{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:E2SPDIWZDJVSSME6VLHU4GAGPO","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":"8ce3e2dfeb59373ab97861204b407101144106bde8c4235dbb2b420262332eaf","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-09T12:30:57Z","title_canon_sha256":"5f6bdb7cd7ae2e985167e55b58116d4f478d615f2a333bc459faa2749237e708"},"schema_version":"1.0","source":{"id":"2502.05879","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.05879","created_at":"2026-07-05T10:11:44Z"},{"alias_kind":"arxiv_version","alias_value":"2502.05879v1","created_at":"2026-07-05T10:11:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.05879","created_at":"2026-07-05T10:11:44Z"},{"alias_kind":"pith_short_12","alias_value":"E2SPDIWZDJVS","created_at":"2026-07-05T10:11:44Z"},{"alias_kind":"pith_short_16","alias_value":"E2SPDIWZDJVSSME6","created_at":"2026-07-05T10:11:44Z"},{"alias_kind":"pith_short_8","alias_value":"E2SPDIWZ","created_at":"2026-07-05T10:11:44Z"}],"graph_snapshots":[{"event_id":"sha256:75d6c5e33a8da581dd8d93984cfd0a5fb8f5f64a9f72c122efbda9b408a2e3fa","target":"graph","created_at":"2026-07-05T10:11:44Z","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/2502.05879/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Depression is one of the leading causes of disability worldwide, posing a severe burden on individuals, healthcare systems, and society at large. Recent advancements in Large Language Models (LLMs) have shown promise in addressing mental health challenges, including the detection of depression through text-based analysis. However, current LLM-based methods often struggle with nuanced symptom identification and lack a transparent, step-by-step reasoning process, making it difficult to accurately classify and explain mental health conditions. To address these challenges, we propose a Chain-of-Th","authors_text":"Jiaqing Liu, Lanfen Lin, Rahul Kumar Jain, Ruibo Hou, Shiyu Teng, Shurong Chai, Tomoko Tateyama, Yen-Wei Chen","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-09T12:30:57Z","title":"Enhancing Depression Detection with Chain-of-Thought Prompting: From Emotion to Reasoning Using Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.05879","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":"sha256:98fe4f928a15b24ea45dda75c8ef9ab864f6b41f6b4b1dba8ec4ca254ea3f3e0","target":"record","created_at":"2026-07-05T10:11:44Z","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":"8ce3e2dfeb59373ab97861204b407101144106bde8c4235dbb2b420262332eaf","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-02-09T12:30:57Z","title_canon_sha256":"5f6bdb7cd7ae2e985167e55b58116d4f478d615f2a333bc459faa2749237e708"},"schema_version":"1.0","source":{"id":"2502.05879","kind":"arxiv","version":1}},"canonical_sha256":"26a4f1a2d91a6b29309eaacf4e18067b8066aff1d26cad0293c2a1115cf0339d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"26a4f1a2d91a6b29309eaacf4e18067b8066aff1d26cad0293c2a1115cf0339d","first_computed_at":"2026-07-05T10:11:44.607134Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:11:44.607134Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0rZIkFbxitZdjhjEnEq0JTQckYp+d6985FUoEwi1V/MJqulnjlkG0Znt/ol8VkIX5IMvMOwVkJ6/BsMKlCTNCg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:11:44.607611Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.05879","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:98fe4f928a15b24ea45dda75c8ef9ab864f6b41f6b4b1dba8ec4ca254ea3f3e0","sha256:75d6c5e33a8da581dd8d93984cfd0a5fb8f5f64a9f72c122efbda9b408a2e3fa"],"state_sha256":"1f8ec074bb53f5c4c90707b1a7521d2e9bfcda1b848602b800f229ce65411c7d"}