{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TLTBTR2TWV45IMG3IF5PDVRYXO","short_pith_number":"pith:TLTBTR2T","canonical_record":{"source":{"id":"2402.01737","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-29T09:07:40Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"408d8c796cfd48154167f6c651518eacc74b031d3cee09de538a09dcc00a341a","abstract_canon_sha256":"04236f4b972c3427e268ac0fa94c7f6a738e9e176db733ccf65f4bd7bd030abd"},"schema_version":"1.0"},"canonical_sha256":"9ae619c753b579d430db417af1d638bb94b685e2280eb6ecf48bd0ddc854dbbf","source":{"kind":"arxiv","id":"2402.01737","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.01737","created_at":"2026-07-05T10:15:15Z"},{"alias_kind":"arxiv_version","alias_value":"2402.01737v3","created_at":"2026-07-05T10:15:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.01737","created_at":"2026-07-05T10:15:15Z"},{"alias_kind":"pith_short_12","alias_value":"TLTBTR2TWV45","created_at":"2026-07-05T10:15:15Z"},{"alias_kind":"pith_short_16","alias_value":"TLTBTR2TWV45IMG3","created_at":"2026-07-05T10:15:15Z"},{"alias_kind":"pith_short_8","alias_value":"TLTBTR2T","created_at":"2026-07-05T10:15:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TLTBTR2TWV45IMG3IF5PDVRYXO","target":"record","payload":{"canonical_record":{"source":{"id":"2402.01737","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-29T09:07:40Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"408d8c796cfd48154167f6c651518eacc74b031d3cee09de538a09dcc00a341a","abstract_canon_sha256":"04236f4b972c3427e268ac0fa94c7f6a738e9e176db733ccf65f4bd7bd030abd"},"schema_version":"1.0"},"canonical_sha256":"9ae619c753b579d430db417af1d638bb94b685e2280eb6ecf48bd0ddc854dbbf","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:15:15.409371Z","signature_b64":"3x5hHCciOz+CQiL4//nAEDmNSrkJNOwNRgloYP+rK9vlj9j7mZpBCysPjCw6jQJ3PEah3Bd+fDtwdsCPFS+8Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9ae619c753b579d430db417af1d638bb94b685e2280eb6ecf48bd0ddc854dbbf","last_reissued_at":"2026-07-05T10:15:15.408874Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:15:15.408874Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.01737","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:15:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"J/fKBgvZQ1gi9uZmGtZDg/zNZ3bPOlTYzcpTorLyQfibLJXyQPNIFk23zEFIJsVR5k/VmUJSvIzfjeyjaF54BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T06:41:20.907183Z"},"content_sha256":"ab2cb7b339f79bc14aa9ec930f6b47bfc628e1aa43e07ab85a5ef8b4eb1ba558","schema_version":"1.0","event_id":"sha256:ab2cb7b339f79bc14aa9ec930f6b47bfc628e1aa43e07ab85a5ef8b4eb1ba558"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TLTBTR2TWV45IMG3IF5PDVRYXO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Assistive Large Language Model Agents for Socially-Aware Negotiation Dialogues","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Gholamreza Haffari, Lizhen Qu, Yuncheng Hua","submitted_at":"2024-01-29T09:07:40Z","abstract_excerpt":"We develop assistive agents based on Large Language Models (LLMs) that aid interlocutors in business negotiations. Specifically, we simulate business negotiations by letting two LLM-based agents engage in role play. A third LLM acts as a remediator agent to rewrite utterances violating norms for improving negotiation outcomes. We introduce a simple tuning-free and label-free In-Context Learning (ICL) method to identify high-quality ICL exemplars for the remediator, where we propose a novel select criteria, called value impact, to measure the quality of the negotiation outcomes. We provide rich"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.01737","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/2402.01737/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":"2026-07-05T10:15:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yu0d3e37p5wIReuYA8841LoerrOpf8FqlSY1gLwiKsiPe06vQ+cpCR1/Ekv/bPg0GVkIoMUksIQ8nN4J1g00Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T06:41:20.907565Z"},"content_sha256":"f4b98e0679669616dccf18cfefd645757ab9ee0e00b58909cf7a2e17f590e933","schema_version":"1.0","event_id":"sha256:f4b98e0679669616dccf18cfefd645757ab9ee0e00b58909cf7a2e17f590e933"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TLTBTR2TWV45IMG3IF5PDVRYXO/bundle.json","state_url":"https://pith.science/pith/TLTBTR2TWV45IMG3IF5PDVRYXO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TLTBTR2TWV45IMG3IF5PDVRYXO/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":"2026-08-14T06:41:20Z","links":{"resolver":"https://pith.science/pith/TLTBTR2TWV45IMG3IF5PDVRYXO","bundle":"https://pith.science/pith/TLTBTR2TWV45IMG3IF5PDVRYXO/bundle.json","state":"https://pith.science/pith/TLTBTR2TWV45IMG3IF5PDVRYXO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TLTBTR2TWV45IMG3IF5PDVRYXO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TLTBTR2TWV45IMG3IF5PDVRYXO","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":"04236f4b972c3427e268ac0fa94c7f6a738e9e176db733ccf65f4bd7bd030abd","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-29T09:07:40Z","title_canon_sha256":"408d8c796cfd48154167f6c651518eacc74b031d3cee09de538a09dcc00a341a"},"schema_version":"1.0","source":{"id":"2402.01737","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.01737","created_at":"2026-07-05T10:15:15Z"},{"alias_kind":"arxiv_version","alias_value":"2402.01737v3","created_at":"2026-07-05T10:15:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.01737","created_at":"2026-07-05T10:15:15Z"},{"alias_kind":"pith_short_12","alias_value":"TLTBTR2TWV45","created_at":"2026-07-05T10:15:15Z"},{"alias_kind":"pith_short_16","alias_value":"TLTBTR2TWV45IMG3","created_at":"2026-07-05T10:15:15Z"},{"alias_kind":"pith_short_8","alias_value":"TLTBTR2T","created_at":"2026-07-05T10:15:15Z"}],"graph_snapshots":[{"event_id":"sha256:f4b98e0679669616dccf18cfefd645757ab9ee0e00b58909cf7a2e17f590e933","target":"graph","created_at":"2026-07-05T10:15:15Z","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/2402.01737/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We develop assistive agents based on Large Language Models (LLMs) that aid interlocutors in business negotiations. Specifically, we simulate business negotiations by letting two LLM-based agents engage in role play. A third LLM acts as a remediator agent to rewrite utterances violating norms for improving negotiation outcomes. We introduce a simple tuning-free and label-free In-Context Learning (ICL) method to identify high-quality ICL exemplars for the remediator, where we propose a novel select criteria, called value impact, to measure the quality of the negotiation outcomes. We provide rich","authors_text":"Gholamreza Haffari, Lizhen Qu, Yuncheng Hua","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-29T09:07:40Z","title":"Assistive Large Language Model Agents for Socially-Aware Negotiation Dialogues"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.01737","kind":"arxiv","version":3},"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:ab2cb7b339f79bc14aa9ec930f6b47bfc628e1aa43e07ab85a5ef8b4eb1ba558","target":"record","created_at":"2026-07-05T10:15:15Z","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":"04236f4b972c3427e268ac0fa94c7f6a738e9e176db733ccf65f4bd7bd030abd","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-01-29T09:07:40Z","title_canon_sha256":"408d8c796cfd48154167f6c651518eacc74b031d3cee09de538a09dcc00a341a"},"schema_version":"1.0","source":{"id":"2402.01737","kind":"arxiv","version":3}},"canonical_sha256":"9ae619c753b579d430db417af1d638bb94b685e2280eb6ecf48bd0ddc854dbbf","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9ae619c753b579d430db417af1d638bb94b685e2280eb6ecf48bd0ddc854dbbf","first_computed_at":"2026-07-05T10:15:15.408874Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:15:15.408874Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3x5hHCciOz+CQiL4//nAEDmNSrkJNOwNRgloYP+rK9vlj9j7mZpBCysPjCw6jQJ3PEah3Bd+fDtwdsCPFS+8Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:15:15.409371Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.01737","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ab2cb7b339f79bc14aa9ec930f6b47bfc628e1aa43e07ab85a5ef8b4eb1ba558","sha256:f4b98e0679669616dccf18cfefd645757ab9ee0e00b58909cf7a2e17f590e933"],"state_sha256":"aa6d122f61f8dc589a3fcdb576a90be22e0960a5537429d4a565b45b795afad8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EznZ4q1TF2PKsaYs6l3SlMDMFWPtAWOLzdoW2Da7m2PX+bEi5zk9DuTTZj5e3ggYUVk2WAQDkbgrjNTzCsMaBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T06:41:20.911549Z","bundle_sha256":"aae73740a9d7d58115265a443513941597dbefddaf70d3505a0bf382227737f2"}}