{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:XTHLEIMA4T2QDRDXBI7WSCT3RD","short_pith_number":"pith:XTHLEIMA","schema_version":"1.0","canonical_sha256":"bcceb22180e4f501c4770a3f690a7b88fb2a05081f87306327db12d2db0bee09","source":{"kind":"arxiv","id":"2312.15198","version":3},"attestation_state":"computed","paper":{"title":"Do LLM Agents Exhibit Social Behavior?","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.SI","econ.GN","q-fin.EC"],"primary_cat":"cs.AI","authors_text":"Yan Leng, Yuan Yuan","submitted_at":"2023-12-23T08:46:53Z","abstract_excerpt":"As LLMs increasingly take on roles in human-AI interactions and autonomous AI systems, understanding their social behavior becomes important for informed use and continuous improvement. However, their behaviors in social interactions with humans and other agents, as well as the mechanisms shaping their responses, remain underexplored. To address this gap, we introduce a novel probabilistic framework, State-Understanding-Value-Action (SUVA), to systematically analyze LLM responses in social contexts based on their textual outputs (i.e., utterances). Using canonical behavioral economics games an"},"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":"2312.15198","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.AI","submitted_at":"2023-12-23T08:46:53Z","cross_cats_sorted":["cs.SI","econ.GN","q-fin.EC"],"title_canon_sha256":"d2d849d95e05765713b2ad7f9596054fd02568bb42efc2afa944a4d6b97ac2ec","abstract_canon_sha256":"ff9d90940708fda2e056871f3453c86b9d10f6c589ecb6a607f38ab1481b4c52"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:21:02.065083Z","signature_b64":"lLSqAik3eWumdpFYI1o+wXfRqoU22aoKYGUnEn4CktGK4PLkoKTsngza0EQWq2IWqgVZNLgwh4tO9U2ZvXHiBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bcceb22180e4f501c4770a3f690a7b88fb2a05081f87306327db12d2db0bee09","last_reissued_at":"2026-07-05T09:21:02.064040Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:21:02.064040Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Do LLM Agents Exhibit Social Behavior?","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.SI","econ.GN","q-fin.EC"],"primary_cat":"cs.AI","authors_text":"Yan Leng, Yuan Yuan","submitted_at":"2023-12-23T08:46:53Z","abstract_excerpt":"As LLMs increasingly take on roles in human-AI interactions and autonomous AI systems, understanding their social behavior becomes important for informed use and continuous improvement. However, their behaviors in social interactions with humans and other agents, as well as the mechanisms shaping their responses, remain underexplored. To address this gap, we introduce a novel probabilistic framework, State-Understanding-Value-Action (SUVA), to systematically analyze LLM responses in social contexts based on their textual outputs (i.e., utterances). Using canonical behavioral economics games an"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.15198","kind":"arxiv","version":3},"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/2312.15198/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":"2312.15198","created_at":"2026-07-05T09:21:02.064103+00:00"},{"alias_kind":"arxiv_version","alias_value":"2312.15198v3","created_at":"2026-07-05T09:21:02.064103+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.15198","created_at":"2026-07-05T09:21:02.064103+00:00"},{"alias_kind":"pith_short_12","alias_value":"XTHLEIMA4T2Q","created_at":"2026-07-05T09:21:02.064103+00:00"},{"alias_kind":"pith_short_16","alias_value":"XTHLEIMA4T2QDRDX","created_at":"2026-07-05T09:21:02.064103+00:00"},{"alias_kind":"pith_short_8","alias_value":"XTHLEIMA","created_at":"2026-07-05T09:21:02.064103+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":9,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.11470","citing_title":"The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes","ref_index":129,"is_internal_anchor":false},{"citing_arxiv_id":"2606.01145","citing_title":"Reasoning4Sciences: Bridging Reasoning Language Models to All Scientific Branches","ref_index":151,"is_internal_anchor":false},{"citing_arxiv_id":"2606.28456","citing_title":"Is Lying an Emergent Behaviour in LLMs? Evidence from Gaslighting AI agents in a Sustainability Game","ref_index":21,"is_internal_anchor":false},{"citing_arxiv_id":"2606.01145","citing_title":"Reasoning4Sciences: Bridging Reasoning Language Models to All Scientific Branches","ref_index":163,"is_internal_anchor":false},{"citing_arxiv_id":"2509.26464","citing_title":"Extreme Self-Preference in Language Models","ref_index":59,"is_internal_anchor":false},{"citing_arxiv_id":"2511.21783","citing_title":"NetworkGames: Simulating Cooperation in Network Games with Personality-driven LLM Agents","ref_index":16,"is_internal_anchor":false},{"citing_arxiv_id":"2604.19260","citing_title":"Understanding the Mechanism of Altruism in Large Language Models","ref_index":149,"is_internal_anchor":false},{"citing_arxiv_id":"2604.19278","citing_title":"Explicit Trait Inference for Multi-Agent Coordination","ref_index":31,"is_internal_anchor":false},{"citing_arxiv_id":"2604.19245","citing_title":"Talking to a Know-It-All GPT or a Second-Guesser Claude? How Repair reveals unreliable Multi-Turn Behavior in LLMs","ref_index":127,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XTHLEIMA4T2QDRDXBI7WSCT3RD","json":"https://pith.science/pith/XTHLEIMA4T2QDRDXBI7WSCT3RD.json","graph_json":"https://pith.science/api/pith-number/XTHLEIMA4T2QDRDXBI7WSCT3RD/graph.json","events_json":"https://pith.science/api/pith-number/XTHLEIMA4T2QDRDXBI7WSCT3RD/events.json","paper":"https://pith.science/paper/XTHLEIMA"},"agent_actions":{"view_html":"https://pith.science/pith/XTHLEIMA4T2QDRDXBI7WSCT3RD","download_json":"https://pith.science/pith/XTHLEIMA4T2QDRDXBI7WSCT3RD.json","view_paper":"https://pith.science/paper/XTHLEIMA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2312.15198&json=true","fetch_graph":"https://pith.science/api/pith-number/XTHLEIMA4T2QDRDXBI7WSCT3RD/graph.json","fetch_events":"https://pith.science/api/pith-number/XTHLEIMA4T2QDRDXBI7WSCT3RD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XTHLEIMA4T2QDRDXBI7WSCT3RD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XTHLEIMA4T2QDRDXBI7WSCT3RD/action/storage_attestation","attest_author":"https://pith.science/pith/XTHLEIMA4T2QDRDXBI7WSCT3RD/action/author_attestation","sign_citation":"https://pith.science/pith/XTHLEIMA4T2QDRDXBI7WSCT3RD/action/citation_signature","submit_replication":"https://pith.science/pith/XTHLEIMA4T2QDRDXBI7WSCT3RD/action/replication_record"}},"created_at":"2026-07-05T09:21:02.064103+00:00","updated_at":"2026-07-05T09:21:02.064103+00:00"}