{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:7MGC464JPBHG567BBSB2Q2HODW","short_pith_number":"pith:7MGC464J","canonical_record":{"source":{"id":"2205.09988","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-05-20T06:45:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"0f7a32807089e166912e73e8bc5702873ecf378c2834c1491f9d35ed8b94be98","abstract_canon_sha256":"7e1c95abcdfaeeb5925e6f0049a2e3273173ff8d6a3b095c26687f8bf60962a4"},"schema_version":"1.0"},"canonical_sha256":"fb0c2e7b89784e6efbe10c83a868ee1d9550e14d1b6ca5a71d8e7fdd50a5ba36","source":{"kind":"arxiv","id":"2205.09988","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.09988","created_at":"2026-07-05T04:25:02Z"},{"alias_kind":"arxiv_version","alias_value":"2205.09988v1","created_at":"2026-07-05T04:25:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.09988","created_at":"2026-07-05T04:25:02Z"},{"alias_kind":"pith_short_12","alias_value":"7MGC464JPBHG","created_at":"2026-07-05T04:25:02Z"},{"alias_kind":"pith_short_16","alias_value":"7MGC464JPBHG567B","created_at":"2026-07-05T04:25:02Z"},{"alias_kind":"pith_short_8","alias_value":"7MGC464J","created_at":"2026-07-05T04:25:02Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:7MGC464JPBHG567BBSB2Q2HODW","target":"record","payload":{"canonical_record":{"source":{"id":"2205.09988","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-05-20T06:45:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"0f7a32807089e166912e73e8bc5702873ecf378c2834c1491f9d35ed8b94be98","abstract_canon_sha256":"7e1c95abcdfaeeb5925e6f0049a2e3273173ff8d6a3b095c26687f8bf60962a4"},"schema_version":"1.0"},"canonical_sha256":"fb0c2e7b89784e6efbe10c83a868ee1d9550e14d1b6ca5a71d8e7fdd50a5ba36","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:25:02.174496Z","signature_b64":"/rWSgqK4bfUjorvz77m2+zVNTOHi8h43a1L7UW3pm1p9ZPxjRk74UlwM2sGqT5+BJMrB3PrM48OdKQS9Js/mCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fb0c2e7b89784e6efbe10c83a868ee1d9550e14d1b6ca5a71d8e7fdd50a5ba36","last_reissued_at":"2026-07-05T04:25:02.174013Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:25:02.174013Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.09988","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":"2026-07-05T04:25:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KOgvfiCU4UNWsNsOXffP21RF0MEOE3pyiwmi5EeIOA/NbALnTOFqVS8qI9/MTIKzaIMS7USjsPpyyOOpmP/lDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T13:12:13.068840Z"},"content_sha256":"1fde1df99a8088508c90ea96054c83198f11300fcc26e501012a3fab31b54991","schema_version":"1.0","event_id":"sha256:1fde1df99a8088508c90ea96054c83198f11300fcc26e501012a3fab31b54991"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:7MGC464JPBHG567BBSB2Q2HODW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SALTED: A Framework for SAlient Long-Tail Translation Error Detection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Arul Menezes, Matt Post, Vikas Raunak","submitted_at":"2022-05-20T06:45:07Z","abstract_excerpt":"Traditional machine translation (MT) metrics provide an average measure of translation quality that is insensitive to the long tail of behavioral problems in MT. Examples include translation of numbers, physical units, dropped content and hallucinations. These errors, which occur rarely and unpredictably in Neural Machine Translation (NMT), greatly undermine the reliability of state-of-the-art MT systems. Consequently, it is important to have visibility into these problems during model development. Towards this direction, we introduce SALTED, a specifications-based framework for behavioral tes"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.09988","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/2205.09988/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":"2026-07-05T04:25:02Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8ixftBJTxhDg6C5tMdkoSBD6aTA00AJ5Xa6FOkpascIkfTnys0KoXrfRna+TOKmA4SP1mRED943RwISzt+qWDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T13:12:13.069210Z"},"content_sha256":"7cfa26ec8fd2ef526b8763b325604e262dd3744cb81b69643f2608cd66e2ffb1","schema_version":"1.0","event_id":"sha256:7cfa26ec8fd2ef526b8763b325604e262dd3744cb81b69643f2608cd66e2ffb1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7MGC464JPBHG567BBSB2Q2HODW/bundle.json","state_url":"https://pith.science/pith/7MGC464JPBHG567BBSB2Q2HODW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7MGC464JPBHG567BBSB2Q2HODW/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":"2026-07-05T13:12:13Z","links":{"resolver":"https://pith.science/pith/7MGC464JPBHG567BBSB2Q2HODW","bundle":"https://pith.science/pith/7MGC464JPBHG567BBSB2Q2HODW/bundle.json","state":"https://pith.science/pith/7MGC464JPBHG567BBSB2Q2HODW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7MGC464JPBHG567BBSB2Q2HODW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:7MGC464JPBHG567BBSB2Q2HODW","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":"7e1c95abcdfaeeb5925e6f0049a2e3273173ff8d6a3b095c26687f8bf60962a4","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-05-20T06:45:07Z","title_canon_sha256":"0f7a32807089e166912e73e8bc5702873ecf378c2834c1491f9d35ed8b94be98"},"schema_version":"1.0","source":{"id":"2205.09988","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.09988","created_at":"2026-07-05T04:25:02Z"},{"alias_kind":"arxiv_version","alias_value":"2205.09988v1","created_at":"2026-07-05T04:25:02Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.09988","created_at":"2026-07-05T04:25:02Z"},{"alias_kind":"pith_short_12","alias_value":"7MGC464JPBHG","created_at":"2026-07-05T04:25:02Z"},{"alias_kind":"pith_short_16","alias_value":"7MGC464JPBHG567B","created_at":"2026-07-05T04:25:02Z"},{"alias_kind":"pith_short_8","alias_value":"7MGC464J","created_at":"2026-07-05T04:25:02Z"}],"graph_snapshots":[{"event_id":"sha256:7cfa26ec8fd2ef526b8763b325604e262dd3744cb81b69643f2608cd66e2ffb1","target":"graph","created_at":"2026-07-05T04:25:02Z","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/2205.09988/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Traditional machine translation (MT) metrics provide an average measure of translation quality that is insensitive to the long tail of behavioral problems in MT. Examples include translation of numbers, physical units, dropped content and hallucinations. These errors, which occur rarely and unpredictably in Neural Machine Translation (NMT), greatly undermine the reliability of state-of-the-art MT systems. Consequently, it is important to have visibility into these problems during model development. Towards this direction, we introduce SALTED, a specifications-based framework for behavioral tes","authors_text":"Arul Menezes, Matt Post, Vikas Raunak","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-05-20T06:45:07Z","title":"SALTED: A Framework for SAlient Long-Tail Translation Error Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.09988","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":"sha256:1fde1df99a8088508c90ea96054c83198f11300fcc26e501012a3fab31b54991","target":"record","created_at":"2026-07-05T04:25:02Z","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":"7e1c95abcdfaeeb5925e6f0049a2e3273173ff8d6a3b095c26687f8bf60962a4","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2022-05-20T06:45:07Z","title_canon_sha256":"0f7a32807089e166912e73e8bc5702873ecf378c2834c1491f9d35ed8b94be98"},"schema_version":"1.0","source":{"id":"2205.09988","kind":"arxiv","version":1}},"canonical_sha256":"fb0c2e7b89784e6efbe10c83a868ee1d9550e14d1b6ca5a71d8e7fdd50a5ba36","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fb0c2e7b89784e6efbe10c83a868ee1d9550e14d1b6ca5a71d8e7fdd50a5ba36","first_computed_at":"2026-07-05T04:25:02.174013Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:25:02.174013Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/rWSgqK4bfUjorvz77m2+zVNTOHi8h43a1L7UW3pm1p9ZPxjRk74UlwM2sGqT5+BJMrB3PrM48OdKQS9Js/mCw==","signature_status":"signed_v1","signed_at":"2026-07-05T04:25:02.174496Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.09988","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1fde1df99a8088508c90ea96054c83198f11300fcc26e501012a3fab31b54991","sha256:7cfa26ec8fd2ef526b8763b325604e262dd3744cb81b69643f2608cd66e2ffb1"],"state_sha256":"ddd5eaf91f9649cb7dd9dd7b92eac115cfa97f21e110f44b8918beb9ed197f09"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S6w4KYY1TL7xoHnqd62YCuxYzSj8gGo0OZ8rMt/FurvgfucGykrvNTbJzmf8mDvoEUW6lhKDgFjT44+vgfuBDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T13:12:13.071861Z","bundle_sha256":"c6d452dc7630843593fdff4313f376e506e36ea3e360671ec487bf2539f9518c"}}