{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:S4WGIUZGRWSWP7F25OAIOU4TU7","short_pith_number":"pith:S4WGIUZG","canonical_record":{"source":{"id":"2310.11182","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2023-10-17T11:59:39Z","cross_cats_sorted":[],"title_canon_sha256":"5ad3af3178f6eaeb20af2235c1817b03c6ce987968c562a3e05dbdfb7feda5e1","abstract_canon_sha256":"07b5d28de0426d6f69404b573689d75dc717909f93662765537868a80a54e78b"},"schema_version":"1.0"},"canonical_sha256":"972c6453268da567fcbaeb80875393a7ee4fd703926c00ae38646f0f46482db3","source":{"kind":"arxiv","id":"2310.11182","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.11182","created_at":"2026-07-05T07:01:51Z"},{"alias_kind":"arxiv_version","alias_value":"2310.11182v1","created_at":"2026-07-05T07:01:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.11182","created_at":"2026-07-05T07:01:51Z"},{"alias_kind":"pith_short_12","alias_value":"S4WGIUZGRWSW","created_at":"2026-07-05T07:01:51Z"},{"alias_kind":"pith_short_16","alias_value":"S4WGIUZGRWSWP7F2","created_at":"2026-07-05T07:01:51Z"},{"alias_kind":"pith_short_8","alias_value":"S4WGIUZG","created_at":"2026-07-05T07:01:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:S4WGIUZGRWSWP7F25OAIOU4TU7","target":"record","payload":{"canonical_record":{"source":{"id":"2310.11182","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2023-10-17T11:59:39Z","cross_cats_sorted":[],"title_canon_sha256":"5ad3af3178f6eaeb20af2235c1817b03c6ce987968c562a3e05dbdfb7feda5e1","abstract_canon_sha256":"07b5d28de0426d6f69404b573689d75dc717909f93662765537868a80a54e78b"},"schema_version":"1.0"},"canonical_sha256":"972c6453268da567fcbaeb80875393a7ee4fd703926c00ae38646f0f46482db3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:01:51.867369Z","signature_b64":"1/PksZ2lQDGlnTGNJB1qpPWW4jStlgNO9C3Qw/I0YKnUtyc5KcTkfaVz7qu/bkmlQ7SK9Ww7Dk1o0SprTQRRDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"972c6453268da567fcbaeb80875393a7ee4fd703926c00ae38646f0f46482db3","last_reissued_at":"2026-07-05T07:01:51.866793Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:01:51.866793Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2310.11182","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:01:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"7dV7RHbbkI58A0w2O/jAwqeXDq3I+tD1fbmhMxBUKZ/BjLRdAnv+FLdH/82zscXoyGB0au4WB0m5a5mhmw3sDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T03:05:40.106873Z"},"content_sha256":"9130e4e2b4dbf6f2da7958d1c2625e7f5ef01ca8d4280ccd7994c094b8be85e9","schema_version":"1.0","event_id":"sha256:9130e4e2b4dbf6f2da7958d1c2625e7f5ef01ca8d4280ccd7994c094b8be85e9"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:S4WGIUZGRWSWP7F25OAIOU4TU7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On the Effectiveness of Creating Conversational Agent Personalities Through Prompting","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.HC","authors_text":"Chadha Degachi, (Eric) Heng Gu, Himanshu Verma, Senthil Chandrasegaran, U\\u{g}ur Gen\\c{c}","submitted_at":"2023-10-17T11:59:39Z","abstract_excerpt":"In this work, we report on the effectiveness of our efforts to tailor the personality and conversational style of a conversational agent based on GPT-3.5 and GPT-4 through prompts. We use three personality dimensions with two levels each to create eight conversational agents archetypes. Ten conversations were collected per chatbot, of ten exchanges each, generating 1600 exchanges across GPT-3.5 and GPT-4. Using Linguistic Inquiry and Word Count (LIWC) analysis, we compared the eight agents on language elements including clout, authenticity, and emotion. Four language cues were significantly di"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.11182","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/2310.11182/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:01:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5TnA2n0vmMIWpPswPn7nhllGSkJyXaU/7b9XkmQdLRQwmy3zBxmpgkzOA2TpZnmk8aJaXA1pD4KV7wADpr8nBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T03:05:40.107360Z"},"content_sha256":"ba42386293df1fb724ee1b6d4db1daf07640c5c00b1b1dbc8d6ee9229dd7ca5c","schema_version":"1.0","event_id":"sha256:ba42386293df1fb724ee1b6d4db1daf07640c5c00b1b1dbc8d6ee9229dd7ca5c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/S4WGIUZGRWSWP7F25OAIOU4TU7/bundle.json","state_url":"https://pith.science/pith/S4WGIUZGRWSWP7F25OAIOU4TU7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/S4WGIUZGRWSWP7F25OAIOU4TU7/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-08T03:05:40Z","links":{"resolver":"https://pith.science/pith/S4WGIUZGRWSWP7F25OAIOU4TU7","bundle":"https://pith.science/pith/S4WGIUZGRWSWP7F25OAIOU4TU7/bundle.json","state":"https://pith.science/pith/S4WGIUZGRWSWP7F25OAIOU4TU7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/S4WGIUZGRWSWP7F25OAIOU4TU7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:S4WGIUZGRWSWP7F25OAIOU4TU7","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":"07b5d28de0426d6f69404b573689d75dc717909f93662765537868a80a54e78b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2023-10-17T11:59:39Z","title_canon_sha256":"5ad3af3178f6eaeb20af2235c1817b03c6ce987968c562a3e05dbdfb7feda5e1"},"schema_version":"1.0","source":{"id":"2310.11182","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2310.11182","created_at":"2026-07-05T07:01:51Z"},{"alias_kind":"arxiv_version","alias_value":"2310.11182v1","created_at":"2026-07-05T07:01:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.11182","created_at":"2026-07-05T07:01:51Z"},{"alias_kind":"pith_short_12","alias_value":"S4WGIUZGRWSW","created_at":"2026-07-05T07:01:51Z"},{"alias_kind":"pith_short_16","alias_value":"S4WGIUZGRWSWP7F2","created_at":"2026-07-05T07:01:51Z"},{"alias_kind":"pith_short_8","alias_value":"S4WGIUZG","created_at":"2026-07-05T07:01:51Z"}],"graph_snapshots":[{"event_id":"sha256:ba42386293df1fb724ee1b6d4db1daf07640c5c00b1b1dbc8d6ee9229dd7ca5c","target":"graph","created_at":"2026-07-05T07:01:51Z","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/2310.11182/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this work, we report on the effectiveness of our efforts to tailor the personality and conversational style of a conversational agent based on GPT-3.5 and GPT-4 through prompts. We use three personality dimensions with two levels each to create eight conversational agents archetypes. Ten conversations were collected per chatbot, of ten exchanges each, generating 1600 exchanges across GPT-3.5 and GPT-4. Using Linguistic Inquiry and Word Count (LIWC) analysis, we compared the eight agents on language elements including clout, authenticity, and emotion. Four language cues were significantly di","authors_text":"Chadha Degachi, (Eric) Heng Gu, Himanshu Verma, Senthil Chandrasegaran, U\\u{g}ur Gen\\c{c}","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2023-10-17T11:59:39Z","title":"On the Effectiveness of Creating Conversational Agent Personalities Through Prompting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.11182","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":"sha256:9130e4e2b4dbf6f2da7958d1c2625e7f5ef01ca8d4280ccd7994c094b8be85e9","target":"record","created_at":"2026-07-05T07:01:51Z","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":"07b5d28de0426d6f69404b573689d75dc717909f93662765537868a80a54e78b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2023-10-17T11:59:39Z","title_canon_sha256":"5ad3af3178f6eaeb20af2235c1817b03c6ce987968c562a3e05dbdfb7feda5e1"},"schema_version":"1.0","source":{"id":"2310.11182","kind":"arxiv","version":1}},"canonical_sha256":"972c6453268da567fcbaeb80875393a7ee4fd703926c00ae38646f0f46482db3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"972c6453268da567fcbaeb80875393a7ee4fd703926c00ae38646f0f46482db3","first_computed_at":"2026-07-05T07:01:51.866793Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:01:51.866793Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1/PksZ2lQDGlnTGNJB1qpPWW4jStlgNO9C3Qw/I0YKnUtyc5KcTkfaVz7qu/bkmlQ7SK9Ww7Dk1o0SprTQRRDw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:01:51.867369Z","signed_message":"canonical_sha256_bytes"},"source_id":"2310.11182","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9130e4e2b4dbf6f2da7958d1c2625e7f5ef01ca8d4280ccd7994c094b8be85e9","sha256:ba42386293df1fb724ee1b6d4db1daf07640c5c00b1b1dbc8d6ee9229dd7ca5c"],"state_sha256":"d6fb6efd01606f3d0d902558b25d5941bf68b1a81ae063bb7fbb53bdb4927010"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HFJ3Q9uuLhlp3F4A07O69kFOt4lc4InIyNfPdZgXbdEf2xD9UberguL4p9/KzCFUnbcKHnrRHvKX2VDdMS3pDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T03:05:40.111874Z","bundle_sha256":"e8bb9fd84892923ff789141c51f8150c956f9752c5028f1c0e717e51f49963d2"}}