{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:XDRU5GGVVVXHZ7MCATFKQTDCSM","short_pith_number":"pith:XDRU5GGV","canonical_record":{"source":{"id":"2607.01557","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-02T00:24:48Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"a6595f54b21355e0a85d74d90db47688e12cf243a2154f3bfea523137600adc9","abstract_canon_sha256":"6329f18f0450c5d70619cb8aed6851f101cb99e6c9369adb436be3bf94069dc2"},"schema_version":"1.0"},"canonical_sha256":"b8e34e98d5ad6e7cfd8204caa84c62930fafdfe738cd4077e3ab0491089f5cee","source":{"kind":"arxiv","id":"2607.01557","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.01557","created_at":"2026-07-03T00:17:03Z"},{"alias_kind":"arxiv_version","alias_value":"2607.01557v1","created_at":"2026-07-03T00:17:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.01557","created_at":"2026-07-03T00:17:03Z"},{"alias_kind":"pith_short_12","alias_value":"XDRU5GGVVVXH","created_at":"2026-07-03T00:17:03Z"},{"alias_kind":"pith_short_16","alias_value":"XDRU5GGVVVXHZ7MC","created_at":"2026-07-03T00:17:03Z"},{"alias_kind":"pith_short_8","alias_value":"XDRU5GGV","created_at":"2026-07-03T00:17:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:XDRU5GGVVVXHZ7MCATFKQTDCSM","target":"record","payload":{"canonical_record":{"source":{"id":"2607.01557","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-02T00:24:48Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"a6595f54b21355e0a85d74d90db47688e12cf243a2154f3bfea523137600adc9","abstract_canon_sha256":"6329f18f0450c5d70619cb8aed6851f101cb99e6c9369adb436be3bf94069dc2"},"schema_version":"1.0"},"canonical_sha256":"b8e34e98d5ad6e7cfd8204caa84c62930fafdfe738cd4077e3ab0491089f5cee","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-03T00:17:03.954839Z","signature_b64":"s6OU9kTA/q0jLZuZGUznF8TUej7VD2eh1OgtjLL62mf9XPAUSRTgt12N/ez4nzzI981ejMUaM2vsOGInlTvbAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b8e34e98d5ad6e7cfd8204caa84c62930fafdfe738cd4077e3ab0491089f5cee","last_reissued_at":"2026-07-03T00:17:03.954453Z","signature_status":"signed_v1","first_computed_at":"2026-07-03T00:17:03.954453Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.01557","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":"2026-07-03T00:17:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3Z0P1RxBKkqYOnLPRak3Wdo+Lsop2aFfeZraNmfiBaK/tdeCJWfy6ryy+m8wwb90gInKWh29xzrcnBl31KtaBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T10:01:09.058129Z"},"content_sha256":"a550773d12f0753c7b0e78811eab9ca469233ac415858eff6edb58ac2612af37","schema_version":"1.0","event_id":"sha256:a550773d12f0753c7b0e78811eab9ca469233ac415858eff6edb58ac2612af37"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:XDRU5GGVVVXHZ7MCATFKQTDCSM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DiPS: Dialogue Policy Selection for High-Stakes Persuasion Agents","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Abrar Anwar, David Traum, Jesse Thomason, Mousumi Das, Tianyi Zhang","submitted_at":"2026-07-02T00:24:48Z","abstract_excerpt":"Large Language Models (LLMs) often struggle with persuasion in high-stakes scenarios. People's individual personalities and concerns require tailored strategies rather than a one-size-fits-all approach. To address this challenge, we focus on a fire-rescue scenario in which an operator must persuade a resident to evacuate as a high-stakes persuasion domain and propose Dialogue Policy Selection (DiPS), a Q-learning framework to dynamically select persuasion strategies adapted to the evolving conversational context. Specifically, we train a critic, trained to maximize the chance of evacuation suc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.01557","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/2607.01557/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":"2026-07-03T00:17:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gDbGVDmMYk+Vlfmzw+InipLAmw3AvRckDL7qf15IbKjOAdxTEscpPC8wxye9qFRBTjBMu9SQy7Mst5K0Z043CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T10:01:09.058512Z"},"content_sha256":"1f11c2c4bc255c1c480494d4c8c22c22490d6010d2000ef9405b98778694e9e8","schema_version":"1.0","event_id":"sha256:1f11c2c4bc255c1c480494d4c8c22c22490d6010d2000ef9405b98778694e9e8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XDRU5GGVVVXHZ7MCATFKQTDCSM/bundle.json","state_url":"https://pith.science/pith/XDRU5GGVVVXHZ7MCATFKQTDCSM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XDRU5GGVVVXHZ7MCATFKQTDCSM/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":"2026-07-06T10:01:09Z","links":{"resolver":"https://pith.science/pith/XDRU5GGVVVXHZ7MCATFKQTDCSM","bundle":"https://pith.science/pith/XDRU5GGVVVXHZ7MCATFKQTDCSM/bundle.json","state":"https://pith.science/pith/XDRU5GGVVVXHZ7MCATFKQTDCSM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XDRU5GGVVVXHZ7MCATFKQTDCSM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:XDRU5GGVVVXHZ7MCATFKQTDCSM","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":"6329f18f0450c5d70619cb8aed6851f101cb99e6c9369adb436be3bf94069dc2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-02T00:24:48Z","title_canon_sha256":"a6595f54b21355e0a85d74d90db47688e12cf243a2154f3bfea523137600adc9"},"schema_version":"1.0","source":{"id":"2607.01557","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.01557","created_at":"2026-07-03T00:17:03Z"},{"alias_kind":"arxiv_version","alias_value":"2607.01557v1","created_at":"2026-07-03T00:17:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.01557","created_at":"2026-07-03T00:17:03Z"},{"alias_kind":"pith_short_12","alias_value":"XDRU5GGVVVXH","created_at":"2026-07-03T00:17:03Z"},{"alias_kind":"pith_short_16","alias_value":"XDRU5GGVVVXHZ7MC","created_at":"2026-07-03T00:17:03Z"},{"alias_kind":"pith_short_8","alias_value":"XDRU5GGV","created_at":"2026-07-03T00:17:03Z"}],"graph_snapshots":[{"event_id":"sha256:1f11c2c4bc255c1c480494d4c8c22c22490d6010d2000ef9405b98778694e9e8","target":"graph","created_at":"2026-07-03T00:17:03Z","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/2607.01557/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) often struggle with persuasion in high-stakes scenarios. People's individual personalities and concerns require tailored strategies rather than a one-size-fits-all approach. To address this challenge, we focus on a fire-rescue scenario in which an operator must persuade a resident to evacuate as a high-stakes persuasion domain and propose Dialogue Policy Selection (DiPS), a Q-learning framework to dynamically select persuasion strategies adapted to the evolving conversational context. Specifically, we train a critic, trained to maximize the chance of evacuation suc","authors_text":"Abrar Anwar, David Traum, Jesse Thomason, Mousumi Das, Tianyi Zhang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-02T00:24:48Z","title":"DiPS: Dialogue Policy Selection for High-Stakes Persuasion Agents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.01557","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:a550773d12f0753c7b0e78811eab9ca469233ac415858eff6edb58ac2612af37","target":"record","created_at":"2026-07-03T00:17:03Z","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":"6329f18f0450c5d70619cb8aed6851f101cb99e6c9369adb436be3bf94069dc2","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2026-07-02T00:24:48Z","title_canon_sha256":"a6595f54b21355e0a85d74d90db47688e12cf243a2154f3bfea523137600adc9"},"schema_version":"1.0","source":{"id":"2607.01557","kind":"arxiv","version":1}},"canonical_sha256":"b8e34e98d5ad6e7cfd8204caa84c62930fafdfe738cd4077e3ab0491089f5cee","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b8e34e98d5ad6e7cfd8204caa84c62930fafdfe738cd4077e3ab0491089f5cee","first_computed_at":"2026-07-03T00:17:03.954453Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-03T00:17:03.954453Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"s6OU9kTA/q0jLZuZGUznF8TUej7VD2eh1OgtjLL62mf9XPAUSRTgt12N/ez4nzzI981ejMUaM2vsOGInlTvbAA==","signature_status":"signed_v1","signed_at":"2026-07-03T00:17:03.954839Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.01557","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a550773d12f0753c7b0e78811eab9ca469233ac415858eff6edb58ac2612af37","sha256:1f11c2c4bc255c1c480494d4c8c22c22490d6010d2000ef9405b98778694e9e8"],"state_sha256":"73e0384b0a54893a0a8ca650ee85fe095cf61b4ee57373b05952a59b487c6913"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9Xs6nTLTyFSDWQdbu5jRMHA/Z4zgmIIxevQekRsz91FP7shvLpm8qT3hkukW+Y4I2dP6ftjZWngC/quKCB4MAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T10:01:09.060351Z","bundle_sha256":"db1473f01a439e7408a09fda64d6369641afee2cb978355986efb992b23d1d0c"}}