{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:2WXAP7XOLUOO6ZI6GB7XGNBMNG","short_pith_number":"pith:2WXAP7XO","schema_version":"1.0","canonical_sha256":"d5ae07feee5d1cef651e307f73342c6995f4aaca06229a31029274d21aa7ef9c","source":{"kind":"arxiv","id":"2405.02814","version":2},"attestation_state":"computed","paper":{"title":"NegativePrompt: Leveraging Psychology for Large Language Models Enhancement via Negative Emotional Stimuli","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Cheng Li, Jindong Wang, Xu Wang, Yi Chang, Yuan Wu","submitted_at":"2024-05-05T05:06:07Z","abstract_excerpt":"Large Language Models (LLMs) have become integral to a wide spectrum of applications, ranging from traditional computing tasks to advanced artificial intelligence (AI) applications. This widespread adoption has spurred extensive research into LLMs across various disciplines, including the social sciences. Notably, studies have revealed that LLMs possess emotional intelligence, which can be further developed through positive emotional stimuli. This discovery raises an intriguing question: can negative emotions similarly influence LLMs, potentially enhancing their performance? In response to thi"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2405.02814","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-05-05T05:06:07Z","cross_cats_sorted":[],"title_canon_sha256":"7d57b361373a8b5c249fe46b5c1ee6a9cff0fe3ee9267638b206f980f6ce12ce","abstract_canon_sha256":"c972ef86343ad5c71564e1fb4a3951d6de4c35c6ae05c73c9b76299db8e287c5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:18:08.334949Z","signature_b64":"9Zruot9qUamzi2xD3NdOeYpSuruTnDPnBc0TwgT6506csWgQ3c1v0jI77EZ3hBYZRCeqor9LTRk8kSZUUnwrAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d5ae07feee5d1cef651e307f73342c6995f4aaca06229a31029274d21aa7ef9c","last_reissued_at":"2026-07-05T08:18:08.334474Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:18:08.334474Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"NegativePrompt: Leveraging Psychology for Large Language Models Enhancement via Negative Emotional Stimuli","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Cheng Li, Jindong Wang, Xu Wang, Yi Chang, Yuan Wu","submitted_at":"2024-05-05T05:06:07Z","abstract_excerpt":"Large Language Models (LLMs) have become integral to a wide spectrum of applications, ranging from traditional computing tasks to advanced artificial intelligence (AI) applications. This widespread adoption has spurred extensive research into LLMs across various disciplines, including the social sciences. Notably, studies have revealed that LLMs possess emotional intelligence, which can be further developed through positive emotional stimuli. This discovery raises an intriguing question: can negative emotions similarly influence LLMs, potentially enhancing their performance? In response to thi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.02814","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/2405.02814/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2405.02814","created_at":"2026-07-05T08:18:08.334531+00:00"},{"alias_kind":"arxiv_version","alias_value":"2405.02814v2","created_at":"2026-07-05T08:18:08.334531+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.02814","created_at":"2026-07-05T08:18:08.334531+00:00"},{"alias_kind":"pith_short_12","alias_value":"2WXAP7XOLUOO","created_at":"2026-07-05T08:18:08.334531+00:00"},{"alias_kind":"pith_short_16","alias_value":"2WXAP7XOLUOO6ZI6","created_at":"2026-07-05T08:18:08.334531+00:00"},{"alias_kind":"pith_short_8","alias_value":"2WXAP7XO","created_at":"2026-07-05T08:18:08.334531+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":3,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.00935","citing_title":"Relational Intervention During Functional Collapse in Large Language Models: A Lexical-Statistical Ablation and a Structure x Register Factorial","ref_index":18,"is_internal_anchor":false},{"citing_arxiv_id":"2605.24138","citing_title":"Understanding Conversational Patterns in Multi-agent Programming: A Case Study on Fibonacci Game Development","ref_index":23,"is_internal_anchor":false},{"citing_arxiv_id":"2604.07369","citing_title":"The Role of Emotional Stimuli and Intensity in Shaping Large Language Model Behavior","ref_index":11,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/2WXAP7XOLUOO6ZI6GB7XGNBMNG","json":"https://pith.science/pith/2WXAP7XOLUOO6ZI6GB7XGNBMNG.json","graph_json":"https://pith.science/api/pith-number/2WXAP7XOLUOO6ZI6GB7XGNBMNG/graph.json","events_json":"https://pith.science/api/pith-number/2WXAP7XOLUOO6ZI6GB7XGNBMNG/events.json","paper":"https://pith.science/paper/2WXAP7XO"},"agent_actions":{"view_html":"https://pith.science/pith/2WXAP7XOLUOO6ZI6GB7XGNBMNG","download_json":"https://pith.science/pith/2WXAP7XOLUOO6ZI6GB7XGNBMNG.json","view_paper":"https://pith.science/paper/2WXAP7XO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2405.02814&json=true","fetch_graph":"https://pith.science/api/pith-number/2WXAP7XOLUOO6ZI6GB7XGNBMNG/graph.json","fetch_events":"https://pith.science/api/pith-number/2WXAP7XOLUOO6ZI6GB7XGNBMNG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/2WXAP7XOLUOO6ZI6GB7XGNBMNG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/2WXAP7XOLUOO6ZI6GB7XGNBMNG/action/storage_attestation","attest_author":"https://pith.science/pith/2WXAP7XOLUOO6ZI6GB7XGNBMNG/action/author_attestation","sign_citation":"https://pith.science/pith/2WXAP7XOLUOO6ZI6GB7XGNBMNG/action/citation_signature","submit_replication":"https://pith.science/pith/2WXAP7XOLUOO6ZI6GB7XGNBMNG/action/replication_record"}},"created_at":"2026-07-05T08:18:08.334531+00:00","updated_at":"2026-07-05T08:18:08.334531+00:00"}