{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:GEXUVRI74VUELC3L6NOS5VE2OO","short_pith_number":"pith:GEXUVRI7","canonical_record":{"source":{"id":"2502.02577","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-04T18:53:42Z","cross_cats_sorted":[],"title_canon_sha256":"f4ba3f4f20c4ad93ca38da57ed8937ed17858614286c759bb98b07edabfd5882","abstract_canon_sha256":"62186909e742a0634e431a2490a95ef632097ece396464fbf95f0245bb424749"},"schema_version":"1.0"},"canonical_sha256":"312f4ac51fe568458b6bf35d2ed49a7396b84097d7168328e28711cdb519fe4c","source":{"kind":"arxiv","id":"2502.02577","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.02577","created_at":"2026-07-05T11:05:39Z"},{"alias_kind":"arxiv_version","alias_value":"2502.02577v3","created_at":"2026-07-05T11:05:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.02577","created_at":"2026-07-05T11:05:39Z"},{"alias_kind":"pith_short_12","alias_value":"GEXUVRI74VUE","created_at":"2026-07-05T11:05:39Z"},{"alias_kind":"pith_short_16","alias_value":"GEXUVRI74VUELC3L","created_at":"2026-07-05T11:05:39Z"},{"alias_kind":"pith_short_8","alias_value":"GEXUVRI7","created_at":"2026-07-05T11:05:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:GEXUVRI74VUELC3L6NOS5VE2OO","target":"record","payload":{"canonical_record":{"source":{"id":"2502.02577","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-04T18:53:42Z","cross_cats_sorted":[],"title_canon_sha256":"f4ba3f4f20c4ad93ca38da57ed8937ed17858614286c759bb98b07edabfd5882","abstract_canon_sha256":"62186909e742a0634e431a2490a95ef632097ece396464fbf95f0245bb424749"},"schema_version":"1.0"},"canonical_sha256":"312f4ac51fe568458b6bf35d2ed49a7396b84097d7168328e28711cdb519fe4c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:05:39.574967Z","signature_b64":"pKaGCSZj+c555SoM56JbR/kuBaBNbiBPP9YAUGT/BrShbk7N9V1VkEeLHEKXx3wp2XcbUlWUJ//zlnZj2pgHBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"312f4ac51fe568458b6bf35d2ed49a7396b84097d7168328e28711cdb519fe4c","last_reissued_at":"2026-07-05T11:05:39.574494Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:05:39.574494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.02577","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":"2026-07-05T11:05:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/TX/hGcthc7Ruai4Cmmrx+FySZqoblF09ZDyZA2h5B2jc7WwhWKaJwQQTybXQo2oXbyWgPUwsiF78Z/DGMLXBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T09:25:49.039670Z"},"content_sha256":"6c4f6defacff88f281f5aa6880317865c8c10106db41cf72b0ed9986e11c576e","schema_version":"1.0","event_id":"sha256:6c4f6defacff88f281f5aa6880317865c8c10106db41cf72b0ed9986e11c576e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:GEXUVRI74VUELC3L6NOS5VE2OO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A comparison of translation performance between DeepL and Supertext","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Alex Fl\\\"uckiger, Chantal Amrhein, Florian Schottmann, Fr\\'ed\\'eric Odermatt, Martin P\\\"omsl, Philippe Schl\\\"apfer, Samuel L\\\"aubli, Tim Graf","submitted_at":"2025-02-04T18:53:42Z","abstract_excerpt":"As strong machine translation (MT) systems are increasingly based on large language models (LLMs), reliable quality benchmarking requires methods that capture their ability to leverage extended context. This study compares two commercial MT systems -- DeepL and Supertext -- by assessing their performance on unsegmented texts. We evaluate translation quality across four language directions with professional translators assessing segments with full document-level context. While segment-level assessments indicate no strong preference between the systems in most cases, document-level analysis reve"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.02577","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/2502.02577/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":"2026-07-05T11:05:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QwJaWMg1nKwDil96iRaGjQ7BOb3AcJ25Q6DP+qxPpIM+Al+SKhF4OlBC8L+9Bp4lNXXJZIf3ATMeDRzxwQgUCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T09:25:49.041147Z"},"content_sha256":"7b8456fbbbd7f3876838c6c89bc9ea24c69dac20ffb654877d897d41cc51cbd5","schema_version":"1.0","event_id":"sha256:7b8456fbbbd7f3876838c6c89bc9ea24c69dac20ffb654877d897d41cc51cbd5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GEXUVRI74VUELC3L6NOS5VE2OO/bundle.json","state_url":"https://pith.science/pith/GEXUVRI74VUELC3L6NOS5VE2OO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GEXUVRI74VUELC3L6NOS5VE2OO/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":"2026-08-10T09:25:49Z","links":{"resolver":"https://pith.science/pith/GEXUVRI74VUELC3L6NOS5VE2OO","bundle":"https://pith.science/pith/GEXUVRI74VUELC3L6NOS5VE2OO/bundle.json","state":"https://pith.science/pith/GEXUVRI74VUELC3L6NOS5VE2OO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GEXUVRI74VUELC3L6NOS5VE2OO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GEXUVRI74VUELC3L6NOS5VE2OO","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":"62186909e742a0634e431a2490a95ef632097ece396464fbf95f0245bb424749","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-04T18:53:42Z","title_canon_sha256":"f4ba3f4f20c4ad93ca38da57ed8937ed17858614286c759bb98b07edabfd5882"},"schema_version":"1.0","source":{"id":"2502.02577","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.02577","created_at":"2026-07-05T11:05:39Z"},{"alias_kind":"arxiv_version","alias_value":"2502.02577v3","created_at":"2026-07-05T11:05:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.02577","created_at":"2026-07-05T11:05:39Z"},{"alias_kind":"pith_short_12","alias_value":"GEXUVRI74VUE","created_at":"2026-07-05T11:05:39Z"},{"alias_kind":"pith_short_16","alias_value":"GEXUVRI74VUELC3L","created_at":"2026-07-05T11:05:39Z"},{"alias_kind":"pith_short_8","alias_value":"GEXUVRI7","created_at":"2026-07-05T11:05:39Z"}],"graph_snapshots":[{"event_id":"sha256:7b8456fbbbd7f3876838c6c89bc9ea24c69dac20ffb654877d897d41cc51cbd5","target":"graph","created_at":"2026-07-05T11:05:39Z","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/2502.02577/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"As strong machine translation (MT) systems are increasingly based on large language models (LLMs), reliable quality benchmarking requires methods that capture their ability to leverage extended context. This study compares two commercial MT systems -- DeepL and Supertext -- by assessing their performance on unsegmented texts. We evaluate translation quality across four language directions with professional translators assessing segments with full document-level context. While segment-level assessments indicate no strong preference between the systems in most cases, document-level analysis reve","authors_text":"Alex Fl\\\"uckiger, Chantal Amrhein, Florian Schottmann, Fr\\'ed\\'eric Odermatt, Martin P\\\"omsl, Philippe Schl\\\"apfer, Samuel L\\\"aubli, Tim Graf","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-04T18:53:42Z","title":"A comparison of translation performance between DeepL and Supertext"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.02577","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":"sha256:6c4f6defacff88f281f5aa6880317865c8c10106db41cf72b0ed9986e11c576e","target":"record","created_at":"2026-07-05T11:05:39Z","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":"62186909e742a0634e431a2490a95ef632097ece396464fbf95f0245bb424749","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-02-04T18:53:42Z","title_canon_sha256":"f4ba3f4f20c4ad93ca38da57ed8937ed17858614286c759bb98b07edabfd5882"},"schema_version":"1.0","source":{"id":"2502.02577","kind":"arxiv","version":3}},"canonical_sha256":"312f4ac51fe568458b6bf35d2ed49a7396b84097d7168328e28711cdb519fe4c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"312f4ac51fe568458b6bf35d2ed49a7396b84097d7168328e28711cdb519fe4c","first_computed_at":"2026-07-05T11:05:39.574494Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:05:39.574494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pKaGCSZj+c555SoM56JbR/kuBaBNbiBPP9YAUGT/BrShbk7N9V1VkEeLHEKXx3wp2XcbUlWUJ//zlnZj2pgHBA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:05:39.574967Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.02577","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6c4f6defacff88f281f5aa6880317865c8c10106db41cf72b0ed9986e11c576e","sha256:7b8456fbbbd7f3876838c6c89bc9ea24c69dac20ffb654877d897d41cc51cbd5"],"state_sha256":"83904b3274473bee02b74fc719ed89faa771eaf18d6d7a89943482260c05110c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D+qWDrwYUArFfE+XvQaL7TmWgF3qwyNpTBOf+OgWqvxDl475+9tQm9F6aKB+tZGW8//xKZJZvWo1X2iy9Q1RBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T09:25:49.049933Z","bundle_sha256":"6910bfc1e2c5c620238ac6eb44ac761772a72581c877ed512baadba49ab92e9e"}}