{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:OCZ3Q3YH6L4PITPK25PYLVFEVD","short_pith_number":"pith:OCZ3Q3YH","canonical_record":{"source":{"id":"2108.13990","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-08-31T17:27:59Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"fd7efcd3a016011a6c1b649a0c7e461507a23493b689237495223d15fc79b077","abstract_canon_sha256":"dd810b8f742cf4df50fe089684e4ca1c886cb44f9ebd95ce943929196e9dcd8e"},"schema_version":"1.0"},"canonical_sha256":"70b3b86f07f2f8f44dead75f85d4a4a8c3d7e971584ed05b3cee8352f1b31483","source":{"kind":"arxiv","id":"2108.13990","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2108.13990","created_at":"2026-07-05T03:12:39Z"},{"alias_kind":"arxiv_version","alias_value":"2108.13990v2","created_at":"2026-07-05T03:12:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.13990","created_at":"2026-07-05T03:12:39Z"},{"alias_kind":"pith_short_12","alias_value":"OCZ3Q3YH6L4P","created_at":"2026-07-05T03:12:39Z"},{"alias_kind":"pith_short_16","alias_value":"OCZ3Q3YH6L4PITPK","created_at":"2026-07-05T03:12:39Z"},{"alias_kind":"pith_short_8","alias_value":"OCZ3Q3YH","created_at":"2026-07-05T03:12:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:OCZ3Q3YH6L4PITPK25PYLVFEVD","target":"record","payload":{"canonical_record":{"source":{"id":"2108.13990","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-08-31T17:27:59Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"fd7efcd3a016011a6c1b649a0c7e461507a23493b689237495223d15fc79b077","abstract_canon_sha256":"dd810b8f742cf4df50fe089684e4ca1c886cb44f9ebd95ce943929196e9dcd8e"},"schema_version":"1.0"},"canonical_sha256":"70b3b86f07f2f8f44dead75f85d4a4a8c3d7e971584ed05b3cee8352f1b31483","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:12:39.711407Z","signature_b64":"luDixbh+rDksgTRk5TnmF6BBsmnJIc34/tfLz48n3PxFfj/1g0hxHrfiNhyfmqmDS1TBHTkWBrz//OromnHKCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"70b3b86f07f2f8f44dead75f85d4a4a8c3d7e971584ed05b3cee8352f1b31483","last_reissued_at":"2026-07-05T03:12:39.710998Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:12:39.710998Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2108.13990","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":"2026-07-05T03:12:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iEqyRy+K1HuqxnjSmAmSCaArAWbFmaVMh4E8kb2yyMX8WOQCEGb067HAlfgZX/2yUZJXCtUNOfnzz4cw7sNfBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T21:38:53.208799Z"},"content_sha256":"901d2b7b6b43ada061b6b3a52c78e71175a89d69c9003e90a4312010ca302a01","schema_version":"1.0","event_id":"sha256:901d2b7b6b43ada061b6b3a52c78e71175a89d69c9003e90a4312010ca302a01"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:OCZ3Q3YH6L4PITPK25PYLVFEVD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Effective Sequence-to-Sequence Dialogue State Tracking","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Jeffrey Zhao, Mahdis Mahdieh, Ye Zhang, Yonghui Wu, Yuan Cao","submitted_at":"2021-08-31T17:27:59Z","abstract_excerpt":"Sequence-to-sequence models have been applied to a wide variety of NLP tasks, but how to properly use them for dialogue state tracking has not been systematically investigated. In this paper, we study this problem from the perspectives of pre-training objectives as well as the formats of context representations. We demonstrate that the choice of pre-training objective makes a significant difference to the state tracking quality. In particular, we find that masked span prediction is more effective than auto-regressive language modeling. We also explore using Pegasus, a span prediction-based pre"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.13990","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2108.13990/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2026-07-05T03:12:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"jH+N7ricf95Fqyp7kXEcA4hUwy05AyKNDhcpZM3mnxmx+MwuLqQtQ7e0Q/TRZzT/2Gp9v/lOGOs1YyQbsG8IDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T21:38:53.209175Z"},"content_sha256":"e99c500d2e5bf476675d7210da1ebe42808a637f6f5337ffb632c14abc3a4865","schema_version":"1.0","event_id":"sha256:e99c500d2e5bf476675d7210da1ebe42808a637f6f5337ffb632c14abc3a4865"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OCZ3Q3YH6L4PITPK25PYLVFEVD/bundle.json","state_url":"https://pith.science/pith/OCZ3Q3YH6L4PITPK25PYLVFEVD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OCZ3Q3YH6L4PITPK25PYLVFEVD/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":"2026-08-04T21:38:53Z","links":{"resolver":"https://pith.science/pith/OCZ3Q3YH6L4PITPK25PYLVFEVD","bundle":"https://pith.science/pith/OCZ3Q3YH6L4PITPK25PYLVFEVD/bundle.json","state":"https://pith.science/pith/OCZ3Q3YH6L4PITPK25PYLVFEVD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OCZ3Q3YH6L4PITPK25PYLVFEVD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:OCZ3Q3YH6L4PITPK25PYLVFEVD","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":"dd810b8f742cf4df50fe089684e4ca1c886cb44f9ebd95ce943929196e9dcd8e","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-08-31T17:27:59Z","title_canon_sha256":"fd7efcd3a016011a6c1b649a0c7e461507a23493b689237495223d15fc79b077"},"schema_version":"1.0","source":{"id":"2108.13990","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2108.13990","created_at":"2026-07-05T03:12:39Z"},{"alias_kind":"arxiv_version","alias_value":"2108.13990v2","created_at":"2026-07-05T03:12:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.13990","created_at":"2026-07-05T03:12:39Z"},{"alias_kind":"pith_short_12","alias_value":"OCZ3Q3YH6L4P","created_at":"2026-07-05T03:12:39Z"},{"alias_kind":"pith_short_16","alias_value":"OCZ3Q3YH6L4PITPK","created_at":"2026-07-05T03:12:39Z"},{"alias_kind":"pith_short_8","alias_value":"OCZ3Q3YH","created_at":"2026-07-05T03:12:39Z"}],"graph_snapshots":[{"event_id":"sha256:e99c500d2e5bf476675d7210da1ebe42808a637f6f5337ffb632c14abc3a4865","target":"graph","created_at":"2026-07-05T03:12:39Z","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/2108.13990/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sequence-to-sequence models have been applied to a wide variety of NLP tasks, but how to properly use them for dialogue state tracking has not been systematically investigated. In this paper, we study this problem from the perspectives of pre-training objectives as well as the formats of context representations. We demonstrate that the choice of pre-training objective makes a significant difference to the state tracking quality. In particular, we find that masked span prediction is more effective than auto-regressive language modeling. We also explore using Pegasus, a span prediction-based pre","authors_text":"Jeffrey Zhao, Mahdis Mahdieh, Ye Zhang, Yonghui Wu, Yuan Cao","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-08-31T17:27:59Z","title":"Effective Sequence-to-Sequence Dialogue State Tracking"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.13990","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":"sha256:901d2b7b6b43ada061b6b3a52c78e71175a89d69c9003e90a4312010ca302a01","target":"record","created_at":"2026-07-05T03:12:39Z","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":"dd810b8f742cf4df50fe089684e4ca1c886cb44f9ebd95ce943929196e9dcd8e","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-08-31T17:27:59Z","title_canon_sha256":"fd7efcd3a016011a6c1b649a0c7e461507a23493b689237495223d15fc79b077"},"schema_version":"1.0","source":{"id":"2108.13990","kind":"arxiv","version":2}},"canonical_sha256":"70b3b86f07f2f8f44dead75f85d4a4a8c3d7e971584ed05b3cee8352f1b31483","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"70b3b86f07f2f8f44dead75f85d4a4a8c3d7e971584ed05b3cee8352f1b31483","first_computed_at":"2026-07-05T03:12:39.710998Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:12:39.710998Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"luDixbh+rDksgTRk5TnmF6BBsmnJIc34/tfLz48n3PxFfj/1g0hxHrfiNhyfmqmDS1TBHTkWBrz//OromnHKCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T03:12:39.711407Z","signed_message":"canonical_sha256_bytes"},"source_id":"2108.13990","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:901d2b7b6b43ada061b6b3a52c78e71175a89d69c9003e90a4312010ca302a01","sha256:e99c500d2e5bf476675d7210da1ebe42808a637f6f5337ffb632c14abc3a4865"],"state_sha256":"6d1f59c971a15384fce50edb5d3d76d07f0420a0c014de521c2e4ef6f86172ee"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Kd49+xq/9zXbT/zLpvXJa6lvrtGec3PJr43L9swL8xagcb6mcXqC2EIc0osJlG7b64OUeLMssbX+aZBP3ykGCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T21:38:53.211933Z","bundle_sha256":"930506e0495b13457a00cf864b40ac135e345fc7d0409b9bed90900d8b65dbd2"}}