{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:ISI4CCSC3HJEYMXERLZA7VE3FH","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":"247042b8461373e26508e775ffc83c0c9349766c0e91ddd46ba0954d38f46a73","cross_cats_sorted":["cs.AI","cs.IR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-05-10T14:07:49Z","title_canon_sha256":"5804b0fa5376dc539b3bc2708a5a53e5412f2e042759db917fd28ae84f16dda8"},"schema_version":"1.0","source":{"id":"2105.04387","kind":"arxiv","version":5}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.04387","created_at":"2026-07-05T04:09:56Z"},{"alias_kind":"arxiv_version","alias_value":"2105.04387v5","created_at":"2026-07-05T04:09:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.04387","created_at":"2026-07-05T04:09:56Z"},{"alias_kind":"pith_short_12","alias_value":"ISI4CCSC3HJE","created_at":"2026-07-05T04:09:56Z"},{"alias_kind":"pith_short_16","alias_value":"ISI4CCSC3HJEYMXE","created_at":"2026-07-05T04:09:56Z"},{"alias_kind":"pith_short_8","alias_value":"ISI4CCSC","created_at":"2026-07-05T04:09:56Z"}],"graph_snapshots":[{"event_id":"sha256:1698036c28c528cb6a3d0403d8e335475d68ab30acf37757c96a71307ce7749a","target":"graph","created_at":"2026-07-05T04:09:56Z","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/2105.04387/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Dialogue systems are a popular natural language processing (NLP) task as it is promising in real-life applications. It is also a complicated task since many NLP tasks deserving study are involved. As a result, a multitude of novel works on this task are carried out, and most of them are deep learning based due to the outstanding performance. In this survey, we mainly focus on the deep learning based dialogue systems. We comprehensively review state-of-the-art research outcomes in dialogue systems and analyze them from two angles: model type and system type. Specifically, from the angle of mode","authors_text":"Erik Cambria, Fuzhao Xue, Jinjie Ni, Tom Young, Vlad Pandelea","cross_cats":["cs.AI","cs.IR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-05-10T14:07:49Z","title":"Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.04387","kind":"arxiv","version":5},"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:ee57c287ca24a684a849b7aeb700a71712deb5a299b7112e129ade55d08443a3","target":"record","created_at":"2026-07-05T04:09:56Z","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":"247042b8461373e26508e775ffc83c0c9349766c0e91ddd46ba0954d38f46a73","cross_cats_sorted":["cs.AI","cs.IR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-05-10T14:07:49Z","title_canon_sha256":"5804b0fa5376dc539b3bc2708a5a53e5412f2e042759db917fd28ae84f16dda8"},"schema_version":"1.0","source":{"id":"2105.04387","kind":"arxiv","version":5}},"canonical_sha256":"4491c10a42d9d24c32e48af20fd49b29d1f6c670d5697de4746db29a484c029d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4491c10a42d9d24c32e48af20fd49b29d1f6c670d5697de4746db29a484c029d","first_computed_at":"2026-07-05T04:09:56.467999Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:09:56.467999Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+jc5qYpufFwbJAWtLBw29wlm3NEj4jWrVEBoiL94JdHXLrlz++FvFI6TPNuBBCm5S4SN4U93ibRPEAiRy2MtAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:09:56.468431Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.04387","source_kind":"arxiv","source_version":5}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ee57c287ca24a684a849b7aeb700a71712deb5a299b7112e129ade55d08443a3","sha256:1698036c28c528cb6a3d0403d8e335475d68ab30acf37757c96a71307ce7749a"],"state_sha256":"db62419961bdd6fd24e96e9e8f455beccedb9b1a93d1f5b0e014aaff5812a025"}