{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:3SC5YDEDOEFX2UHDSGBTBI73T2","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":"dd47e3a87b258bac572e25923038037f4e36a099e9a70c0c025ca64dd478b67c","cross_cats_sorted":["cs.AI","cs.CL","cs.FL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-01T17:30:50Z","title_canon_sha256":"3a0e15d3a90668d29e061cbb07c8e7cdb5bec07fe76d29f96551da045c2e35d5"},"schema_version":"1.0","source":{"id":"2402.00798","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.00798","created_at":"2026-07-05T08:54:35Z"},{"alias_kind":"arxiv_version","alias_value":"2402.00798v4","created_at":"2026-07-05T08:54:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.00798","created_at":"2026-07-05T08:54:35Z"},{"alias_kind":"pith_short_12","alias_value":"3SC5YDEDOEFX","created_at":"2026-07-05T08:54:35Z"},{"alias_kind":"pith_short_16","alias_value":"3SC5YDEDOEFX2UHD","created_at":"2026-07-05T08:54:35Z"},{"alias_kind":"pith_short_8","alias_value":"3SC5YDED","created_at":"2026-07-05T08:54:35Z"}],"graph_snapshots":[{"event_id":"sha256:6377b4f6becb7432bd68f4af98f4d56de5838e152c2297e0b184844f0bbaf116","target":"graph","created_at":"2026-07-05T08:54:35Z","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/2402.00798/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advancements on Large Language Models (LLMs) enable AI Agents to automatically generate and execute multi-step plans to solve complex tasks. However, since LLM's content generation process is hardly controllable, current LLM-based agents frequently generate invalid or non-executable plans, which jeopardizes the performance of the generated plans and corrupts users' trust in LLM-based agents. In response, this paper proposes a novel \"Formal-LLM\" framework for LLM-based agents by integrating the expressiveness of natural language and the precision of formal language. Specifically, the fra","authors_text":"Hao Wang, He Zhu, Wenyue Hua, Yongfeng Zhang, Zelong Li","cross_cats":["cs.AI","cs.CL","cs.FL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-01T17:30:50Z","title":"Formal-LLM: Integrating Formal Language and Natural Language for Controllable LLM-based Agents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.00798","kind":"arxiv","version":4},"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":"sha256:0247f6ee2eee83a05edd4776eea65a8ed92a722e7d2f95fdb1717fbc79619093","target":"record","created_at":"2026-07-05T08:54:35Z","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":"dd47e3a87b258bac572e25923038037f4e36a099e9a70c0c025ca64dd478b67c","cross_cats_sorted":["cs.AI","cs.CL","cs.FL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-02-01T17:30:50Z","title_canon_sha256":"3a0e15d3a90668d29e061cbb07c8e7cdb5bec07fe76d29f96551da045c2e35d5"},"schema_version":"1.0","source":{"id":"2402.00798","kind":"arxiv","version":4}},"canonical_sha256":"dc85dc0c83710b7d50e3918330a3fb9eac5d24ecf0149fecfe2472b2722bced2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"dc85dc0c83710b7d50e3918330a3fb9eac5d24ecf0149fecfe2472b2722bced2","first_computed_at":"2026-07-05T08:54:35.890597Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:54:35.890597Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Nssr7ooxpXQgQADDbYNeXkv4IJVX0VAu8vFzR1BtrWnyzUpMi7HspwkTLOHVnJf+3P1Qmur3UJmtJ7AHyDrODA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:54:35.891080Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.00798","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0247f6ee2eee83a05edd4776eea65a8ed92a722e7d2f95fdb1717fbc79619093","sha256:6377b4f6becb7432bd68f4af98f4d56de5838e152c2297e0b184844f0bbaf116"],"state_sha256":"500a26f0b63bf5f828194b0932c4f5b3ee23ec04ac73b9944ac1fe64c075de90"}