{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:KT5ZUZMMFHZMMUEOWDRURYKNO6","short_pith_number":"pith:KT5ZUZMM","canonical_record":{"source":{"id":"1902.11205","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-02-28T16:45:19Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"6b527d4651fd5003b1472a5db911f2195578655eb8b6329c656390a4fd60fb7e","abstract_canon_sha256":"c1749fd0f035d808f980d6258987245270ac222a87311588b0124fc709dc0157"},"schema_version":"1.0"},"canonical_sha256":"54fb9a658c29f2c6508eb0e348e14d779187c50ec2617378902405c34dd3b082","source":{"kind":"arxiv","id":"1902.11205","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.11205","created_at":"2026-05-17T23:49:21Z"},{"alias_kind":"arxiv_version","alias_value":"1902.11205v3","created_at":"2026-05-17T23:49:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.11205","created_at":"2026-05-17T23:49:21Z"},{"alias_kind":"pith_short_12","alias_value":"KT5ZUZMMFHZM","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"KT5ZUZMMFHZMMUEO","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"KT5ZUZMM","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:KT5ZUZMMFHZMMUEOWDRURYKNO6","target":"record","payload":{"canonical_record":{"source":{"id":"1902.11205","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-02-28T16:45:19Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"6b527d4651fd5003b1472a5db911f2195578655eb8b6329c656390a4fd60fb7e","abstract_canon_sha256":"c1749fd0f035d808f980d6258987245270ac222a87311588b0124fc709dc0157"},"schema_version":"1.0"},"canonical_sha256":"54fb9a658c29f2c6508eb0e348e14d779187c50ec2617378902405c34dd3b082","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:49:21.829614Z","signature_b64":"0VmfDWusGVVgHM4GKk2+IE1awYQWH3BdbUGTLZDAto1sjWo6w/YTRqXnLn2MWhogF91825467dnCqsS1On7yAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"54fb9a658c29f2c6508eb0e348e14d779187c50ec2617378902405c34dd3b082","last_reissued_at":"2026-05-17T23:49:21.829079Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:49:21.829079Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1902.11205","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":"2026-05-17T23:49:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vhY/wt3+ZylcuLnycvFNHVXBnpCEVogZyT4pYmr0Clw6WNO3f3b7cEBpD73jlEzYxnimAzYy7VLnYyvs/FklCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T18:01:50.957609Z"},"content_sha256":"29ef5c41a974738d5abeee9575868e49bafeb2eabbe4d6b580026ea360d9d3aa","schema_version":"1.0","event_id":"sha256:29ef5c41a974738d5abeee9575868e49bafeb2eabbe4d6b580026ea360d9d3aa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:KT5ZUZMMFHZMMUEOWDRURYKNO6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Jointly Optimizing Diversity and Relevance in Neural Response Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Bill Dolan, Chris Brockett, Jianfeng Gao, Michel Galley, Sungjin Lee, Xiang Gao, Yizhe Zhang","submitted_at":"2019-02-28T16:45:19Z","abstract_excerpt":"Although recent neural conversation models have shown great potential, they often generate bland and generic responses. While various approaches have been explored to diversify the output of the conversation model, the improvement often comes at the cost of decreased relevance. In this paper, we propose a SpaceFusion model to jointly optimize diversity and relevance that essentially fuses the latent space of a sequence-to-sequence model and that of an autoencoder model by leveraging novel regularization terms. As a result, our approach induces a latent space in which the distance and direction"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.11205","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":""},"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":"2026-05-17T23:49:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vEwlJhHricdfhgZ4gfzAjNn3t8yMPsIKVWXuVhOvBwVS36fP9GSo5aoF30kOFjjvkycoQhG3AEZWH3rrRDenDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T18:01:50.958274Z"},"content_sha256":"54849059573251be70b2c93e56698a7b04f4f8ece3a88bbe193a4a9fa458c1a8","schema_version":"1.0","event_id":"sha256:54849059573251be70b2c93e56698a7b04f4f8ece3a88bbe193a4a9fa458c1a8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KT5ZUZMMFHZMMUEOWDRURYKNO6/bundle.json","state_url":"https://pith.science/pith/KT5ZUZMMFHZMMUEOWDRURYKNO6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KT5ZUZMMFHZMMUEOWDRURYKNO6/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":"2026-05-25T18:01:50Z","links":{"resolver":"https://pith.science/pith/KT5ZUZMMFHZMMUEOWDRURYKNO6","bundle":"https://pith.science/pith/KT5ZUZMMFHZMMUEOWDRURYKNO6/bundle.json","state":"https://pith.science/pith/KT5ZUZMMFHZMMUEOWDRURYKNO6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KT5ZUZMMFHZMMUEOWDRURYKNO6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:KT5ZUZMMFHZMMUEOWDRURYKNO6","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":"c1749fd0f035d808f980d6258987245270ac222a87311588b0124fc709dc0157","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-02-28T16:45:19Z","title_canon_sha256":"6b527d4651fd5003b1472a5db911f2195578655eb8b6329c656390a4fd60fb7e"},"schema_version":"1.0","source":{"id":"1902.11205","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1902.11205","created_at":"2026-05-17T23:49:21Z"},{"alias_kind":"arxiv_version","alias_value":"1902.11205v3","created_at":"2026-05-17T23:49:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1902.11205","created_at":"2026-05-17T23:49:21Z"},{"alias_kind":"pith_short_12","alias_value":"KT5ZUZMMFHZM","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"KT5ZUZMMFHZMMUEO","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"KT5ZUZMM","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:54849059573251be70b2c93e56698a7b04f4f8ece3a88bbe193a4a9fa458c1a8","target":"graph","created_at":"2026-05-17T23:49:21Z","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":"Although recent neural conversation models have shown great potential, they often generate bland and generic responses. While various approaches have been explored to diversify the output of the conversation model, the improvement often comes at the cost of decreased relevance. In this paper, we propose a SpaceFusion model to jointly optimize diversity and relevance that essentially fuses the latent space of a sequence-to-sequence model and that of an autoencoder model by leveraging novel regularization terms. As a result, our approach induces a latent space in which the distance and direction","authors_text":"Bill Dolan, Chris Brockett, Jianfeng Gao, Michel Galley, Sungjin Lee, Xiang Gao, Yizhe Zhang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-02-28T16:45:19Z","title":"Jointly Optimizing Diversity and Relevance in Neural Response Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1902.11205","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":"sha256:29ef5c41a974738d5abeee9575868e49bafeb2eabbe4d6b580026ea360d9d3aa","target":"record","created_at":"2026-05-17T23:49:21Z","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":"c1749fd0f035d808f980d6258987245270ac222a87311588b0124fc709dc0157","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2019-02-28T16:45:19Z","title_canon_sha256":"6b527d4651fd5003b1472a5db911f2195578655eb8b6329c656390a4fd60fb7e"},"schema_version":"1.0","source":{"id":"1902.11205","kind":"arxiv","version":3}},"canonical_sha256":"54fb9a658c29f2c6508eb0e348e14d779187c50ec2617378902405c34dd3b082","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"54fb9a658c29f2c6508eb0e348e14d779187c50ec2617378902405c34dd3b082","first_computed_at":"2026-05-17T23:49:21.829079Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:49:21.829079Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0VmfDWusGVVgHM4GKk2+IE1awYQWH3BdbUGTLZDAto1sjWo6w/YTRqXnLn2MWhogF91825467dnCqsS1On7yAw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:49:21.829614Z","signed_message":"canonical_sha256_bytes"},"source_id":"1902.11205","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:29ef5c41a974738d5abeee9575868e49bafeb2eabbe4d6b580026ea360d9d3aa","sha256:54849059573251be70b2c93e56698a7b04f4f8ece3a88bbe193a4a9fa458c1a8"],"state_sha256":"9f55ac72ba82a5c3575e8ae39a3276f317a597d267d56ecee4f5f083cff4685f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jKNN+Ewx7qRufpIfACkAx7JoHc7Soz7rILImTetxTUzdSM3HUT1fjDJIR6ydxUcU3uF96Y7NhHgdKZaGHBb1Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T18:01:50.961039Z","bundle_sha256":"4263d2e451744776b6940fed105c0b3ffa31b4265392c8f805c52070c87b688f"}}