{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:4CX3YIBOLO4T7OWHD7BBFCZH5Q","short_pith_number":"pith:4CX3YIBO","canonical_record":{"source":{"id":"2502.08561","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-12T16:49:52Z","cross_cats_sorted":[],"title_canon_sha256":"50ba36a1ed28d6281d5b47fcec1ad4e4dce69ba8c0b1b9251ecb6b3bbe934c41","abstract_canon_sha256":"1165a42e4ccb309c97a97d3ed5061e37a9bd1350a8cc5c4183b9f0f3e96553a3"},"schema_version":"1.0"},"canonical_sha256":"e0afbc202e5bb93fbac71fc2128b27ec190d8c9de5d323cf82ab34fd0645f47b","source":{"kind":"arxiv","id":"2502.08561","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.08561","created_at":"2026-07-05T11:13:20Z"},{"alias_kind":"arxiv_version","alias_value":"2502.08561v3","created_at":"2026-07-05T11:13:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.08561","created_at":"2026-07-05T11:13:20Z"},{"alias_kind":"pith_short_12","alias_value":"4CX3YIBOLO4T","created_at":"2026-07-05T11:13:20Z"},{"alias_kind":"pith_short_16","alias_value":"4CX3YIBOLO4T7OWH","created_at":"2026-07-05T11:13:20Z"},{"alias_kind":"pith_short_8","alias_value":"4CX3YIBO","created_at":"2026-07-05T11:13:20Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:4CX3YIBOLO4T7OWHD7BBFCZH5Q","target":"record","payload":{"canonical_record":{"source":{"id":"2502.08561","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-12T16:49:52Z","cross_cats_sorted":[],"title_canon_sha256":"50ba36a1ed28d6281d5b47fcec1ad4e4dce69ba8c0b1b9251ecb6b3bbe934c41","abstract_canon_sha256":"1165a42e4ccb309c97a97d3ed5061e37a9bd1350a8cc5c4183b9f0f3e96553a3"},"schema_version":"1.0"},"canonical_sha256":"e0afbc202e5bb93fbac71fc2128b27ec190d8c9de5d323cf82ab34fd0645f47b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:13:20.151328Z","signature_b64":"1dAWhFNiWr2ozOrPpSvnFPMxSXLbwWzOR4LN5wP3XcMEh1t3wgbTRlS9SiWVWSl+TXIAkycW3/DBP7KAJ7wZAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e0afbc202e5bb93fbac71fc2128b27ec190d8c9de5d323cf82ab34fd0645f47b","last_reissued_at":"2026-07-05T11:13:20.150876Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:13:20.150876Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.08561","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:13:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PGvJMef5Evw9yn32NFjm5mVqZku0AqFI7tMQDKHOIpKp2pf8wrjHD4vi+ILbbCWe44kVY1wmWqPjiX7zzS4vCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T13:00:59.068342Z"},"content_sha256":"3b2700241ab556944344e11aeba478e585e2078e9bdd312eb60be507698ce85c","schema_version":"1.0","event_id":"sha256:3b2700241ab556944344e11aeba478e585e2078e9bdd312eb60be507698ce85c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:4CX3YIBOLO4T7OWHD7BBFCZH5Q","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Quality-Aware Decoding: Unifying Quality Estimation and Decoding","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jan Niehues, Matthias Huck, Miriam Exel, Sai Koneru","submitted_at":"2025-02-12T16:49:52Z","abstract_excerpt":"Quality Estimation (QE) models for Neural Machine Translation (NMT) predict the quality of the hypothesis without having access to the reference. An emerging research direction in NMT involves the use of QE models, which have demonstrated high correlations with human judgment and can enhance translations through Quality-Aware Decoding. Although several approaches have been proposed based on sampling multiple candidate translations and picking the best candidate, none have integrated these models directly into the decoding process. In this paper, we address this by proposing a novel token-level"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.08561","kind":"arxiv","version":3},"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/2502.08561/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":"2026-07-05T11:13:20Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TAyffZ4sGeK8lhVpqBQic6VHrlBii7K9bsJ4PztkPMMPcMyyhfuzGAjm2sCdbtK3e3mL155uGOoQwzdd6fS+Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T13:00:59.068850Z"},"content_sha256":"967a9becf71cb8964bc0a764ba24db815bf17c361a6e0ffe5ddcc44eaed20917","schema_version":"1.0","event_id":"sha256:967a9becf71cb8964bc0a764ba24db815bf17c361a6e0ffe5ddcc44eaed20917"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4CX3YIBOLO4T7OWHD7BBFCZH5Q/bundle.json","state_url":"https://pith.science/pith/4CX3YIBOLO4T7OWHD7BBFCZH5Q/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4CX3YIBOLO4T7OWHD7BBFCZH5Q/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":"2026-08-17T13:00:59Z","links":{"resolver":"https://pith.science/pith/4CX3YIBOLO4T7OWHD7BBFCZH5Q","bundle":"https://pith.science/pith/4CX3YIBOLO4T7OWHD7BBFCZH5Q/bundle.json","state":"https://pith.science/pith/4CX3YIBOLO4T7OWHD7BBFCZH5Q/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4CX3YIBOLO4T7OWHD7BBFCZH5Q/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4CX3YIBOLO4T7OWHD7BBFCZH5Q","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":"1165a42e4ccb309c97a97d3ed5061e37a9bd1350a8cc5c4183b9f0f3e96553a3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-12T16:49:52Z","title_canon_sha256":"50ba36a1ed28d6281d5b47fcec1ad4e4dce69ba8c0b1b9251ecb6b3bbe934c41"},"schema_version":"1.0","source":{"id":"2502.08561","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.08561","created_at":"2026-07-05T11:13:20Z"},{"alias_kind":"arxiv_version","alias_value":"2502.08561v3","created_at":"2026-07-05T11:13:20Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.08561","created_at":"2026-07-05T11:13:20Z"},{"alias_kind":"pith_short_12","alias_value":"4CX3YIBOLO4T","created_at":"2026-07-05T11:13:20Z"},{"alias_kind":"pith_short_16","alias_value":"4CX3YIBOLO4T7OWH","created_at":"2026-07-05T11:13:20Z"},{"alias_kind":"pith_short_8","alias_value":"4CX3YIBO","created_at":"2026-07-05T11:13:20Z"}],"graph_snapshots":[{"event_id":"sha256:967a9becf71cb8964bc0a764ba24db815bf17c361a6e0ffe5ddcc44eaed20917","target":"graph","created_at":"2026-07-05T11:13:20Z","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/2502.08561/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Quality Estimation (QE) models for Neural Machine Translation (NMT) predict the quality of the hypothesis without having access to the reference. An emerging research direction in NMT involves the use of QE models, which have demonstrated high correlations with human judgment and can enhance translations through Quality-Aware Decoding. Although several approaches have been proposed based on sampling multiple candidate translations and picking the best candidate, none have integrated these models directly into the decoding process. In this paper, we address this by proposing a novel token-level","authors_text":"Jan Niehues, Matthias Huck, Miriam Exel, Sai Koneru","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-12T16:49:52Z","title":"Quality-Aware Decoding: Unifying Quality Estimation and Decoding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.08561","kind":"arxiv","version":3},"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":"sha256:3b2700241ab556944344e11aeba478e585e2078e9bdd312eb60be507698ce85c","target":"record","created_at":"2026-07-05T11:13:20Z","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":"1165a42e4ccb309c97a97d3ed5061e37a9bd1350a8cc5c4183b9f0f3e96553a3","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-12T16:49:52Z","title_canon_sha256":"50ba36a1ed28d6281d5b47fcec1ad4e4dce69ba8c0b1b9251ecb6b3bbe934c41"},"schema_version":"1.0","source":{"id":"2502.08561","kind":"arxiv","version":3}},"canonical_sha256":"e0afbc202e5bb93fbac71fc2128b27ec190d8c9de5d323cf82ab34fd0645f47b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e0afbc202e5bb93fbac71fc2128b27ec190d8c9de5d323cf82ab34fd0645f47b","first_computed_at":"2026-07-05T11:13:20.150876Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:13:20.150876Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1dAWhFNiWr2ozOrPpSvnFPMxSXLbwWzOR4LN5wP3XcMEh1t3wgbTRlS9SiWVWSl+TXIAkycW3/DBP7KAJ7wZAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:13:20.151328Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.08561","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3b2700241ab556944344e11aeba478e585e2078e9bdd312eb60be507698ce85c","sha256:967a9becf71cb8964bc0a764ba24db815bf17c361a6e0ffe5ddcc44eaed20917"],"state_sha256":"97b3e02645008ca366b3d6438121c2fb3a9c59178c3b7faff27bb07684e7e0f1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8jWh2TSBE1EmGgz6QD2jatXpBvpHJm+E1pvw7iZfRh9PJCUiih8S6Xni2Ijef1GrfCg5RE5PWXl2F3YM/Am+Dg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T13:00:59.107501Z","bundle_sha256":"5f3b06a4588d673a5ae0c31ec08bdae399539f50d37451db0a9afce77fbe1649"}}