{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:HPZOAI65BBFQJ6WJICPMU3OB7W","short_pith_number":"pith:HPZOAI65","canonical_record":{"source":{"id":"1607.00070","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-30T22:51:00Z","cross_cats_sorted":[],"title_canon_sha256":"edc452e6de4ca58efa59f00b3fe4e29289b0bd4cb27e86532705c48360a9a017","abstract_canon_sha256":"5fc074a30c538b7851cf5db699a8dda937ba06d205833a8c4adbee39f91ad8c1"},"schema_version":"1.0"},"canonical_sha256":"3bf2e023dd084b04fac9409eca6dc1fd980305aec5899246e8ad4770a7ac7ce3","source":{"kind":"arxiv","id":"1607.00070","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.00070","created_at":"2026-05-18T01:11:38Z"},{"alias_kind":"arxiv_version","alias_value":"1607.00070v1","created_at":"2026-05-18T01:11:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.00070","created_at":"2026-05-18T01:11:38Z"},{"alias_kind":"pith_short_12","alias_value":"HPZOAI65BBFQ","created_at":"2026-05-18T12:30:19Z"},{"alias_kind":"pith_short_16","alias_value":"HPZOAI65BBFQJ6WJ","created_at":"2026-05-18T12:30:19Z"},{"alias_kind":"pith_short_8","alias_value":"HPZOAI65","created_at":"2026-05-18T12:30:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:HPZOAI65BBFQJ6WJICPMU3OB7W","target":"record","payload":{"canonical_record":{"source":{"id":"1607.00070","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-30T22:51:00Z","cross_cats_sorted":[],"title_canon_sha256":"edc452e6de4ca58efa59f00b3fe4e29289b0bd4cb27e86532705c48360a9a017","abstract_canon_sha256":"5fc074a30c538b7851cf5db699a8dda937ba06d205833a8c4adbee39f91ad8c1"},"schema_version":"1.0"},"canonical_sha256":"3bf2e023dd084b04fac9409eca6dc1fd980305aec5899246e8ad4770a7ac7ce3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:11:38.096125Z","signature_b64":"CQeeT7Ee0rkw2a4Z5oe8Tx+R06u1ONFnYhj6hYCHyA4S29wyTZQAoufAgsqzXhc8nLetYTino7kJXqUfJaq7Cg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3bf2e023dd084b04fac9409eca6dc1fd980305aec5899246e8ad4770a7ac7ce3","last_reissued_at":"2026-05-18T01:11:38.095774Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:11:38.095774Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1607.00070","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":"2026-05-18T01:11:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IzFTNYu9+tR3lzQJ62JObSlPfV4TrlZTTSNOacykUyi5AUEn46xtwXeNlk4huDwexaVaUuH49FlpfRHZxz82Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T16:52:20.365677Z"},"content_sha256":"3970e45bb9ae814c610625bacb386675743a9d8b2e14d986065777c765de6564","schema_version":"1.0","event_id":"sha256:3970e45bb9ae814c610625bacb386675743a9d8b2e14d986065777c765de6564"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:HPZOAI65BBFQJ6WJICPMU3OB7W","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Sequence-to-Sequence Model for User Simulation in Spoken Dialogue Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jing He, Kaheer Suleman, Layla El Asri","submitted_at":"2016-06-30T22:51:00Z","abstract_excerpt":"User simulation is essential for generating enough data to train a statistical spoken dialogue system. Previous models for user simulation suffer from several drawbacks, such as the inability to take dialogue history into account, the need of rigid structure to ensure coherent user behaviour, heavy dependence on a specific domain, the inability to output several user intentions during one dialogue turn, or the requirement of a summarized action space for tractability. This paper introduces a data-driven user simulator based on an encoder-decoder recurrent neural network. The model takes as inp"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.00070","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":""},"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":"2026-05-18T01:11:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zvIEVWel8KA5xSlyIgyqaXNCvarA1Wfe++HFQ0Br/ENo2uUNnfS8b1izr1QONxeAviIclZR7maJSbd5bM/D8AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-27T16:52:20.366361Z"},"content_sha256":"2bfb7aaf45c572b979f65efe24d046bfcedb70bfb04fe07c58030cf5524a9793","schema_version":"1.0","event_id":"sha256:2bfb7aaf45c572b979f65efe24d046bfcedb70bfb04fe07c58030cf5524a9793"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HPZOAI65BBFQJ6WJICPMU3OB7W/bundle.json","state_url":"https://pith.science/pith/HPZOAI65BBFQJ6WJICPMU3OB7W/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HPZOAI65BBFQJ6WJICPMU3OB7W/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":"2026-05-27T16:52:20Z","links":{"resolver":"https://pith.science/pith/HPZOAI65BBFQJ6WJICPMU3OB7W","bundle":"https://pith.science/pith/HPZOAI65BBFQJ6WJICPMU3OB7W/bundle.json","state":"https://pith.science/pith/HPZOAI65BBFQJ6WJICPMU3OB7W/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HPZOAI65BBFQJ6WJICPMU3OB7W/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:HPZOAI65BBFQJ6WJICPMU3OB7W","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":"5fc074a30c538b7851cf5db699a8dda937ba06d205833a8c4adbee39f91ad8c1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-30T22:51:00Z","title_canon_sha256":"edc452e6de4ca58efa59f00b3fe4e29289b0bd4cb27e86532705c48360a9a017"},"schema_version":"1.0","source":{"id":"1607.00070","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1607.00070","created_at":"2026-05-18T01:11:38Z"},{"alias_kind":"arxiv_version","alias_value":"1607.00070v1","created_at":"2026-05-18T01:11:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1607.00070","created_at":"2026-05-18T01:11:38Z"},{"alias_kind":"pith_short_12","alias_value":"HPZOAI65BBFQ","created_at":"2026-05-18T12:30:19Z"},{"alias_kind":"pith_short_16","alias_value":"HPZOAI65BBFQJ6WJ","created_at":"2026-05-18T12:30:19Z"},{"alias_kind":"pith_short_8","alias_value":"HPZOAI65","created_at":"2026-05-18T12:30:19Z"}],"graph_snapshots":[{"event_id":"sha256:2bfb7aaf45c572b979f65efe24d046bfcedb70bfb04fe07c58030cf5524a9793","target":"graph","created_at":"2026-05-18T01:11:38Z","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":"User simulation is essential for generating enough data to train a statistical spoken dialogue system. Previous models for user simulation suffer from several drawbacks, such as the inability to take dialogue history into account, the need of rigid structure to ensure coherent user behaviour, heavy dependence on a specific domain, the inability to output several user intentions during one dialogue turn, or the requirement of a summarized action space for tractability. This paper introduces a data-driven user simulator based on an encoder-decoder recurrent neural network. The model takes as inp","authors_text":"Jing He, Kaheer Suleman, Layla El Asri","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-30T22:51:00Z","title":"A Sequence-to-Sequence Model for User Simulation in Spoken Dialogue Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1607.00070","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":"sha256:3970e45bb9ae814c610625bacb386675743a9d8b2e14d986065777c765de6564","target":"record","created_at":"2026-05-18T01:11:38Z","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":"5fc074a30c538b7851cf5db699a8dda937ba06d205833a8c4adbee39f91ad8c1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2016-06-30T22:51:00Z","title_canon_sha256":"edc452e6de4ca58efa59f00b3fe4e29289b0bd4cb27e86532705c48360a9a017"},"schema_version":"1.0","source":{"id":"1607.00070","kind":"arxiv","version":1}},"canonical_sha256":"3bf2e023dd084b04fac9409eca6dc1fd980305aec5899246e8ad4770a7ac7ce3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3bf2e023dd084b04fac9409eca6dc1fd980305aec5899246e8ad4770a7ac7ce3","first_computed_at":"2026-05-18T01:11:38.095774Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:11:38.095774Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CQeeT7Ee0rkw2a4Z5oe8Tx+R06u1ONFnYhj6hYCHyA4S29wyTZQAoufAgsqzXhc8nLetYTino7kJXqUfJaq7Cg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:11:38.096125Z","signed_message":"canonical_sha256_bytes"},"source_id":"1607.00070","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3970e45bb9ae814c610625bacb386675743a9d8b2e14d986065777c765de6564","sha256:2bfb7aaf45c572b979f65efe24d046bfcedb70bfb04fe07c58030cf5524a9793"],"state_sha256":"81df04d3b615773f3232cf4f89b42b8241c1a667e8ffcd4b3bb4c55aa2132ffd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Pf1CVKqOl1yQlaTENpImBnHuRK2sFUqRzbJrYGSAHrxSeB9O/EzXxigOpxxLTBFdEt5EugQGP21/bvh6xVGoDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-27T16:52:20.370011Z","bundle_sha256":"d2ccbe75a991d19e687083bd95dd9821c05df547f622ee3fd792e815b0b3c139"}}