{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:YFCAI2WWYWC5YLDFSAPEKA3LGM","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":"467a8a8981e8eec491ebc0d24e060673a022bef9be8347c6ed09defbdf64529b","cross_cats_sorted":["q-fin.CP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-02-06T06:47:14Z","title_canon_sha256":"0f54fc8729e0388756285689fc72db67ec4594406a6d01e5b0ade59d53870a7b"},"schema_version":"1.0","source":{"id":"2402.03755","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.03755","created_at":"2026-07-05T07:41:58Z"},{"alias_kind":"arxiv_version","alias_value":"2402.03755v1","created_at":"2026-07-05T07:41:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.03755","created_at":"2026-07-05T07:41:58Z"},{"alias_kind":"pith_short_12","alias_value":"YFCAI2WWYWC5","created_at":"2026-07-05T07:41:58Z"},{"alias_kind":"pith_short_16","alias_value":"YFCAI2WWYWC5YLDF","created_at":"2026-07-05T07:41:58Z"},{"alias_kind":"pith_short_8","alias_value":"YFCAI2WW","created_at":"2026-07-05T07:41:58Z"}],"graph_snapshots":[{"event_id":"sha256:71f71af1a73165074a29e4e28df2e55fe2627e63faeecead5274864c1e3a7d99","target":"graph","created_at":"2026-07-05T07:41:58Z","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/2402.03755/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Autonomous agents based on Large Language Models (LLMs) that devise plans and tackle real-world challenges have gained prominence.However, tailoring these agents for specialized domains like quantitative investment remains a formidable task. The core challenge involves efficiently building and integrating a domain-specific knowledge base for the agent's learning process. This paper introduces a principled framework to address this challenge, comprising a two-layer loop.In the inner loop, the agent refines its responses by drawing from its knowledge base, while in the outer loop, these response","authors_text":"Hang Yuan, Jian Guo, Lionel M. Ni, Saizhuo Wang","cross_cats":["q-fin.CP"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-02-06T06:47:14Z","title":"QuantAgent: Seeking Holy Grail in Trading by Self-Improving Large Language Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.03755","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":"sha256:566f431347c1868e147272353754940d96df79cd5d7b7467dcc7e110bec10b4c","target":"record","created_at":"2026-07-05T07:41:58Z","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":"467a8a8981e8eec491ebc0d24e060673a022bef9be8347c6ed09defbdf64529b","cross_cats_sorted":["q-fin.CP"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-02-06T06:47:14Z","title_canon_sha256":"0f54fc8729e0388756285689fc72db67ec4594406a6d01e5b0ade59d53870a7b"},"schema_version":"1.0","source":{"id":"2402.03755","kind":"arxiv","version":1}},"canonical_sha256":"c144046ad6c585dc2c65901e45036b332a8bf32fd891ac0448e81a4a699eda08","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c144046ad6c585dc2c65901e45036b332a8bf32fd891ac0448e81a4a699eda08","first_computed_at":"2026-07-05T07:41:58.004514Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:41:58.004514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mp7IUxDI02jlJkl05WHsNSmbB311tjfjXdBGdSY3eilw1vB0kkOyqgQral0b9DjTiunWyFxFKfitns3Y17GpCA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:41:58.006203Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.03755","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:566f431347c1868e147272353754940d96df79cd5d7b7467dcc7e110bec10b4c","sha256:71f71af1a73165074a29e4e28df2e55fe2627e63faeecead5274864c1e3a7d99"],"state_sha256":"3ef30f99910ed15141f58464ecf15be080060dcbc1e908644a1da95c2c39490d"}