic normal-form games and finite-length games. We provide novel convergence guarantees and verify our theoretical results through numer","authors_text":"Kazuki Ota, Motoki Omura, Takayuki Osa, Tatsuya Harada","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-11T14:25:38Z","title":"Revisiting Regularized Policy Optimization for Stable and Efficient Reinforcement Learning in Two-Player Games"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2602.10894","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:8c27ed14efd469404fdfbafffd9440276b126f1ffa9eacd4e8eb1bab8be9f61c","target":"record","created_at":"2026-05-22T01:03:57Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"8bfefb7991d44f485d672f5eafa151aa34d575868c15fcfc9c503bfe293539a1","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2026-02-11T14:25:38Z","title_canon_sha256":"0e99f88961f75e13dee7138345ee3b9d9d4c5cac9a8989e744683f2f5f4f5630"},"schema_version":"1.0","source":{"id":"2602.10894","kind":"arxiv","version":2}},"canonical_sha256":"9386ca98945aef85f9abc27f163fd38a7de49b2760ff4df8555cbf1d8bb5fcc5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9386ca98945aef85f9abc27f163fd38a7de49b2760ff4df8555cbf1d8bb5fcc5","first_computed_at":"2026-05-22T01:03:57.298517Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-22T01:03:57.298517Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0nyoC25UBemJxXap6fjA2dtNzAw4LDpbC28tod3kFVgb5Y8Ms+Q53HU7pwLzG/sZjxo9ij1iSc/xtL+6qKjFDw==","signature_status":"signed_v1","signed_at":"2026-05-22T01:03:57.299159Z","signed_message":"canonical_sha256_bytes"},"source_id":"2602.10894","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8c27ed14efd469404fdfbafffd9440276b126f1ffa9eacd4e8eb1bab8be9f61c","sha256:1b737012ae86f670c7c32fea7e53dd21a98ce8e130e4dac54ad191e76c973c31"],"state_sha256":"4aed6d9075e9ad64c4629729e660deb14f0f88abfb2325069b45f85c0146ec17"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PWzTJu4C//PaPPoIgWeMAb71eSahoOYerG6fGFOxqxAZQAhbAyVCizn8VAYQoUjeT5oZSO7YyiTWeJO+985ZAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T19:31:55.522875Z","bundle_sha256":"ce86cdc9a0448b1629d0e761059c7b5854593f393d180376c0b403fcd9f69f6a"}}