{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:BDTDV26LLMIBTM7B3OALLNQUMO","short_pith_number":"pith:BDTDV26L","canonical_record":{"source":{"id":"2402.07157","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-11T11:03:04Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"2730f12c8ea64b6b5a2cf8d1b0e0e2766b970f0598984d8a414a930985835a6f","abstract_canon_sha256":"a5d3278c0f51506fe97adc1138c6d2033175cab2c67310178beb9682ec31d68d"},"schema_version":"1.0"},"canonical_sha256":"08e63aebcb5b1019b3e1db80b5b614638fb1bb96273d2e05f2c5a27b85d0ed3a","source":{"kind":"arxiv","id":"2402.07157","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.07157","created_at":"2026-07-05T07:45:15Z"},{"alias_kind":"arxiv_version","alias_value":"2402.07157v2","created_at":"2026-07-05T07:45:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.07157","created_at":"2026-07-05T07:45:15Z"},{"alias_kind":"pith_short_12","alias_value":"BDTDV26LLMIB","created_at":"2026-07-05T07:45:15Z"},{"alias_kind":"pith_short_16","alias_value":"BDTDV26LLMIBTM7B","created_at":"2026-07-05T07:45:15Z"},{"alias_kind":"pith_short_8","alias_value":"BDTDV26L","created_at":"2026-07-05T07:45:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:BDTDV26LLMIBTM7B3OALLNQUMO","target":"record","payload":{"canonical_record":{"source":{"id":"2402.07157","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-11T11:03:04Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"2730f12c8ea64b6b5a2cf8d1b0e0e2766b970f0598984d8a414a930985835a6f","abstract_canon_sha256":"a5d3278c0f51506fe97adc1138c6d2033175cab2c67310178beb9682ec31d68d"},"schema_version":"1.0"},"canonical_sha256":"08e63aebcb5b1019b3e1db80b5b614638fb1bb96273d2e05f2c5a27b85d0ed3a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:45:15.751737Z","signature_b64":"nC0J3naCUo759UbGRdcssd941VFczTWDGZPwWqLIPfr1Lr6nRJqJoRylAHoWaIGabP4IS2OvHzUNYf4jgFw2BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"08e63aebcb5b1019b3e1db80b5b614638fb1bb96273d2e05f2c5a27b85d0ed3a","last_reissued_at":"2026-07-05T07:45:15.751245Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:45:15.751245Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.07157","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":"2026-07-05T07:45:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rOtelj2TE5Jrl4EuNjDLfFYll0V1pF9x2+yVlcj5A8VCnhc/Ck35hBBu+DbY4RyEXGBYtFlMUrPJKZfZwJHFCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T08:51:19.049522Z"},"content_sha256":"1c6735f5e38d9c7c3f8ad7e8bc73c74256ba1bd53697569e5fbf8eab36fe2206","schema_version":"1.0","event_id":"sha256:1c6735f5e38d9c7c3f8ad7e8bc73c74256ba1bd53697569e5fbf8eab36fe2206"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:BDTDV26LLMIBTM7B3OALLNQUMO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Natural Language Reinforcement Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Girish A. Koushik, Jun Wang, Mengyue Yang, Xidong Feng, Yali Du, Ying Wen, Ziyan Wang, Ziyu Wan","submitted_at":"2024-02-11T11:03:04Z","abstract_excerpt":"Reinforcement Learning (RL) has shown remarkable abilities in learning policies for decision-making tasks. However, RL is often hindered by issues such as low sample efficiency, lack of interpretability, and sparse supervision signals. To tackle these limitations, we take inspiration from the human learning process and introduce Natural Language Reinforcement Learning (NLRL), which innovatively combines RL principles with natural language representation. Specifically, NLRL redefines RL concepts like task objectives, policy, value function, Bellman equation, and policy iteration in natural lang"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.07157","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/2402.07157/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":"2026-07-05T07:45:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RblM9uBayAnVWFkiCnjcOv+VyHq7mfZjrxIqQXPRI9qq5Ojqs6UDyIRvmJ+sWoyz3SV5zbkar79aAZhgnJxkDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T08:51:19.050469Z"},"content_sha256":"e8d4e61be44464c235a3ecb69514879c4447b1abbb4fce172a0818811c0d6dee","schema_version":"1.0","event_id":"sha256:e8d4e61be44464c235a3ecb69514879c4447b1abbb4fce172a0818811c0d6dee"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BDTDV26LLMIBTM7B3OALLNQUMO/bundle.json","state_url":"https://pith.science/pith/BDTDV26LLMIBTM7B3OALLNQUMO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BDTDV26LLMIBTM7B3OALLNQUMO/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":"2026-08-14T08:51:19Z","links":{"resolver":"https://pith.science/pith/BDTDV26LLMIBTM7B3OALLNQUMO","bundle":"https://pith.science/pith/BDTDV26LLMIBTM7B3OALLNQUMO/bundle.json","state":"https://pith.science/pith/BDTDV26LLMIBTM7B3OALLNQUMO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BDTDV26LLMIBTM7B3OALLNQUMO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:BDTDV26LLMIBTM7B3OALLNQUMO","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":"a5d3278c0f51506fe97adc1138c6d2033175cab2c67310178beb9682ec31d68d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-11T11:03:04Z","title_canon_sha256":"2730f12c8ea64b6b5a2cf8d1b0e0e2766b970f0598984d8a414a930985835a6f"},"schema_version":"1.0","source":{"id":"2402.07157","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.07157","created_at":"2026-07-05T07:45:15Z"},{"alias_kind":"arxiv_version","alias_value":"2402.07157v2","created_at":"2026-07-05T07:45:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.07157","created_at":"2026-07-05T07:45:15Z"},{"alias_kind":"pith_short_12","alias_value":"BDTDV26LLMIB","created_at":"2026-07-05T07:45:15Z"},{"alias_kind":"pith_short_16","alias_value":"BDTDV26LLMIBTM7B","created_at":"2026-07-05T07:45:15Z"},{"alias_kind":"pith_short_8","alias_value":"BDTDV26L","created_at":"2026-07-05T07:45:15Z"}],"graph_snapshots":[{"event_id":"sha256:e8d4e61be44464c235a3ecb69514879c4447b1abbb4fce172a0818811c0d6dee","target":"graph","created_at":"2026-07-05T07:45:15Z","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/2402.07157/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Reinforcement Learning (RL) has shown remarkable abilities in learning policies for decision-making tasks. However, RL is often hindered by issues such as low sample efficiency, lack of interpretability, and sparse supervision signals. To tackle these limitations, we take inspiration from the human learning process and introduce Natural Language Reinforcement Learning (NLRL), which innovatively combines RL principles with natural language representation. Specifically, NLRL redefines RL concepts like task objectives, policy, value function, Bellman equation, and policy iteration in natural lang","authors_text":"Girish A. Koushik, Jun Wang, Mengyue Yang, Xidong Feng, Yali Du, Ying Wen, Ziyan Wang, Ziyu Wan","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-11T11:03:04Z","title":"Natural Language Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.07157","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":"sha256:1c6735f5e38d9c7c3f8ad7e8bc73c74256ba1bd53697569e5fbf8eab36fe2206","target":"record","created_at":"2026-07-05T07:45:15Z","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":"a5d3278c0f51506fe97adc1138c6d2033175cab2c67310178beb9682ec31d68d","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-02-11T11:03:04Z","title_canon_sha256":"2730f12c8ea64b6b5a2cf8d1b0e0e2766b970f0598984d8a414a930985835a6f"},"schema_version":"1.0","source":{"id":"2402.07157","kind":"arxiv","version":2}},"canonical_sha256":"08e63aebcb5b1019b3e1db80b5b614638fb1bb96273d2e05f2c5a27b85d0ed3a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"08e63aebcb5b1019b3e1db80b5b614638fb1bb96273d2e05f2c5a27b85d0ed3a","first_computed_at":"2026-07-05T07:45:15.751245Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:45:15.751245Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nC0J3naCUo759UbGRdcssd941VFczTWDGZPwWqLIPfr1Lr6nRJqJoRylAHoWaIGabP4IS2OvHzUNYf4jgFw2BA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:45:15.751737Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.07157","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1c6735f5e38d9c7c3f8ad7e8bc73c74256ba1bd53697569e5fbf8eab36fe2206","sha256:e8d4e61be44464c235a3ecb69514879c4447b1abbb4fce172a0818811c0d6dee"],"state_sha256":"9c73907e2f9b05d35979fffe97c89441fb5ac6245274b5d128fe442698a7b493"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/BDhcVRMu77hXAyEIqHzm3VcD2Gq3/uSa4eWESKKZwLdl4Kmeb8K7ydlmW2HrY8fW6P9wriqX06nQwswmtHuDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T08:51:19.056084Z","bundle_sha256":"25a43c3459798db3642166b4a6c0df39adcb8addcd6ee94e68f5a7c2a92e958f"}}