{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:FOAREZ3TXEXGB3O7X2RM7DMOOZ","short_pith_number":"pith:FOAREZ3T","canonical_record":{"source":{"id":"2010.15025","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-10-28T15:00:09Z","cross_cats_sorted":["cs.CL","eess.AS"],"title_canon_sha256":"e358eeaecb88cead3c8c5a0976ffda1ffb476caafbf2ba7b6f418a8ccd31bb7c","abstract_canon_sha256":"dbc99aa8b9ac1ad4f350fb561451deaa220c550fe2df2b1ad7a15f1295e34abb"},"schema_version":"1.0"},"canonical_sha256":"2b81126773b92e60eddfbea2cf8d8e767724f0264f9ffcbd5810d718ed0b524c","source":{"kind":"arxiv","id":"2010.15025","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.15025","created_at":"2026-07-05T02:32:34Z"},{"alias_kind":"arxiv_version","alias_value":"2010.15025v2","created_at":"2026-07-05T02:32:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.15025","created_at":"2026-07-05T02:32:34Z"},{"alias_kind":"pith_short_12","alias_value":"FOAREZ3TXEXG","created_at":"2026-07-05T02:32:34Z"},{"alias_kind":"pith_short_16","alias_value":"FOAREZ3TXEXGB3O7","created_at":"2026-07-05T02:32:34Z"},{"alias_kind":"pith_short_8","alias_value":"FOAREZ3T","created_at":"2026-07-05T02:32:34Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:FOAREZ3TXEXGB3O7X2RM7DMOOZ","target":"record","payload":{"canonical_record":{"source":{"id":"2010.15025","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-10-28T15:00:09Z","cross_cats_sorted":["cs.CL","eess.AS"],"title_canon_sha256":"e358eeaecb88cead3c8c5a0976ffda1ffb476caafbf2ba7b6f418a8ccd31bb7c","abstract_canon_sha256":"dbc99aa8b9ac1ad4f350fb561451deaa220c550fe2df2b1ad7a15f1295e34abb"},"schema_version":"1.0"},"canonical_sha256":"2b81126773b92e60eddfbea2cf8d8e767724f0264f9ffcbd5810d718ed0b524c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:32:34.036825Z","signature_b64":"VauqEpSX+eSMdzvlkkObvDQMUIeLSbn7DtKZJEExM+DASWRCMHCCRZIlzmjrGSA8C1FQ1eTq5lQ4JaLdqJf+DQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2b81126773b92e60eddfbea2cf8d8e767724f0264f9ffcbd5810d718ed0b524c","last_reissued_at":"2026-07-05T02:32:34.036334Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:32:34.036334Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2010.15025","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":"2026-07-05T02:32:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9U1uewG5dniBYAERWQzR4sZkkk861qbx5r8f9P4yMcCMA2rjK2IGsbogaz6nCMfRQMIs2RV1nMAcOw8NFohhCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T13:00:10.355987Z"},"content_sha256":"5281d70fa239f501d9dc0a744dd5c3db5c4180b8f2c868226fe1ca053333e60c","schema_version":"1.0","event_id":"sha256:5281d70fa239f501d9dc0a744dd5c3db5c4180b8f2c868226fe1ca053333e60c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:FOAREZ3TXEXGB3O7X2RM7DMOOZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Non-Autoregressive Transformer ASR with CTC-Enhanced Decoder Input","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CL","eess.AS"],"primary_cat":"cs.SD","authors_text":"Chao Weng, Dan Su, Helen Meng, Xingchen Song, Yiheng Huang, Zhiyong Wu","submitted_at":"2020-10-28T15:00:09Z","abstract_excerpt":"Non-autoregressive (NAR) transformer models have achieved significantly inference speedup but at the cost of inferior accuracy compared to autoregressive (AR) models in automatic speech recognition (ASR). Most of the NAR transformers take a fixed-length sequence filled with MASK tokens or a redundant sequence copied from encoder states as decoder input, they cannot provide efficient target-side information thus leading to accuracy degradation. To address this problem, we propose a CTC-enhanced NAR transformer, which generates target sequence by refining predictions of the CTC module. Experimen"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.15025","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/2010.15025/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":"2026-07-05T02:32:34Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PeZxgwl6A/12eFqvPELBq2RUEeI4yLM54Eamm6QKpb3VvTe9KltRCpv8QMjWU/gGVJTypIEda/f7F1hBC3NhAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T13:00:10.356886Z"},"content_sha256":"8da82d354864312f20467052358b47589c069dda4a5546f4495904b197efb273","schema_version":"1.0","event_id":"sha256:8da82d354864312f20467052358b47589c069dda4a5546f4495904b197efb273"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FOAREZ3TXEXGB3O7X2RM7DMOOZ/bundle.json","state_url":"https://pith.science/pith/FOAREZ3TXEXGB3O7X2RM7DMOOZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FOAREZ3TXEXGB3O7X2RM7DMOOZ/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":"2026-08-01T13:00:10Z","links":{"resolver":"https://pith.science/pith/FOAREZ3TXEXGB3O7X2RM7DMOOZ","bundle":"https://pith.science/pith/FOAREZ3TXEXGB3O7X2RM7DMOOZ/bundle.json","state":"https://pith.science/pith/FOAREZ3TXEXGB3O7X2RM7DMOOZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FOAREZ3TXEXGB3O7X2RM7DMOOZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:FOAREZ3TXEXGB3O7X2RM7DMOOZ","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":"dbc99aa8b9ac1ad4f350fb561451deaa220c550fe2df2b1ad7a15f1295e34abb","cross_cats_sorted":["cs.CL","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-10-28T15:00:09Z","title_canon_sha256":"e358eeaecb88cead3c8c5a0976ffda1ffb476caafbf2ba7b6f418a8ccd31bb7c"},"schema_version":"1.0","source":{"id":"2010.15025","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2010.15025","created_at":"2026-07-05T02:32:34Z"},{"alias_kind":"arxiv_version","alias_value":"2010.15025v2","created_at":"2026-07-05T02:32:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.15025","created_at":"2026-07-05T02:32:34Z"},{"alias_kind":"pith_short_12","alias_value":"FOAREZ3TXEXG","created_at":"2026-07-05T02:32:34Z"},{"alias_kind":"pith_short_16","alias_value":"FOAREZ3TXEXGB3O7","created_at":"2026-07-05T02:32:34Z"},{"alias_kind":"pith_short_8","alias_value":"FOAREZ3T","created_at":"2026-07-05T02:32:34Z"}],"graph_snapshots":[{"event_id":"sha256:8da82d354864312f20467052358b47589c069dda4a5546f4495904b197efb273","target":"graph","created_at":"2026-07-05T02:32:34Z","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/2010.15025/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Non-autoregressive (NAR) transformer models have achieved significantly inference speedup but at the cost of inferior accuracy compared to autoregressive (AR) models in automatic speech recognition (ASR). Most of the NAR transformers take a fixed-length sequence filled with MASK tokens or a redundant sequence copied from encoder states as decoder input, they cannot provide efficient target-side information thus leading to accuracy degradation. To address this problem, we propose a CTC-enhanced NAR transformer, which generates target sequence by refining predictions of the CTC module. Experimen","authors_text":"Chao Weng, Dan Su, Helen Meng, Xingchen Song, Yiheng Huang, Zhiyong Wu","cross_cats":["cs.CL","eess.AS"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-10-28T15:00:09Z","title":"Non-Autoregressive Transformer ASR with CTC-Enhanced Decoder Input"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.15025","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":"sha256:5281d70fa239f501d9dc0a744dd5c3db5c4180b8f2c868226fe1ca053333e60c","target":"record","created_at":"2026-07-05T02:32:34Z","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":"dbc99aa8b9ac1ad4f350fb561451deaa220c550fe2df2b1ad7a15f1295e34abb","cross_cats_sorted":["cs.CL","eess.AS"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.SD","submitted_at":"2020-10-28T15:00:09Z","title_canon_sha256":"e358eeaecb88cead3c8c5a0976ffda1ffb476caafbf2ba7b6f418a8ccd31bb7c"},"schema_version":"1.0","source":{"id":"2010.15025","kind":"arxiv","version":2}},"canonical_sha256":"2b81126773b92e60eddfbea2cf8d8e767724f0264f9ffcbd5810d718ed0b524c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2b81126773b92e60eddfbea2cf8d8e767724f0264f9ffcbd5810d718ed0b524c","first_computed_at":"2026-07-05T02:32:34.036334Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:32:34.036334Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VauqEpSX+eSMdzvlkkObvDQMUIeLSbn7DtKZJEExM+DASWRCMHCCRZIlzmjrGSA8C1FQ1eTq5lQ4JaLdqJf+DQ==","signature_status":"signed_v1","signed_at":"2026-07-05T02:32:34.036825Z","signed_message":"canonical_sha256_bytes"},"source_id":"2010.15025","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5281d70fa239f501d9dc0a744dd5c3db5c4180b8f2c868226fe1ca053333e60c","sha256:8da82d354864312f20467052358b47589c069dda4a5546f4495904b197efb273"],"state_sha256":"a1617c4f0273d94a3eaa5f5fef0ac82a6db8d04474cebdace636b806105412d3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e69F+fAorOZ0vXr31V/puvH/UTOsHieeANNGqPXDVzzMwl9WniFYXWFajLxNx5WbEHgTBQE6Fi8murJjCSMNDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T13:00:10.366656Z","bundle_sha256":"4c31481d153da0081a0308b9145082eee43ebc81e13a94739645bbf904549103"}}