{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:KJYYWQFLD3N5IJGTSLYUHLMRE2","short_pith_number":"pith:KJYYWQFL","canonical_record":{"source":{"id":"2210.05146","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-11T04:55:16Z","cross_cats_sorted":[],"title_canon_sha256":"112ff423a87cbeeb2c3c8f26bea64891f22ed3208f72ad479457cfad188dbcb1","abstract_canon_sha256":"8ff9d927771b759f269c186c075ab12a1a491230005e20c65ed3077764bcd73a"},"schema_version":"1.0"},"canonical_sha256":"52718b40ab1edbd424d392f143ad9126861dac49b79a3e2f7ba1a25166adecd3","source":{"kind":"arxiv","id":"2210.05146","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.05146","created_at":"2026-07-05T05:05:13Z"},{"alias_kind":"arxiv_version","alias_value":"2210.05146v1","created_at":"2026-07-05T05:05:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.05146","created_at":"2026-07-05T05:05:13Z"},{"alias_kind":"pith_short_12","alias_value":"KJYYWQFLD3N5","created_at":"2026-07-05T05:05:13Z"},{"alias_kind":"pith_short_16","alias_value":"KJYYWQFLD3N5IJGT","created_at":"2026-07-05T05:05:13Z"},{"alias_kind":"pith_short_8","alias_value":"KJYYWQFL","created_at":"2026-07-05T05:05:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:KJYYWQFLD3N5IJGTSLYUHLMRE2","target":"record","payload":{"canonical_record":{"source":{"id":"2210.05146","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-11T04:55:16Z","cross_cats_sorted":[],"title_canon_sha256":"112ff423a87cbeeb2c3c8f26bea64891f22ed3208f72ad479457cfad188dbcb1","abstract_canon_sha256":"8ff9d927771b759f269c186c075ab12a1a491230005e20c65ed3077764bcd73a"},"schema_version":"1.0"},"canonical_sha256":"52718b40ab1edbd424d392f143ad9126861dac49b79a3e2f7ba1a25166adecd3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:05:13.459402Z","signature_b64":"5KehGr3Ya7E83z/WCuWTMYn9T8Ft2wlfmXeirafV1ewPfytPswfZdUPe9yxfSt156WHXLb6CMvgpJCP+3u06Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"52718b40ab1edbd424d392f143ad9126861dac49b79a3e2f7ba1a25166adecd3","last_reissued_at":"2026-07-05T05:05:13.458949Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:05:13.458949Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.05146","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":"2026-07-05T05:05:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xpiCzTR18KmeXNDUqWnn+M0gm8AWXTUPCaxud4RQTZTdvje5wJkVc8zEhApQy6kMIupuknMonZnNn0iN/nzaBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T07:31:14.833505Z"},"content_sha256":"269d9d20572897427619494870295c4fbb5b0c645ddb379b7a45cadd4c3fbd8b","schema_version":"1.0","event_id":"sha256:269d9d20572897427619494870295c4fbb5b0c645ddb379b7a45cadd4c3fbd8b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:KJYYWQFLD3N5IJGTSLYUHLMRE2","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CSS: Combining Self-training and Self-supervised Learning for Few-shot Dialogue State Tracking","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Haipeng Sun, Haoning Zhang, Huaishao Luo, Junwei Bao, Shuguang Cui, Wenye Li","submitted_at":"2022-10-11T04:55:16Z","abstract_excerpt":"Few-shot dialogue state tracking (DST) is a realistic problem that trains the DST model with limited labeled data. Existing few-shot methods mainly transfer knowledge learned from external labeled dialogue data (e.g., from question answering, dialogue summarization, machine reading comprehension tasks, etc.) into DST, whereas collecting a large amount of external labeled data is laborious, and the external data may not effectively contribute to the DST-specific task. In this paper, we propose a few-shot DST framework called CSS, which Combines Self-training and Self-supervised learning methods"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.05146","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2210.05146/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":"2026-07-05T05:05:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OM+c97bi/0eRIFu1goRevA1gdFsER4Z6xxJGDEkRqJf/3qdnx0OL1LgjjBOSsCUTXpxnRMaeIazV9/GeUka5CA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T07:31:14.834398Z"},"content_sha256":"ed7cd000ea9930d33f76ec7ddd5be3111a375a4fe4e996721755a67ef3fcdfcf","schema_version":"1.0","event_id":"sha256:ed7cd000ea9930d33f76ec7ddd5be3111a375a4fe4e996721755a67ef3fcdfcf"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KJYYWQFLD3N5IJGTSLYUHLMRE2/bundle.json","state_url":"https://pith.science/pith/KJYYWQFLD3N5IJGTSLYUHLMRE2/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KJYYWQFLD3N5IJGTSLYUHLMRE2/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":"2026-08-14T07:31:14Z","links":{"resolver":"https://pith.science/pith/KJYYWQFLD3N5IJGTSLYUHLMRE2","bundle":"https://pith.science/pith/KJYYWQFLD3N5IJGTSLYUHLMRE2/bundle.json","state":"https://pith.science/pith/KJYYWQFLD3N5IJGTSLYUHLMRE2/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KJYYWQFLD3N5IJGTSLYUHLMRE2/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:KJYYWQFLD3N5IJGTSLYUHLMRE2","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":"8ff9d927771b759f269c186c075ab12a1a491230005e20c65ed3077764bcd73a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-11T04:55:16Z","title_canon_sha256":"112ff423a87cbeeb2c3c8f26bea64891f22ed3208f72ad479457cfad188dbcb1"},"schema_version":"1.0","source":{"id":"2210.05146","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.05146","created_at":"2026-07-05T05:05:13Z"},{"alias_kind":"arxiv_version","alias_value":"2210.05146v1","created_at":"2026-07-05T05:05:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.05146","created_at":"2026-07-05T05:05:13Z"},{"alias_kind":"pith_short_12","alias_value":"KJYYWQFLD3N5","created_at":"2026-07-05T05:05:13Z"},{"alias_kind":"pith_short_16","alias_value":"KJYYWQFLD3N5IJGT","created_at":"2026-07-05T05:05:13Z"},{"alias_kind":"pith_short_8","alias_value":"KJYYWQFL","created_at":"2026-07-05T05:05:13Z"}],"graph_snapshots":[{"event_id":"sha256:ed7cd000ea9930d33f76ec7ddd5be3111a375a4fe4e996721755a67ef3fcdfcf","target":"graph","created_at":"2026-07-05T05:05:13Z","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/2210.05146/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Few-shot dialogue state tracking (DST) is a realistic problem that trains the DST model with limited labeled data. Existing few-shot methods mainly transfer knowledge learned from external labeled dialogue data (e.g., from question answering, dialogue summarization, machine reading comprehension tasks, etc.) into DST, whereas collecting a large amount of external labeled data is laborious, and the external data may not effectively contribute to the DST-specific task. In this paper, we propose a few-shot DST framework called CSS, which Combines Self-training and Self-supervised learning methods","authors_text":"Haipeng Sun, Haoning Zhang, Huaishao Luo, Junwei Bao, Shuguang Cui, Wenye Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-11T04:55:16Z","title":"CSS: Combining Self-training and Self-supervised Learning for Few-shot Dialogue State Tracking"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.05146","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":"sha256:269d9d20572897427619494870295c4fbb5b0c645ddb379b7a45cadd4c3fbd8b","target":"record","created_at":"2026-07-05T05:05:13Z","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":"8ff9d927771b759f269c186c075ab12a1a491230005e20c65ed3077764bcd73a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2022-10-11T04:55:16Z","title_canon_sha256":"112ff423a87cbeeb2c3c8f26bea64891f22ed3208f72ad479457cfad188dbcb1"},"schema_version":"1.0","source":{"id":"2210.05146","kind":"arxiv","version":1}},"canonical_sha256":"52718b40ab1edbd424d392f143ad9126861dac49b79a3e2f7ba1a25166adecd3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"52718b40ab1edbd424d392f143ad9126861dac49b79a3e2f7ba1a25166adecd3","first_computed_at":"2026-07-05T05:05:13.458949Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:05:13.458949Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5KehGr3Ya7E83z/WCuWTMYn9T8Ft2wlfmXeirafV1ewPfytPswfZdUPe9yxfSt156WHXLb6CMvgpJCP+3u06Cw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:05:13.459402Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.05146","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:269d9d20572897427619494870295c4fbb5b0c645ddb379b7a45cadd4c3fbd8b","sha256:ed7cd000ea9930d33f76ec7ddd5be3111a375a4fe4e996721755a67ef3fcdfcf"],"state_sha256":"1e4d703d4bedc9d7b8eb4b3997ed0584560441cb30624247a9917476c0a4210f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6JxeeQmk6gRavsaGOeHParDjUHXdjbgevT6dGp9TjlnG2OutHl5UUy5L+ak8ij9anI/2JpOhPfa4ki+gfjt4Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T07:31:14.840917Z","bundle_sha256":"9649f735e38456c5b59a14516622e1e5dae4e4b91eb01e91e9f2e6229d3fc888"}}