{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:THTG5FSWWZQLHNQ37PH57QBVND","short_pith_number":"pith:THTG5FSW","canonical_record":{"source":{"id":"2412.11417","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-12-16T03:33:49Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"3289e97596aa2ad3d5d097101327dadaecb86948a483b1b132bda866b69304a6","abstract_canon_sha256":"f1ee4f1f20599ee33593fe0165332dc278cfbaa0d39901086aad86d9afb24637"},"schema_version":"1.0"},"canonical_sha256":"99e66e9656b660b3b61bfbcfdfc03568e222ac6b05f19342e0f4936356466286","source":{"kind":"arxiv","id":"2412.11417","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.11417","created_at":"2026-07-05T09:50:09Z"},{"alias_kind":"arxiv_version","alias_value":"2412.11417v2","created_at":"2026-07-05T09:50:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.11417","created_at":"2026-07-05T09:50:09Z"},{"alias_kind":"pith_short_12","alias_value":"THTG5FSWWZQL","created_at":"2026-07-05T09:50:09Z"},{"alias_kind":"pith_short_16","alias_value":"THTG5FSWWZQLHNQ3","created_at":"2026-07-05T09:50:09Z"},{"alias_kind":"pith_short_8","alias_value":"THTG5FSW","created_at":"2026-07-05T09:50:09Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:THTG5FSWWZQLHNQ37PH57QBVND","target":"record","payload":{"canonical_record":{"source":{"id":"2412.11417","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-12-16T03:33:49Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"3289e97596aa2ad3d5d097101327dadaecb86948a483b1b132bda866b69304a6","abstract_canon_sha256":"f1ee4f1f20599ee33593fe0165332dc278cfbaa0d39901086aad86d9afb24637"},"schema_version":"1.0"},"canonical_sha256":"99e66e9656b660b3b61bfbcfdfc03568e222ac6b05f19342e0f4936356466286","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:50:09.369589Z","signature_b64":"oVp3y2rd8U71g1ZrbF3tUCAI5CEq5BQ94Tn5c1lcEc1S0oI6ppOu017ms7+4vptrTAnzUGmwI9Vhs83mpp7qCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"99e66e9656b660b3b61bfbcfdfc03568e222ac6b05f19342e0f4936356466286","last_reissued_at":"2026-07-05T09:50:09.369099Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:50:09.369099Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.11417","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":"2026-07-05T09:50:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tc8xcHVh36wJRasmalt8PX3VG+PBNvBpmw7KA90Ji8xa++mD6f8PynIKku1n4hTq/Cej2v239TtSBkyvHaBgCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-10T12:38:10.733897Z"},"content_sha256":"80fb29d97f40954d4658d9859214d02fe55731c21e538e651a788591033e8b32","schema_version":"1.0","event_id":"sha256:80fb29d97f40954d4658d9859214d02fe55731c21e538e651a788591033e8b32"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:THTG5FSWWZQLHNQ37PH57QBVND","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RL-LLM-DT: An Automatic Decision Tree Generation Method Based on RL Evaluation and LLM Enhancement","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.AI","authors_text":"Houqiang Li, Jian Zhao, Junjie Lin, Lanxiao Huang, Lin Liu, Wengang Zhou, Xia Lin, Youpeng Zhao, Yue Deng","submitted_at":"2024-12-16T03:33:49Z","abstract_excerpt":"Traditionally, AI development for two-player zero-sum games has relied on two primary techniques: decision trees and reinforcement learning (RL). A common approach involves using a fixed decision tree as one player's strategy while training an RL agent as the opponent to identify vulnerabilities in the decision tree, thereby improving its strategic strength iteratively. However, this process often requires significant human intervention to refine the decision tree after identifying its weaknesses, resulting in inefficiencies and hindering full automation of the strategy enhancement process. Fo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.11417","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/2412.11417/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":"2026-07-05T09:50:09Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1XA3+rQagD77jCMByKM+n2yUSRlJikXphK+kO8CpDNMYs9YmchqLjWZ+c3I9c9G7fx4W7cWcaGUerYzxV+NGCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-10T12:38:10.734276Z"},"content_sha256":"9628410f2de8630dd156e3640200b4936de4455bce5fa992a0312be7415709e1","schema_version":"1.0","event_id":"sha256:9628410f2de8630dd156e3640200b4936de4455bce5fa992a0312be7415709e1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/THTG5FSWWZQLHNQ37PH57QBVND/bundle.json","state_url":"https://pith.science/pith/THTG5FSWWZQLHNQ37PH57QBVND/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/THTG5FSWWZQLHNQ37PH57QBVND/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":"2026-07-10T12:38:10Z","links":{"resolver":"https://pith.science/pith/THTG5FSWWZQLHNQ37PH57QBVND","bundle":"https://pith.science/pith/THTG5FSWWZQLHNQ37PH57QBVND/bundle.json","state":"https://pith.science/pith/THTG5FSWWZQLHNQ37PH57QBVND/state.json","well_known_bundle":"https://pith.science/.well-known/pith/THTG5FSWWZQLHNQ37PH57QBVND/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:THTG5FSWWZQLHNQ37PH57QBVND","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":"f1ee4f1f20599ee33593fe0165332dc278cfbaa0d39901086aad86d9afb24637","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-12-16T03:33:49Z","title_canon_sha256":"3289e97596aa2ad3d5d097101327dadaecb86948a483b1b132bda866b69304a6"},"schema_version":"1.0","source":{"id":"2412.11417","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.11417","created_at":"2026-07-05T09:50:09Z"},{"alias_kind":"arxiv_version","alias_value":"2412.11417v2","created_at":"2026-07-05T09:50:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.11417","created_at":"2026-07-05T09:50:09Z"},{"alias_kind":"pith_short_12","alias_value":"THTG5FSWWZQL","created_at":"2026-07-05T09:50:09Z"},{"alias_kind":"pith_short_16","alias_value":"THTG5FSWWZQLHNQ3","created_at":"2026-07-05T09:50:09Z"},{"alias_kind":"pith_short_8","alias_value":"THTG5FSW","created_at":"2026-07-05T09:50:09Z"}],"graph_snapshots":[{"event_id":"sha256:9628410f2de8630dd156e3640200b4936de4455bce5fa992a0312be7415709e1","target":"graph","created_at":"2026-07-05T09:50:09Z","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/2412.11417/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Traditionally, AI development for two-player zero-sum games has relied on two primary techniques: decision trees and reinforcement learning (RL). A common approach involves using a fixed decision tree as one player's strategy while training an RL agent as the opponent to identify vulnerabilities in the decision tree, thereby improving its strategic strength iteratively. However, this process often requires significant human intervention to refine the decision tree after identifying its weaknesses, resulting in inefficiencies and hindering full automation of the strategy enhancement process. Fo","authors_text":"Houqiang Li, Jian Zhao, Junjie Lin, Lanxiao Huang, Lin Liu, Wengang Zhou, Xia Lin, Youpeng Zhao, Yue Deng","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-12-16T03:33:49Z","title":"RL-LLM-DT: An Automatic Decision Tree Generation Method Based on RL Evaluation and LLM Enhancement"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.11417","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":"sha256:80fb29d97f40954d4658d9859214d02fe55731c21e538e651a788591033e8b32","target":"record","created_at":"2026-07-05T09:50:09Z","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":"f1ee4f1f20599ee33593fe0165332dc278cfbaa0d39901086aad86d9afb24637","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2024-12-16T03:33:49Z","title_canon_sha256":"3289e97596aa2ad3d5d097101327dadaecb86948a483b1b132bda866b69304a6"},"schema_version":"1.0","source":{"id":"2412.11417","kind":"arxiv","version":2}},"canonical_sha256":"99e66e9656b660b3b61bfbcfdfc03568e222ac6b05f19342e0f4936356466286","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"99e66e9656b660b3b61bfbcfdfc03568e222ac6b05f19342e0f4936356466286","first_computed_at":"2026-07-05T09:50:09.369099Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:50:09.369099Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oVp3y2rd8U71g1ZrbF3tUCAI5CEq5BQ94Tn5c1lcEc1S0oI6ppOu017ms7+4vptrTAnzUGmwI9Vhs83mpp7qCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:50:09.369589Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.11417","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:80fb29d97f40954d4658d9859214d02fe55731c21e538e651a788591033e8b32","sha256:9628410f2de8630dd156e3640200b4936de4455bce5fa992a0312be7415709e1"],"state_sha256":"ab35b3f0672baadba3ba03d520013208ed18b6a6d6cb8e477a914368cb108827"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1u+9EjQvrs/153p56zWS04BMsGp6382wK42mO02CaCfox2yYg6p8mH3ZWq4ywoAhjPt+3cRBjWcRoopHCbuUBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-10T12:38:10.736496Z","bundle_sha256":"7b9a4320677d90460bc73ee07b5481851e1c2b5a855886e9ded38a8e4c6d6319"}}