{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:DRUM346J5CL5WKVLULOCL7L64W","short_pith_number":"pith:DRUM346J","schema_version":"1.0","canonical_sha256":"1c68cdf3c9e897db2aaba2dc25fd7ee59a9247829200b4acd5bd5a14e3820e90","source":{"kind":"arxiv","id":"2403.05045","version":1},"attestation_state":"computed","paper":{"title":"Are Human Conversations Special? A Large Language Model Perspective","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Chaitanya Animesh, Kartik Talamadupula, Larry Heck, Sekhar Vallath, Toshish Jawale","submitted_at":"2024-03-08T04:44:25Z","abstract_excerpt":"This study analyzes changes in the attention mechanisms of large language models (LLMs) when used to understand natural conversations between humans (human-human). We analyze three use cases of LLMs: interactions over web content, code, and mathematical texts. By analyzing attention distance, dispersion, and interdependency across these domains, we highlight the unique challenges posed by conversational data. Notably, conversations require nuanced handling of long-term contextual relationships and exhibit higher complexity through their attention patterns. Our findings reveal that while langua"},"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":"2403.05045","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-08T04:44:25Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"a905401f387a19b5a373ad499d16347ad4a1f29d03e4b4287c1ebea16a5b4f1b","abstract_canon_sha256":"d20524828fa1e8864f2223c20e73572a40828aa0f3e1db0bc1126b3904168815"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:53:37.651474Z","signature_b64":"S0tuI43jQJYC1CBdkyVl7v+mftMmuQqp6o/XA/yZvuNNHLX1NslyuSgfMP5VaJOwfEFpZuF+IeSoHKbA3KPABg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1c68cdf3c9e897db2aaba2dc25fd7ee59a9247829200b4acd5bd5a14e3820e90","last_reissued_at":"2026-07-05T07:53:37.650991Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:53:37.650991Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Are Human Conversations Special? A Large Language Model Perspective","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Chaitanya Animesh, Kartik Talamadupula, Larry Heck, Sekhar Vallath, Toshish Jawale","submitted_at":"2024-03-08T04:44:25Z","abstract_excerpt":"This study analyzes changes in the attention mechanisms of large language models (LLMs) when used to understand natural conversations between humans (human-human). We analyze three use cases of LLMs: interactions over web content, code, and mathematical texts. By analyzing attention distance, dispersion, and interdependency across these domains, we highlight the unique challenges posed by conversational data. Notably, conversations require nuanced handling of long-term contextual relationships and exhibit higher complexity through their attention patterns. Our findings reveal that while langua"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.05045","kind":"arxiv","version":1},"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/2403.05045/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":"2403.05045","created_at":"2026-07-05T07:53:37.651063+00:00"},{"alias_kind":"arxiv_version","alias_value":"2403.05045v1","created_at":"2026-07-05T07:53:37.651063+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.05045","created_at":"2026-07-05T07:53:37.651063+00:00"},{"alias_kind":"pith_short_12","alias_value":"DRUM346J5CL5","created_at":"2026-07-05T07:53:37.651063+00:00"},{"alias_kind":"pith_short_16","alias_value":"DRUM346J5CL5WKVL","created_at":"2026-07-05T07:53:37.651063+00:00"},{"alias_kind":"pith_short_8","alias_value":"DRUM346J","created_at":"2026-07-05T07:53:37.651063+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2501.04138","citing_title":"\"Yeah Right!\" -- Do LLMs Exhibit Multimodal Feature Transfer?","ref_index":2024,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/DRUM346J5CL5WKVLULOCL7L64W","json":"https://pith.science/pith/DRUM346J5CL5WKVLULOCL7L64W.json","graph_json":"https://pith.science/api/pith-number/DRUM346J5CL5WKVLULOCL7L64W/graph.json","events_json":"https://pith.science/api/pith-number/DRUM346J5CL5WKVLULOCL7L64W/events.json","paper":"https://pith.science/paper/DRUM346J"},"agent_actions":{"view_html":"https://pith.science/pith/DRUM346J5CL5WKVLULOCL7L64W","download_json":"https://pith.science/pith/DRUM346J5CL5WKVLULOCL7L64W.json","view_paper":"https://pith.science/paper/DRUM346J","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2403.05045&json=true","fetch_graph":"https://pith.science/api/pith-number/DRUM346J5CL5WKVLULOCL7L64W/graph.json","fetch_events":"https://pith.science/api/pith-number/DRUM346J5CL5WKVLULOCL7L64W/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/DRUM346J5CL5WKVLULOCL7L64W/action/timestamp_anchor","attest_storage":"https://pith.science/pith/DRUM346J5CL5WKVLULOCL7L64W/action/storage_attestation","attest_author":"https://pith.science/pith/DRUM346J5CL5WKVLULOCL7L64W/action/author_attestation","sign_citation":"https://pith.science/pith/DRUM346J5CL5WKVLULOCL7L64W/action/citation_signature","submit_replication":"https://pith.science/pith/DRUM346J5CL5WKVLULOCL7L64W/action/replication_record"}},"created_at":"2026-07-05T07:53:37.651063+00:00","updated_at":"2026-07-05T07:53:37.651063+00:00"}