{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:5TLYPTLLSNWCZSASNTRUQEXNYV","short_pith_number":"pith:5TLYPTLL","canonical_record":{"source":{"id":"2312.16233","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-12-25T02:18:58Z","cross_cats_sorted":[],"title_canon_sha256":"b994883cbb287915b17874d778168d1bbe09c51141c52ec267877a0309c9a93a","abstract_canon_sha256":"765cea00a1bb01e9e83c6aa843ef8e24e04a14212a663cd646bc146792907b46"},"schema_version":"1.0"},"canonical_sha256":"ecd787cd6b936c2cc8126ce34812edc56d6c4637b7679df8914cba941a6c3a06","source":{"kind":"arxiv","id":"2312.16233","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.16233","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"arxiv_version","alias_value":"2312.16233v1","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.16233","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"pith_short_12","alias_value":"5TLYPTLLSNWC","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"pith_short_16","alias_value":"5TLYPTLLSNWCZSAS","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"pith_short_8","alias_value":"5TLYPTLL","created_at":"2026-07-05T07:28:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:5TLYPTLLSNWCZSASNTRUQEXNYV","target":"record","payload":{"canonical_record":{"source":{"id":"2312.16233","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-12-25T02:18:58Z","cross_cats_sorted":[],"title_canon_sha256":"b994883cbb287915b17874d778168d1bbe09c51141c52ec267877a0309c9a93a","abstract_canon_sha256":"765cea00a1bb01e9e83c6aa843ef8e24e04a14212a663cd646bc146792907b46"},"schema_version":"1.0"},"canonical_sha256":"ecd787cd6b936c2cc8126ce34812edc56d6c4637b7679df8914cba941a6c3a06","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:28:14.784797Z","signature_b64":"ZBCupD0KVo1MLU6f8pLtT+3f5pXSKTh2xapIedWyIAx7dHviZ5EFAesVPmROrZrrQN/tLdd3hnkNva4/ySErBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ecd787cd6b936c2cc8126ce34812edc56d6c4637b7679df8914cba941a6c3a06","last_reissued_at":"2026-07-05T07:28:14.784363Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:28:14.784363Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.16233","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":"2026-07-05T07:28:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zG05Wj0E8vvkF4pBO/GEHKStutm3TphgWTevaMy7/eM96l1C0CXLgB4le0kmSei7qzHNu7ECaV4a38PiHed+AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T03:56:05.573614Z"},"content_sha256":"acddd50d66a9cdd6a5c74f81e7a5980a6f7d74e0bd1270975973691a53864d54","schema_version":"1.0","event_id":"sha256:acddd50d66a9cdd6a5c74f81e7a5980a6f7d74e0bd1270975973691a53864d54"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:5TLYPTLLSNWCZSASNTRUQEXNYV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Chatbot is Not All You Need: Information-rich Prompting for More Realistic Responses","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Assentay Makhmud, Seokhoon Jeong","submitted_at":"2023-12-25T02:18:58Z","abstract_excerpt":"Recent Large Language Models (LLMs) have shown remarkable capabilities in mimicking fictional characters or real humans in conversational settings. However, the realism and consistency of these responses can be further enhanced by providing richer information of the agent being mimicked. In this paper, we propose a novel approach to generate more realistic and consistent responses from LLMs, leveraging five senses, attributes, emotional states, relationship with the interlocutor, and memories. By incorporating these factors, we aim to increase the LLM's capacity for generating natural and real"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.16233","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/2312.16233/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":"2026-07-05T07:28:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+EfIawL3ZKL+XAcEkzj8VNH+UTuVb7c37yYUkXqxVspJ/6lfpc0ay+N5bkYjq+ozqdf4XIh+jkIZjQLhspkhBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T03:56:05.574147Z"},"content_sha256":"afe943521652844d48840d4c2241c40add4cd743e3b6129a27d46846e3112bb6","schema_version":"1.0","event_id":"sha256:afe943521652844d48840d4c2241c40add4cd743e3b6129a27d46846e3112bb6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5TLYPTLLSNWCZSASNTRUQEXNYV/bundle.json","state_url":"https://pith.science/pith/5TLYPTLLSNWCZSASNTRUQEXNYV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5TLYPTLLSNWCZSASNTRUQEXNYV/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":"2026-08-23T03:56:05Z","links":{"resolver":"https://pith.science/pith/5TLYPTLLSNWCZSASNTRUQEXNYV","bundle":"https://pith.science/pith/5TLYPTLLSNWCZSASNTRUQEXNYV/bundle.json","state":"https://pith.science/pith/5TLYPTLLSNWCZSASNTRUQEXNYV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5TLYPTLLSNWCZSASNTRUQEXNYV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:5TLYPTLLSNWCZSASNTRUQEXNYV","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":"765cea00a1bb01e9e83c6aa843ef8e24e04a14212a663cd646bc146792907b46","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-12-25T02:18:58Z","title_canon_sha256":"b994883cbb287915b17874d778168d1bbe09c51141c52ec267877a0309c9a93a"},"schema_version":"1.0","source":{"id":"2312.16233","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.16233","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"arxiv_version","alias_value":"2312.16233v1","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.16233","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"pith_short_12","alias_value":"5TLYPTLLSNWC","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"pith_short_16","alias_value":"5TLYPTLLSNWCZSAS","created_at":"2026-07-05T07:28:14Z"},{"alias_kind":"pith_short_8","alias_value":"5TLYPTLL","created_at":"2026-07-05T07:28:14Z"}],"graph_snapshots":[{"event_id":"sha256:afe943521652844d48840d4c2241c40add4cd743e3b6129a27d46846e3112bb6","target":"graph","created_at":"2026-07-05T07:28:14Z","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/2312.16233/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent Large Language Models (LLMs) have shown remarkable capabilities in mimicking fictional characters or real humans in conversational settings. However, the realism and consistency of these responses can be further enhanced by providing richer information of the agent being mimicked. In this paper, we propose a novel approach to generate more realistic and consistent responses from LLMs, leveraging five senses, attributes, emotional states, relationship with the interlocutor, and memories. By incorporating these factors, we aim to increase the LLM's capacity for generating natural and real","authors_text":"Assentay Makhmud, Seokhoon Jeong","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-12-25T02:18:58Z","title":"Chatbot is Not All You Need: Information-rich Prompting for More Realistic Responses"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.16233","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:acddd50d66a9cdd6a5c74f81e7a5980a6f7d74e0bd1270975973691a53864d54","target":"record","created_at":"2026-07-05T07:28:14Z","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":"765cea00a1bb01e9e83c6aa843ef8e24e04a14212a663cd646bc146792907b46","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2023-12-25T02:18:58Z","title_canon_sha256":"b994883cbb287915b17874d778168d1bbe09c51141c52ec267877a0309c9a93a"},"schema_version":"1.0","source":{"id":"2312.16233","kind":"arxiv","version":1}},"canonical_sha256":"ecd787cd6b936c2cc8126ce34812edc56d6c4637b7679df8914cba941a6c3a06","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ecd787cd6b936c2cc8126ce34812edc56d6c4637b7679df8914cba941a6c3a06","first_computed_at":"2026-07-05T07:28:14.784363Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:28:14.784363Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZBCupD0KVo1MLU6f8pLtT+3f5pXSKTh2xapIedWyIAx7dHviZ5EFAesVPmROrZrrQN/tLdd3hnkNva4/ySErBg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:28:14.784797Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.16233","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:acddd50d66a9cdd6a5c74f81e7a5980a6f7d74e0bd1270975973691a53864d54","sha256:afe943521652844d48840d4c2241c40add4cd743e3b6129a27d46846e3112bb6"],"state_sha256":"ca71ec422191277465c3d875596bc46e0ba694bf6b6a27449d7a3a6bb3729ded"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EsT/7RSENQInL2cjpOmFqBUNcjP8a+Jh4lLg5smRR4ghqYyXLLYy2v9R163iMMkl7dRWHltc8j5udpsuhKxdDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T03:56:05.578941Z","bundle_sha256":"da638e01bab1bac8a0f8810ff7ea88a8fd21b8694d57b4fa1848fc8fda1a698d"}}