{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:G27FQAI6UDJJ44OIJ6LJTDOWGN","short_pith_number":"pith:G27FQAI6","canonical_record":{"source":{"id":"2408.16440","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-29T11:05:54Z","cross_cats_sorted":[],"title_canon_sha256":"295b8e8b4b0f24e7b2a9b40a4cb34d7a98bbd374c0458874cffd690403700630","abstract_canon_sha256":"a1c263923ee61d2eb325b75cfd3c975d5dceead93235053d3bbfedeeaccf18b5"},"schema_version":"1.0"},"canonical_sha256":"36be58011ea0d29e71c84f96998dd6335aad61793785a78d4fbe1b6034fac994","source":{"kind":"arxiv","id":"2408.16440","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.16440","created_at":"2026-07-05T11:45:28Z"},{"alias_kind":"arxiv_version","alias_value":"2408.16440v2","created_at":"2026-07-05T11:45:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.16440","created_at":"2026-07-05T11:45:28Z"},{"alias_kind":"pith_short_12","alias_value":"G27FQAI6UDJJ","created_at":"2026-07-05T11:45:28Z"},{"alias_kind":"pith_short_16","alias_value":"G27FQAI6UDJJ44OI","created_at":"2026-07-05T11:45:28Z"},{"alias_kind":"pith_short_8","alias_value":"G27FQAI6","created_at":"2026-07-05T11:45:28Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:G27FQAI6UDJJ44OIJ6LJTDOWGN","target":"record","payload":{"canonical_record":{"source":{"id":"2408.16440","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-29T11:05:54Z","cross_cats_sorted":[],"title_canon_sha256":"295b8e8b4b0f24e7b2a9b40a4cb34d7a98bbd374c0458874cffd690403700630","abstract_canon_sha256":"a1c263923ee61d2eb325b75cfd3c975d5dceead93235053d3bbfedeeaccf18b5"},"schema_version":"1.0"},"canonical_sha256":"36be58011ea0d29e71c84f96998dd6335aad61793785a78d4fbe1b6034fac994","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:45:29.000409Z","signature_b64":"/2m4oZYNZmr/jNLiMu8K3lOWMOJWRPgFJTG96lZvxQTaV23Pi+Ug4k0vy5E+FikVB5ThB5gt3ummTRquqKy0Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"36be58011ea0d29e71c84f96998dd6335aad61793785a78d4fbe1b6034fac994","last_reissued_at":"2026-07-05T11:45:28.999931Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:45:28.999931Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2408.16440","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":"2026-07-05T11:45:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OLgThHl7xSiJdEXj38lyG7RtDri50l2CCFnf9yWa6NlbRXZ3gT2CqAOjjtOpi0KyvUrh/7YcQ08bc2C6RfyUAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T13:26:05.099514Z"},"content_sha256":"3dc7db7c66111374c0907733274cc8b71271aac3bcffa7f3df08f4a0a82f6932","schema_version":"1.0","event_id":"sha256:3dc7db7c66111374c0907733274cc8b71271aac3bcffa7f3df08f4a0a82f6932"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:G27FQAI6UDJJ44OIJ6LJTDOWGN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Instruction-tuned Large Language Models for Machine Translation in the Medical Domain","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Miguel Rios","submitted_at":"2024-08-29T11:05:54Z","abstract_excerpt":"Large Language Models (LLMs) have shown promising results on machine translation for high resource language pairs and domains. However, in specialised domains (e.g. medical) LLMs have shown lower performance compared to standard neural machine translation models. The consistency in the machine translation of terminology is crucial for users, researchers, and translators in specialised domains. In this study, we compare the performance between baseline LLMs and instruction-tuned LLMs in the medical domain. In addition, we introduce terminology from specialised medical dictionaries into the inst"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.16440","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/2408.16440/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":"2026-07-05T11:45:28Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/IbZX856bgjPqjWJL5b349cormiZupHMkN17r39wHLyXNSlPi8fA+1/5adp5IISES/3X8ACVHgw9oGzabvH6BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T13:26:05.099886Z"},"content_sha256":"c674c4c7f7194f91f4888de7ec4a11d10c40ff05051d58492eaa1fa692b719c6","schema_version":"1.0","event_id":"sha256:c674c4c7f7194f91f4888de7ec4a11d10c40ff05051d58492eaa1fa692b719c6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/G27FQAI6UDJJ44OIJ6LJTDOWGN/bundle.json","state_url":"https://pith.science/pith/G27FQAI6UDJJ44OIJ6LJTDOWGN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/G27FQAI6UDJJ44OIJ6LJTDOWGN/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":"2026-08-19T13:26:05Z","links":{"resolver":"https://pith.science/pith/G27FQAI6UDJJ44OIJ6LJTDOWGN","bundle":"https://pith.science/pith/G27FQAI6UDJJ44OIJ6LJTDOWGN/bundle.json","state":"https://pith.science/pith/G27FQAI6UDJJ44OIJ6LJTDOWGN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/G27FQAI6UDJJ44OIJ6LJTDOWGN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:G27FQAI6UDJJ44OIJ6LJTDOWGN","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":"a1c263923ee61d2eb325b75cfd3c975d5dceead93235053d3bbfedeeaccf18b5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-29T11:05:54Z","title_canon_sha256":"295b8e8b4b0f24e7b2a9b40a4cb34d7a98bbd374c0458874cffd690403700630"},"schema_version":"1.0","source":{"id":"2408.16440","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.16440","created_at":"2026-07-05T11:45:28Z"},{"alias_kind":"arxiv_version","alias_value":"2408.16440v2","created_at":"2026-07-05T11:45:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.16440","created_at":"2026-07-05T11:45:28Z"},{"alias_kind":"pith_short_12","alias_value":"G27FQAI6UDJJ","created_at":"2026-07-05T11:45:28Z"},{"alias_kind":"pith_short_16","alias_value":"G27FQAI6UDJJ44OI","created_at":"2026-07-05T11:45:28Z"},{"alias_kind":"pith_short_8","alias_value":"G27FQAI6","created_at":"2026-07-05T11:45:28Z"}],"graph_snapshots":[{"event_id":"sha256:c674c4c7f7194f91f4888de7ec4a11d10c40ff05051d58492eaa1fa692b719c6","target":"graph","created_at":"2026-07-05T11:45:28Z","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/2408.16440/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have shown promising results on machine translation for high resource language pairs and domains. However, in specialised domains (e.g. medical) LLMs have shown lower performance compared to standard neural machine translation models. The consistency in the machine translation of terminology is crucial for users, researchers, and translators in specialised domains. In this study, we compare the performance between baseline LLMs and instruction-tuned LLMs in the medical domain. In addition, we introduce terminology from specialised medical dictionaries into the inst","authors_text":"Miguel Rios","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-29T11:05:54Z","title":"Instruction-tuned Large Language Models for Machine Translation in the Medical Domain"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.16440","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":"sha256:3dc7db7c66111374c0907733274cc8b71271aac3bcffa7f3df08f4a0a82f6932","target":"record","created_at":"2026-07-05T11:45:28Z","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":"a1c263923ee61d2eb325b75cfd3c975d5dceead93235053d3bbfedeeaccf18b5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CL","submitted_at":"2024-08-29T11:05:54Z","title_canon_sha256":"295b8e8b4b0f24e7b2a9b40a4cb34d7a98bbd374c0458874cffd690403700630"},"schema_version":"1.0","source":{"id":"2408.16440","kind":"arxiv","version":2}},"canonical_sha256":"36be58011ea0d29e71c84f96998dd6335aad61793785a78d4fbe1b6034fac994","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"36be58011ea0d29e71c84f96998dd6335aad61793785a78d4fbe1b6034fac994","first_computed_at":"2026-07-05T11:45:28.999931Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:45:28.999931Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/2m4oZYNZmr/jNLiMu8K3lOWMOJWRPgFJTG96lZvxQTaV23Pi+Ug4k0vy5E+FikVB5ThB5gt3ummTRquqKy0Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:45:29.000409Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.16440","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3dc7db7c66111374c0907733274cc8b71271aac3bcffa7f3df08f4a0a82f6932","sha256:c674c4c7f7194f91f4888de7ec4a11d10c40ff05051d58492eaa1fa692b719c6"],"state_sha256":"1836bebee29750ebb5548bd45f81f333eb05d3b7d15ec0f622671c311c672e8d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FWof9UMTcLNV7uz+2FSqhfKaqUSnIMdk00ozYz+xeAnG6FWGnL3wTUtzIebBUS7EFW7ugRGfpzoO0N4qZWy6Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T13:26:05.102271Z","bundle_sha256":"4fc8267d89fd7072b69106ab63d04b71c7510bf656663673ddea2c0205732a54"}}