{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:USCHOORMGEWK5MOQ2RYIE5M6UH","short_pith_number":"pith:USCHOORM","canonical_record":{"source":{"id":"2406.11736","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-17T16:52:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"54497344ee4f8ba7047038cd0edc14ee0d3b907ca2525396bc7e572c041f2834","abstract_canon_sha256":"d1b3ce85c2fb1972c073f04d3452889dac9822656a05f0e81b1f17b4dec41221"},"schema_version":"1.0"},"canonical_sha256":"a484773a2c312caeb1d0d47082759ea1d54818a0b40354c10b21f6a4b9d01242","source":{"kind":"arxiv","id":"2406.11736","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.11736","created_at":"2026-07-05T08:32:56Z"},{"alias_kind":"arxiv_version","alias_value":"2406.11736v1","created_at":"2026-07-05T08:32:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.11736","created_at":"2026-07-05T08:32:56Z"},{"alias_kind":"pith_short_12","alias_value":"USCHOORMGEWK","created_at":"2026-07-05T08:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"USCHOORMGEWK5MOQ","created_at":"2026-07-05T08:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"USCHOORM","created_at":"2026-07-05T08:32:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:USCHOORMGEWK5MOQ2RYIE5M6UH","target":"record","payload":{"canonical_record":{"source":{"id":"2406.11736","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-17T16:52:56Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"54497344ee4f8ba7047038cd0edc14ee0d3b907ca2525396bc7e572c041f2834","abstract_canon_sha256":"d1b3ce85c2fb1972c073f04d3452889dac9822656a05f0e81b1f17b4dec41221"},"schema_version":"1.0"},"canonical_sha256":"a484773a2c312caeb1d0d47082759ea1d54818a0b40354c10b21f6a4b9d01242","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:32:56.976643Z","signature_b64":"kEJCh34z/OtyTQPcBgOQx5Hkt1+/f8GrLNm9vbwqJCROOfpEtS/siWFTm36+SpYqH1EOcn2vZI0IoeWf/qYADA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a484773a2c312caeb1d0d47082759ea1d54818a0b40354c10b21f6a4b9d01242","last_reissued_at":"2026-07-05T08:32:56.976195Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:32:56.976195Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.11736","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:32:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yzKdN65PGdys9DaWBg0V6F4qndxiwwY7TlWn79aGLN4D7wwS5b4AcHMb04n/BtJVMl6MD5d0ZNP/Gz/it15UCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T10:39:09.982778Z"},"content_sha256":"41d4f72398f5ff9aae8b191961291045802a7f1382fe745aebcfedacba4b3c77","schema_version":"1.0","event_id":"sha256:41d4f72398f5ff9aae8b191961291045802a7f1382fe745aebcfedacba4b3c77"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:USCHOORMGEWK5MOQ2RYIE5M6UH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Fangzhi Xu, Jun Liu, Kanzhi Cheng, Qiushi Sun, Yu Qiao, Zhiyong Wu","submitted_at":"2024-06-17T16:52:56Z","abstract_excerpt":"One of the primary driving forces contributing to the superior performance of Large Language Models (LLMs) is the extensive availability of human-annotated natural language data, which is used for alignment fine-tuning. This inspired researchers to investigate self-training methods to mitigate the extensive reliance on human annotations. However, the current success of self-training has been primarily observed in natural language scenarios, rather than in the increasingly important neural-symbolic scenarios. To this end, we propose an environment-guided neural-symbolic self-training framework "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.11736","kind":"arxiv","version":1},"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/2406.11736/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":"2026-07-05T08:32:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Mlpy2xTXmt+Cgfc0vtXpX7l6g+ifTeLqXYUfgXoqL4yrgzSsYPrqbxL26aEIYpL3n2IaRmsOGs3FYhK19UnSBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T10:39:09.983302Z"},"content_sha256":"4b5901ac14e08345d81572d8e482040a10ecc03aa7d259c6b98e6bd814820ee4","schema_version":"1.0","event_id":"sha256:4b5901ac14e08345d81572d8e482040a10ecc03aa7d259c6b98e6bd814820ee4"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/USCHOORMGEWK5MOQ2RYIE5M6UH/bundle.json","state_url":"https://pith.science/pith/USCHOORMGEWK5MOQ2RYIE5M6UH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/USCHOORMGEWK5MOQ2RYIE5M6UH/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":"2026-08-07T10:39:09Z","links":{"resolver":"https://pith.science/pith/USCHOORMGEWK5MOQ2RYIE5M6UH","bundle":"https://pith.science/pith/USCHOORMGEWK5MOQ2RYIE5M6UH/bundle.json","state":"https://pith.science/pith/USCHOORMGEWK5MOQ2RYIE5M6UH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/USCHOORMGEWK5MOQ2RYIE5M6UH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:USCHOORMGEWK5MOQ2RYIE5M6UH","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":"d1b3ce85c2fb1972c073f04d3452889dac9822656a05f0e81b1f17b4dec41221","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-17T16:52:56Z","title_canon_sha256":"54497344ee4f8ba7047038cd0edc14ee0d3b907ca2525396bc7e572c041f2834"},"schema_version":"1.0","source":{"id":"2406.11736","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.11736","created_at":"2026-07-05T08:32:56Z"},{"alias_kind":"arxiv_version","alias_value":"2406.11736v1","created_at":"2026-07-05T08:32:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.11736","created_at":"2026-07-05T08:32:56Z"},{"alias_kind":"pith_short_12","alias_value":"USCHOORMGEWK","created_at":"2026-07-05T08:32:56Z"},{"alias_kind":"pith_short_16","alias_value":"USCHOORMGEWK5MOQ","created_at":"2026-07-05T08:32:56Z"},{"alias_kind":"pith_short_8","alias_value":"USCHOORM","created_at":"2026-07-05T08:32:56Z"}],"graph_snapshots":[{"event_id":"sha256:4b5901ac14e08345d81572d8e482040a10ecc03aa7d259c6b98e6bd814820ee4","target":"graph","created_at":"2026-07-05T08:32:56Z","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/2406.11736/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"One of the primary driving forces contributing to the superior performance of Large Language Models (LLMs) is the extensive availability of human-annotated natural language data, which is used for alignment fine-tuning. This inspired researchers to investigate self-training methods to mitigate the extensive reliance on human annotations. However, the current success of self-training has been primarily observed in natural language scenarios, rather than in the increasingly important neural-symbolic scenarios. To this end, we propose an environment-guided neural-symbolic self-training framework ","authors_text":"Fangzhi Xu, Jun Liu, Kanzhi Cheng, Qiushi Sun, Yu Qiao, Zhiyong Wu","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-17T16:52:56Z","title":"Interactive Evolution: A Neural-Symbolic Self-Training Framework For Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.11736","kind":"arxiv","version":1},"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":"sha256:41d4f72398f5ff9aae8b191961291045802a7f1382fe745aebcfedacba4b3c77","target":"record","created_at":"2026-07-05T08:32:56Z","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":"d1b3ce85c2fb1972c073f04d3452889dac9822656a05f0e81b1f17b4dec41221","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-17T16:52:56Z","title_canon_sha256":"54497344ee4f8ba7047038cd0edc14ee0d3b907ca2525396bc7e572c041f2834"},"schema_version":"1.0","source":{"id":"2406.11736","kind":"arxiv","version":1}},"canonical_sha256":"a484773a2c312caeb1d0d47082759ea1d54818a0b40354c10b21f6a4b9d01242","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a484773a2c312caeb1d0d47082759ea1d54818a0b40354c10b21f6a4b9d01242","first_computed_at":"2026-07-05T08:32:56.976195Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:32:56.976195Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kEJCh34z/OtyTQPcBgOQx5Hkt1+/f8GrLNm9vbwqJCROOfpEtS/siWFTm36+SpYqH1EOcn2vZI0IoeWf/qYADA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:32:56.976643Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.11736","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:41d4f72398f5ff9aae8b191961291045802a7f1382fe745aebcfedacba4b3c77","sha256:4b5901ac14e08345d81572d8e482040a10ecc03aa7d259c6b98e6bd814820ee4"],"state_sha256":"3a4313b30662e6d137ffba73a5ff11cfdca3c7fdc974e9ab02272230808cd524"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4aNU1P4gNl+PA9msAF9eawot3RqzXZUvtIayxM6hfsxj6KDuewtd3N9DgXhtZdPyareLod43DYLpwu949BTdDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T10:39:09.987822Z","bundle_sha256":"55d7be2ea6d16b232078a5397b5b56ba05ac6d68a090ed5857a31b08f3911bff"}}