{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:5GSEL5XBBNFCEHSVQJJGB7ORNK","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":"c60f3b0e6a6e72e1b953fa6912f15683bb230ce0b0a6e765a503332f51235bb3","cross_cats_sorted":["cs.CL","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-16T08:40:47Z","title_canon_sha256":"ebf2c10773aa51167ca3f2e41e62e2fe90c0666fcf9d0bee2cb7edf235068feb"},"schema_version":"1.0","source":{"id":"1905.06597","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1905.06597","created_at":"2026-05-17T23:46:01Z"},{"alias_kind":"arxiv_version","alias_value":"1905.06597v1","created_at":"2026-05-17T23:46:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1905.06597","created_at":"2026-05-17T23:46:01Z"},{"alias_kind":"pith_short_12","alias_value":"5GSEL5XBBNFC","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_16","alias_value":"5GSEL5XBBNFCEHSV","created_at":"2026-05-18T12:33:10Z"},{"alias_kind":"pith_short_8","alias_value":"5GSEL5XB","created_at":"2026-05-18T12:33:10Z"}],"graph_snapshots":[{"event_id":"sha256:ee5323df81be4a9d87a8637a75800cc763364968868df91c67200285d144c991","target":"graph","created_at":"2026-05-17T23:46:01Z","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":"How to generate human like response is one of the most challenging tasks for artificial intelligence. In a real application, after reading the same post different people might write responses with positive or negative sentiment according to their own experiences and attitudes. To simulate this procedure, we propose a simple but effective dual-decoder model to generate response with a particular sentiment, by connecting two sentiment decoders to one encoder. To support this model training, we construct a new conversation dataset with the form of (post, resp1, resp2) where two responses contain ","authors_text":"Xiuyu Wu, Yunfang Wu","cross_cats":["cs.CL","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-16T08:40:47Z","title":"A Simple Dual-decoder Model for Generating Response with Sentiment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1905.06597","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:a4b78a5dca5aec0fff76d908fce74f4364c625d2bc75fd21d2795939ebb64560","target":"record","created_at":"2026-05-17T23:46:01Z","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":"c60f3b0e6a6e72e1b953fa6912f15683bb230ce0b0a6e765a503332f51235bb3","cross_cats_sorted":["cs.CL","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-05-16T08:40:47Z","title_canon_sha256":"ebf2c10773aa51167ca3f2e41e62e2fe90c0666fcf9d0bee2cb7edf235068feb"},"schema_version":"1.0","source":{"id":"1905.06597","kind":"arxiv","version":1}},"canonical_sha256":"e9a445f6e10b4a221e55825260fdd16a9a214c5fa21e58a24b893adc084057a8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e9a445f6e10b4a221e55825260fdd16a9a214c5fa21e58a24b893adc084057a8","first_computed_at":"2026-05-17T23:46:01.744613Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:46:01.744613Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yfshz45VBvol6tCcXbD4/NS36F6U3La5EphCUCOW09OFtk5V2a5gzQ6XRBkVRdqf/VK0e2HmoGGS+KL93/JvBQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:46:01.745200Z","signed_message":"canonical_sha256_bytes"},"source_id":"1905.06597","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a4b78a5dca5aec0fff76d908fce74f4364c625d2bc75fd21d2795939ebb64560","sha256:ee5323df81be4a9d87a8637a75800cc763364968868df91c67200285d144c991"],"state_sha256":"3372e10e8f568d5fcca85cee84f6590a9a9c86059e719e3d6240494248205422"}