{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:PFCIC2PGONPXACMPLA4ZCLSKHG","short_pith_number":"pith:PFCIC2PG","canonical_record":{"source":{"id":"2403.09522","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-14T16:07:39Z","cross_cats_sorted":[],"title_canon_sha256":"30004e1b7d4f29bfcf6bfad1ee3fcc072615b23670d58c37d1df9390976c86c2","abstract_canon_sha256":"b945535738151022a8da197b4d87d042d94b872db2f71dff711624af41d83819"},"schema_version":"1.0"},"canonical_sha256":"79448169e6735f70098f5839912e4a39a33810d08a3dfe9b5b05a973ae8903e4","source":{"kind":"arxiv","id":"2403.09522","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.09522","created_at":"2026-07-05T08:02:51Z"},{"alias_kind":"arxiv_version","alias_value":"2403.09522v2","created_at":"2026-07-05T08:02:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.09522","created_at":"2026-07-05T08:02:51Z"},{"alias_kind":"pith_short_12","alias_value":"PFCIC2PGONPX","created_at":"2026-07-05T08:02:51Z"},{"alias_kind":"pith_short_16","alias_value":"PFCIC2PGONPXACMP","created_at":"2026-07-05T08:02:51Z"},{"alias_kind":"pith_short_8","alias_value":"PFCIC2PG","created_at":"2026-07-05T08:02:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:PFCIC2PGONPXACMPLA4ZCLSKHG","target":"record","payload":{"canonical_record":{"source":{"id":"2403.09522","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-14T16:07:39Z","cross_cats_sorted":[],"title_canon_sha256":"30004e1b7d4f29bfcf6bfad1ee3fcc072615b23670d58c37d1df9390976c86c2","abstract_canon_sha256":"b945535738151022a8da197b4d87d042d94b872db2f71dff711624af41d83819"},"schema_version":"1.0"},"canonical_sha256":"79448169e6735f70098f5839912e4a39a33810d08a3dfe9b5b05a973ae8903e4","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:02:51.827468Z","signature_b64":"6EdOcYzV3UKBYrGNPn4+Vzb6HqiGmlbQxDlhila1gVZF/w5z/5kuNDUlmORYx9aQpgCu/U+RFCFpCtai6bntBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"79448169e6735f70098f5839912e4a39a33810d08a3dfe9b5b05a973ae8903e4","last_reissued_at":"2026-07-05T08:02:51.827009Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:02:51.827009Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.09522","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":"2026-07-05T08:02:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Kb9t/eRMl1+E8VaHks17jlV3cm93D2AdbYGls/2EIAOCCsq8ocm6QuG2d8Xdy634Fx/rhJZWmO+iPtWp/By1Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T05:55:10.687045Z"},"content_sha256":"de314cfaf6f21ce9565f9439c557182b013ebcc40e9eeeed7078a9d9bc3201a6","schema_version":"1.0","event_id":"sha256:de314cfaf6f21ce9565f9439c557182b013ebcc40e9eeeed7078a9d9bc3201a6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:PFCIC2PGONPXACMPLA4ZCLSKHG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MT-PATCHER: Selective and Extendable Knowledge Distillation from Large Language Models for Machine Translation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Jiahuan Li, Jiajun Chen, Shanbo Cheng, Shujian Huang","submitted_at":"2024-03-14T16:07:39Z","abstract_excerpt":"Large Language Models (LLM) have demonstrated their strong ability in the field of machine translation (MT), yet they suffer from high computational cost and latency. Therefore, transferring translation knowledge from giant LLMs to medium-sized machine translation models is a promising research direction. However, traditional knowledge distillation methods do not take the capability of student and teacher models into consideration, therefore repeatedly teaching student models on the knowledge they have learned, and failing to extend to novel contexts and knowledge. In this paper, we propose a "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.09522","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/2403.09522/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":"2026-07-05T08:02:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"azye8OikBHMyIekztZbrJNPz4MENSs/Q7IzBImp4K1RAMLcSqPa/SNQU0HPahiTO6Cu8elKBB+b5gkULocS4BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T05:55:10.688391Z"},"content_sha256":"6bf9a4825681597ca488993af74e1a532f83b91553fae480329e1d9332dbda5a","schema_version":"1.0","event_id":"sha256:6bf9a4825681597ca488993af74e1a532f83b91553fae480329e1d9332dbda5a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PFCIC2PGONPXACMPLA4ZCLSKHG/bundle.json","state_url":"https://pith.science/pith/PFCIC2PGONPXACMPLA4ZCLSKHG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PFCIC2PGONPXACMPLA4ZCLSKHG/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":"2026-08-05T05:55:10Z","links":{"resolver":"https://pith.science/pith/PFCIC2PGONPXACMPLA4ZCLSKHG","bundle":"https://pith.science/pith/PFCIC2PGONPXACMPLA4ZCLSKHG/bundle.json","state":"https://pith.science/pith/PFCIC2PGONPXACMPLA4ZCLSKHG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PFCIC2PGONPXACMPLA4ZCLSKHG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:PFCIC2PGONPXACMPLA4ZCLSKHG","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":"b945535738151022a8da197b4d87d042d94b872db2f71dff711624af41d83819","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-14T16:07:39Z","title_canon_sha256":"30004e1b7d4f29bfcf6bfad1ee3fcc072615b23670d58c37d1df9390976c86c2"},"schema_version":"1.0","source":{"id":"2403.09522","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.09522","created_at":"2026-07-05T08:02:51Z"},{"alias_kind":"arxiv_version","alias_value":"2403.09522v2","created_at":"2026-07-05T08:02:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.09522","created_at":"2026-07-05T08:02:51Z"},{"alias_kind":"pith_short_12","alias_value":"PFCIC2PGONPX","created_at":"2026-07-05T08:02:51Z"},{"alias_kind":"pith_short_16","alias_value":"PFCIC2PGONPXACMP","created_at":"2026-07-05T08:02:51Z"},{"alias_kind":"pith_short_8","alias_value":"PFCIC2PG","created_at":"2026-07-05T08:02:51Z"}],"graph_snapshots":[{"event_id":"sha256:6bf9a4825681597ca488993af74e1a532f83b91553fae480329e1d9332dbda5a","target":"graph","created_at":"2026-07-05T08:02:51Z","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/2403.09522/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLM) have demonstrated their strong ability in the field of machine translation (MT), yet they suffer from high computational cost and latency. Therefore, transferring translation knowledge from giant LLMs to medium-sized machine translation models is a promising research direction. However, traditional knowledge distillation methods do not take the capability of student and teacher models into consideration, therefore repeatedly teaching student models on the knowledge they have learned, and failing to extend to novel contexts and knowledge. In this paper, we propose a ","authors_text":"Jiahuan Li, Jiajun Chen, Shanbo Cheng, Shujian Huang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-14T16:07:39Z","title":"MT-PATCHER: Selective and Extendable Knowledge Distillation from Large Language Models for Machine Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.09522","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:de314cfaf6f21ce9565f9439c557182b013ebcc40e9eeeed7078a9d9bc3201a6","target":"record","created_at":"2026-07-05T08:02:51Z","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":"b945535738151022a8da197b4d87d042d94b872db2f71dff711624af41d83819","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-14T16:07:39Z","title_canon_sha256":"30004e1b7d4f29bfcf6bfad1ee3fcc072615b23670d58c37d1df9390976c86c2"},"schema_version":"1.0","source":{"id":"2403.09522","kind":"arxiv","version":2}},"canonical_sha256":"79448169e6735f70098f5839912e4a39a33810d08a3dfe9b5b05a973ae8903e4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"79448169e6735f70098f5839912e4a39a33810d08a3dfe9b5b05a973ae8903e4","first_computed_at":"2026-07-05T08:02:51.827009Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:02:51.827009Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6EdOcYzV3UKBYrGNPn4+Vzb6HqiGmlbQxDlhila1gVZF/w5z/5kuNDUlmORYx9aQpgCu/U+RFCFpCtai6bntBA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:02:51.827468Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.09522","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:de314cfaf6f21ce9565f9439c557182b013ebcc40e9eeeed7078a9d9bc3201a6","sha256:6bf9a4825681597ca488993af74e1a532f83b91553fae480329e1d9332dbda5a"],"state_sha256":"3ef49eb857860d139cef08ddcba9ca69f68829b9c98beb1d2dd5756170712440"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vXFohbTyc1syMF9DvRbLV/PqiFmbiOBlnEICzGBrYnGsfYS8CFu8tc8c51qvmvB215IR+fIuXRvZNo0pL14xAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T05:55:10.782635Z","bundle_sha256":"b687573f5c6b34e7d242a11c0da13fd8f25295069fa21fb1b66bde68e583cbf3"}}