{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:5WRD7ZFWZT72MOKDDHHDUCIF4A","short_pith_number":"pith:5WRD7ZFW","canonical_record":{"source":{"id":"1702.01932","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-02-07T09:16:46Z","cross_cats_sorted":[],"title_canon_sha256":"a95a4d1d0b03f1401fc9595b03fcfa25bf00526daf34580a62ee179ed01a9839","abstract_canon_sha256":"68de932b5c4025e875392c3e28018b31dd5036030100db5892bd36ecf19289ee"},"schema_version":"1.0"},"canonical_sha256":"eda23fe4b6ccffa6394319ce3a0905e028fd96304b2453a2a797e5858cb2eb03","source":{"kind":"arxiv","id":"1702.01932","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1702.01932","created_at":"2026-05-18T00:00:35Z"},{"alias_kind":"arxiv_version","alias_value":"1702.01932v2","created_at":"2026-05-18T00:00:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.01932","created_at":"2026-05-18T00:00:35Z"},{"alias_kind":"pith_short_12","alias_value":"5WRD7ZFWZT72","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_16","alias_value":"5WRD7ZFWZT72MOKD","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_8","alias_value":"5WRD7ZFW","created_at":"2026-05-18T12:31:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:5WRD7ZFWZT72MOKDDHHDUCIF4A","target":"record","payload":{"canonical_record":{"source":{"id":"1702.01932","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-02-07T09:16:46Z","cross_cats_sorted":[],"title_canon_sha256":"a95a4d1d0b03f1401fc9595b03fcfa25bf00526daf34580a62ee179ed01a9839","abstract_canon_sha256":"68de932b5c4025e875392c3e28018b31dd5036030100db5892bd36ecf19289ee"},"schema_version":"1.0"},"canonical_sha256":"eda23fe4b6ccffa6394319ce3a0905e028fd96304b2453a2a797e5858cb2eb03","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:00:35.623948Z","signature_b64":"gu1cTGKD9FYzKilapyiMEpCf5nqbSD5zcj+OvdKu03Q3i6kK2lc5Z7bTXDsmBYCxdnDWvGFAUgUEO2z5XRe8Ag==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eda23fe4b6ccffa6394319ce3a0905e028fd96304b2453a2a797e5858cb2eb03","last_reissued_at":"2026-05-18T00:00:35.623370Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:00:35.623370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1702.01932","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T00:00:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dmK3dvYiLypEpug8cOqm2s7EpW+9DPd2bc5t+FPoY9Hm8iKUOIBnd8p0g0fKMr5FGSx5NZPgHh3vx9gByZtuDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T18:48:34.809180Z"},"content_sha256":"319028f9e177db2db88217723f7b598230dfd1bdcaa45c903837b1671275ed9a","schema_version":"1.0","event_id":"sha256:319028f9e177db2db88217723f7b598230dfd1bdcaa45c903837b1671275ed9a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:5WRD7ZFWZT72MOKDDHHDUCIF4A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Knowledge-Grounded Neural Conversation Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Bill Dolan, Chris Brockett, Jianfeng Gao, Marjan Ghazvininejad, Michel Galley, Ming-Wei Chang, Wen-tau Yih","submitted_at":"2017-02-07T09:16:46Z","abstract_excerpt":"Neural network models are capable of generating extremely natural sounding conversational interactions. Nevertheless, these models have yet to demonstrate that they can incorporate content in the form of factual information or entity-grounded opinion that would enable them to serve in more task-oriented conversational applications. This paper presents a novel, fully data-driven, and knowledge-grounded neural conversation model aimed at producing more contentful responses without slot filling. We generalize the widely-used Seq2Seq approach by conditioning responses on both conversation history "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.01932","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"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":"2026-05-18T00:00:35Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EoPmtbWo+DqN1uMskSgY9bZfYKSGpcqlRrOXOviiA1O3Qx3JDt+TcadtJ8uu2boQsN4IJbO4wSsnVgmeG3RoAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T18:48:34.809656Z"},"content_sha256":"a82d75ae7310046ad71e9f8f81426a8392884406d18f2f30e4e8ae41d518c2a7","schema_version":"1.0","event_id":"sha256:a82d75ae7310046ad71e9f8f81426a8392884406d18f2f30e4e8ae41d518c2a7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5WRD7ZFWZT72MOKDDHHDUCIF4A/bundle.json","state_url":"https://pith.science/pith/5WRD7ZFWZT72MOKDDHHDUCIF4A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5WRD7ZFWZT72MOKDDHHDUCIF4A/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":"2026-05-25T18:48:34Z","links":{"resolver":"https://pith.science/pith/5WRD7ZFWZT72MOKDDHHDUCIF4A","bundle":"https://pith.science/pith/5WRD7ZFWZT72MOKDDHHDUCIF4A/bundle.json","state":"https://pith.science/pith/5WRD7ZFWZT72MOKDDHHDUCIF4A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5WRD7ZFWZT72MOKDDHHDUCIF4A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:5WRD7ZFWZT72MOKDDHHDUCIF4A","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":"68de932b5c4025e875392c3e28018b31dd5036030100db5892bd36ecf19289ee","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-02-07T09:16:46Z","title_canon_sha256":"a95a4d1d0b03f1401fc9595b03fcfa25bf00526daf34580a62ee179ed01a9839"},"schema_version":"1.0","source":{"id":"1702.01932","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1702.01932","created_at":"2026-05-18T00:00:35Z"},{"alias_kind":"arxiv_version","alias_value":"1702.01932v2","created_at":"2026-05-18T00:00:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1702.01932","created_at":"2026-05-18T00:00:35Z"},{"alias_kind":"pith_short_12","alias_value":"5WRD7ZFWZT72","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_16","alias_value":"5WRD7ZFWZT72MOKD","created_at":"2026-05-18T12:31:03Z"},{"alias_kind":"pith_short_8","alias_value":"5WRD7ZFW","created_at":"2026-05-18T12:31:03Z"}],"graph_snapshots":[{"event_id":"sha256:a82d75ae7310046ad71e9f8f81426a8392884406d18f2f30e4e8ae41d518c2a7","target":"graph","created_at":"2026-05-18T00:00:35Z","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"},"paper":{"abstract_excerpt":"Neural network models are capable of generating extremely natural sounding conversational interactions. Nevertheless, these models have yet to demonstrate that they can incorporate content in the form of factual information or entity-grounded opinion that would enable them to serve in more task-oriented conversational applications. This paper presents a novel, fully data-driven, and knowledge-grounded neural conversation model aimed at producing more contentful responses without slot filling. We generalize the widely-used Seq2Seq approach by conditioning responses on both conversation history ","authors_text":"Bill Dolan, Chris Brockett, Jianfeng Gao, Marjan Ghazvininejad, Michel Galley, Ming-Wei Chang, Wen-tau Yih","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-02-07T09:16:46Z","title":"A Knowledge-Grounded Neural Conversation Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1702.01932","kind":"arxiv","version":2},"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":"sha256:319028f9e177db2db88217723f7b598230dfd1bdcaa45c903837b1671275ed9a","target":"record","created_at":"2026-05-18T00:00:35Z","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":"68de932b5c4025e875392c3e28018b31dd5036030100db5892bd36ecf19289ee","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2017-02-07T09:16:46Z","title_canon_sha256":"a95a4d1d0b03f1401fc9595b03fcfa25bf00526daf34580a62ee179ed01a9839"},"schema_version":"1.0","source":{"id":"1702.01932","kind":"arxiv","version":2}},"canonical_sha256":"eda23fe4b6ccffa6394319ce3a0905e028fd96304b2453a2a797e5858cb2eb03","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eda23fe4b6ccffa6394319ce3a0905e028fd96304b2453a2a797e5858cb2eb03","first_computed_at":"2026-05-18T00:00:35.623370Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:00:35.623370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gu1cTGKD9FYzKilapyiMEpCf5nqbSD5zcj+OvdKu03Q3i6kK2lc5Z7bTXDsmBYCxdnDWvGFAUgUEO2z5XRe8Ag==","signature_status":"signed_v1","signed_at":"2026-05-18T00:00:35.623948Z","signed_message":"canonical_sha256_bytes"},"source_id":"1702.01932","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:319028f9e177db2db88217723f7b598230dfd1bdcaa45c903837b1671275ed9a","sha256:a82d75ae7310046ad71e9f8f81426a8392884406d18f2f30e4e8ae41d518c2a7"],"state_sha256":"9f75bbbbeb6e55c0b5e2663d6f509da0ac64a0a7914250d1093d88b999194167"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"58nhvOPMF3e5Z/OnQ7mL7F9So0bgBXNMurf4d8+mpJer5uhWkvLevmR9QSDmT80/zcG4D0rJgCmeS6S3pLFODQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T18:48:34.812945Z","bundle_sha256":"b6e7aeae235ef74a9100f927cacbfc7c440efcc29f58a59a422336f23a1a1b23"}}