{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:EGACRL3YM7RDQULYJHIXQ4REJC","short_pith_number":"pith:EGACRL3Y","canonical_record":{"source":{"id":"2501.11977","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-21T08:51:12Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b49485e69873d441bdb6e4e08906c8c381b2a04c7130533369344b338bdc942a","abstract_canon_sha256":"7d3567f331e83be2bde420fa696826c941123536bcd866efee6206b7b46a0852"},"schema_version":"1.0"},"canonical_sha256":"218028af7867e238517849d178722448819b574bbde398a2ba92e02dd423a22c","source":{"kind":"arxiv","id":"2501.11977","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.11977","created_at":"2026-07-05T10:03:16Z"},{"alias_kind":"arxiv_version","alias_value":"2501.11977v1","created_at":"2026-07-05T10:03:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.11977","created_at":"2026-07-05T10:03:16Z"},{"alias_kind":"pith_short_12","alias_value":"EGACRL3YM7RD","created_at":"2026-07-05T10:03:16Z"},{"alias_kind":"pith_short_16","alias_value":"EGACRL3YM7RDQULY","created_at":"2026-07-05T10:03:16Z"},{"alias_kind":"pith_short_8","alias_value":"EGACRL3Y","created_at":"2026-07-05T10:03:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:EGACRL3YM7RDQULYJHIXQ4REJC","target":"record","payload":{"canonical_record":{"source":{"id":"2501.11977","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-21T08:51:12Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"b49485e69873d441bdb6e4e08906c8c381b2a04c7130533369344b338bdc942a","abstract_canon_sha256":"7d3567f331e83be2bde420fa696826c941123536bcd866efee6206b7b46a0852"},"schema_version":"1.0"},"canonical_sha256":"218028af7867e238517849d178722448819b574bbde398a2ba92e02dd423a22c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:03:16.937823Z","signature_b64":"ZroXqsD4CKIxhxdrYUwpotHgrAKOXuSEKoWlPCkhkkeeHp56yAQ8He0WxhVw8y+87R0xbY7oT0kMglYlX6K6Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"218028af7867e238517849d178722448819b574bbde398a2ba92e02dd423a22c","last_reissued_at":"2026-07-05T10:03:16.937440Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:03:16.937440Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2501.11977","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":"2026-07-05T10:03:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3IbNhcRVSVhDJezWizX/WoIm25M4kAxX4Wk2Vq+/qHC1ydG/XC+FyQNKa9sXFF2+OGkjPHi+DYS6POR6HBr3BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T21:28:20.058774Z"},"content_sha256":"ba5a008e055e3b6fbf224c0555f99d6e4cc8ab71f29f8e5296afe9393d4a071a","schema_version":"1.0","event_id":"sha256:ba5a008e055e3b6fbf224c0555f99d6e4cc8ab71f29f8e5296afe9393d4a071a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:EGACRL3YM7RDQULYJHIXQ4REJC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Leveraging Graph Structures and Large Language Models for End-to-End Synthetic Task-Oriented Dialogues","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Bruno Yun, Fr\\'ed\\'eric Armetta, Hugo Imbert, Maya Medjad, Rapha\\\"el Szymocha","submitted_at":"2025-01-21T08:51:12Z","abstract_excerpt":"Training task-oriented dialogue systems is both costly and time-consuming, due to the need for high-quality datasets encompassing diverse intents. Traditional methods depend on extensive human annotation, while recent advancements leverage large language models (LLMs) to generate synthetic data. However, these approaches often require custom prompts or code, limiting accessibility for non-technical users. We introduce GraphTOD, an end-to-end framework that simplifies the generation of task-oriented dialogues. Users can create dialogues by specifying transition graphs in JSON format. Our evalua"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.11977","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/2501.11977/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":"2026-07-05T10:03:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sIJb+0TeCyW0ume3WlDHpgoAK3SEssBC4HyrB2fQymbWecSSTc2HKTCKOjNtfatZmua+b6VgfRXYo/EYRkIaAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T21:28:20.059697Z"},"content_sha256":"f47489296ebbba08ad7f53cec1cb8d3c69323d89c42fb2f699ae89c3bbb2501e","schema_version":"1.0","event_id":"sha256:f47489296ebbba08ad7f53cec1cb8d3c69323d89c42fb2f699ae89c3bbb2501e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EGACRL3YM7RDQULYJHIXQ4REJC/bundle.json","state_url":"https://pith.science/pith/EGACRL3YM7RDQULYJHIXQ4REJC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EGACRL3YM7RDQULYJHIXQ4REJC/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":"2026-08-20T21:28:20Z","links":{"resolver":"https://pith.science/pith/EGACRL3YM7RDQULYJHIXQ4REJC","bundle":"https://pith.science/pith/EGACRL3YM7RDQULYJHIXQ4REJC/bundle.json","state":"https://pith.science/pith/EGACRL3YM7RDQULYJHIXQ4REJC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EGACRL3YM7RDQULYJHIXQ4REJC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:EGACRL3YM7RDQULYJHIXQ4REJC","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":"7d3567f331e83be2bde420fa696826c941123536bcd866efee6206b7b46a0852","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-21T08:51:12Z","title_canon_sha256":"b49485e69873d441bdb6e4e08906c8c381b2a04c7130533369344b338bdc942a"},"schema_version":"1.0","source":{"id":"2501.11977","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2501.11977","created_at":"2026-07-05T10:03:16Z"},{"alias_kind":"arxiv_version","alias_value":"2501.11977v1","created_at":"2026-07-05T10:03:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.11977","created_at":"2026-07-05T10:03:16Z"},{"alias_kind":"pith_short_12","alias_value":"EGACRL3YM7RD","created_at":"2026-07-05T10:03:16Z"},{"alias_kind":"pith_short_16","alias_value":"EGACRL3YM7RDQULY","created_at":"2026-07-05T10:03:16Z"},{"alias_kind":"pith_short_8","alias_value":"EGACRL3Y","created_at":"2026-07-05T10:03:16Z"}],"graph_snapshots":[{"event_id":"sha256:f47489296ebbba08ad7f53cec1cb8d3c69323d89c42fb2f699ae89c3bbb2501e","target":"graph","created_at":"2026-07-05T10:03:16Z","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/2501.11977/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Training task-oriented dialogue systems is both costly and time-consuming, due to the need for high-quality datasets encompassing diverse intents. Traditional methods depend on extensive human annotation, while recent advancements leverage large language models (LLMs) to generate synthetic data. However, these approaches often require custom prompts or code, limiting accessibility for non-technical users. We introduce GraphTOD, an end-to-end framework that simplifies the generation of task-oriented dialogues. Users can create dialogues by specifying transition graphs in JSON format. Our evalua","authors_text":"Bruno Yun, Fr\\'ed\\'eric Armetta, Hugo Imbert, Maya Medjad, Rapha\\\"el Szymocha","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-21T08:51:12Z","title":"Leveraging Graph Structures and Large Language Models for End-to-End Synthetic Task-Oriented Dialogues"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.11977","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:ba5a008e055e3b6fbf224c0555f99d6e4cc8ab71f29f8e5296afe9393d4a071a","target":"record","created_at":"2026-07-05T10:03:16Z","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":"7d3567f331e83be2bde420fa696826c941123536bcd866efee6206b7b46a0852","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-01-21T08:51:12Z","title_canon_sha256":"b49485e69873d441bdb6e4e08906c8c381b2a04c7130533369344b338bdc942a"},"schema_version":"1.0","source":{"id":"2501.11977","kind":"arxiv","version":1}},"canonical_sha256":"218028af7867e238517849d178722448819b574bbde398a2ba92e02dd423a22c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"218028af7867e238517849d178722448819b574bbde398a2ba92e02dd423a22c","first_computed_at":"2026-07-05T10:03:16.937440Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:03:16.937440Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZroXqsD4CKIxhxdrYUwpotHgrAKOXuSEKoWlPCkhkkeeHp56yAQ8He0WxhVw8y+87R0xbY7oT0kMglYlX6K6Ag==","signature_status":"signed_v1","signed_at":"2026-07-05T10:03:16.937823Z","signed_message":"canonical_sha256_bytes"},"source_id":"2501.11977","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ba5a008e055e3b6fbf224c0555f99d6e4cc8ab71f29f8e5296afe9393d4a071a","sha256:f47489296ebbba08ad7f53cec1cb8d3c69323d89c42fb2f699ae89c3bbb2501e"],"state_sha256":"68bc5c5b2b826170ae098a14ed030e2cf90b001737400e75579f3f9d08aa9e74"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2J9Jyw8IkqVFCBhDIER4fQgYbyd3K1IYSQFK2JpVZ8pwX5+WhGG6m4BtXRa84SN/ct4INmFcRAe13uylJmqQDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T21:28:20.065362Z","bundle_sha256":"20975c56046be0e3bd8a08c15fd95dc9abee1e53a63b3a982a34247b06a298e9"}}