{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:XKXKCVDTQU6NOBJ26KCHRZVXTS","short_pith_number":"pith:XKXKCVDT","canonical_record":{"source":{"id":"2110.02600","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-10-06T09:10:10Z","cross_cats_sorted":[],"title_canon_sha256":"f5104c93a5d69bf85b7e5bf62cf795589c31bcf58f23631741397b23e13e874b","abstract_canon_sha256":"9aed7da94827db2eb18ddf416abe6bd85c56103198bbc1a6ad092c77d4a67084"},"schema_version":"1.0"},"canonical_sha256":"baaea15473853cd7053af28478e6b79c913962fa299d42e65d48b542df319d54","source":{"kind":"arxiv","id":"2110.02600","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.02600","created_at":"2026-07-05T04:00:18Z"},{"alias_kind":"arxiv_version","alias_value":"2110.02600v3","created_at":"2026-07-05T04:00:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.02600","created_at":"2026-07-05T04:00:18Z"},{"alias_kind":"pith_short_12","alias_value":"XKXKCVDTQU6N","created_at":"2026-07-05T04:00:18Z"},{"alias_kind":"pith_short_16","alias_value":"XKXKCVDTQU6NOBJ2","created_at":"2026-07-05T04:00:18Z"},{"alias_kind":"pith_short_8","alias_value":"XKXKCVDT","created_at":"2026-07-05T04:00:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:XKXKCVDTQU6NOBJ26KCHRZVXTS","target":"record","payload":{"canonical_record":{"source":{"id":"2110.02600","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-10-06T09:10:10Z","cross_cats_sorted":[],"title_canon_sha256":"f5104c93a5d69bf85b7e5bf62cf795589c31bcf58f23631741397b23e13e874b","abstract_canon_sha256":"9aed7da94827db2eb18ddf416abe6bd85c56103198bbc1a6ad092c77d4a67084"},"schema_version":"1.0"},"canonical_sha256":"baaea15473853cd7053af28478e6b79c913962fa299d42e65d48b542df319d54","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:00:18.653063Z","signature_b64":"FqjLHGK6g9a1nKgxvVWW0UxCavgMoOXm16vS+4zwgHgB2Gu1LUVpF2YuK/y0NftZsRku6uymsUMGyjHMpyWLDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"baaea15473853cd7053af28478e6b79c913962fa299d42e65d48b542df319d54","last_reissued_at":"2026-07-05T04:00:18.652554Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:00:18.652554Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2110.02600","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":"2026-07-05T04:00:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"r/4b00F3CLyC8jVo4X8cCD3VVf+7SmG8V6PG4Ug3P+js6GHpQT37/F5pzONFKTu3E3XXqocLhfGQ2OLrQRWjBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T10:56:02.522801Z"},"content_sha256":"e03471be7dde7f9340d948a5b5afba9bb2dfcdc71b66553907c1790f745f52cc","schema_version":"1.0","event_id":"sha256:e03471be7dde7f9340d948a5b5afba9bb2dfcdc71b66553907c1790f745f52cc"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:XKXKCVDTQU6NOBJ26KCHRZVXTS","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Hae Beom Lee, Juho Lee, Seanie Lee, Sung Ju Hwang","submitted_at":"2021-10-06T09:10:10Z","abstract_excerpt":"Multilingual models jointly pretrained on multiple languages have achieved remarkable performance on various multilingual downstream tasks. Moreover, models finetuned on a single monolingual downstream task have shown to generalize to unseen languages. In this paper, we first show that it is crucial for those tasks to align gradients between them in order to maximize knowledge transfer while minimizing negative transfer. Despite its importance, the existing methods for gradient alignment either have a completely different purpose, ignore inter-task alignment, or aim to solve continual learning"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.02600","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/2110.02600/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":"2026-07-05T04:00:18Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HqZWfhCmIj/wy8gRlfm9N3eN6TJJ+HuYDfwu/3l/WajKl7umVd0ra+R2HNtPDleGrLLxlLANkkbbCJVhYpqTBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-28T10:56:02.523176Z"},"content_sha256":"e2ff8aaee6d6db2fed38b8886be3f67c5995216467d40a7e0a934c2c4c20aba9","schema_version":"1.0","event_id":"sha256:e2ff8aaee6d6db2fed38b8886be3f67c5995216467d40a7e0a934c2c4c20aba9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XKXKCVDTQU6NOBJ26KCHRZVXTS/bundle.json","state_url":"https://pith.science/pith/XKXKCVDTQU6NOBJ26KCHRZVXTS/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XKXKCVDTQU6NOBJ26KCHRZVXTS/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":"2026-07-28T10:56:02Z","links":{"resolver":"https://pith.science/pith/XKXKCVDTQU6NOBJ26KCHRZVXTS","bundle":"https://pith.science/pith/XKXKCVDTQU6NOBJ26KCHRZVXTS/bundle.json","state":"https://pith.science/pith/XKXKCVDTQU6NOBJ26KCHRZVXTS/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XKXKCVDTQU6NOBJ26KCHRZVXTS/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:XKXKCVDTQU6NOBJ26KCHRZVXTS","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":"9aed7da94827db2eb18ddf416abe6bd85c56103198bbc1a6ad092c77d4a67084","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-10-06T09:10:10Z","title_canon_sha256":"f5104c93a5d69bf85b7e5bf62cf795589c31bcf58f23631741397b23e13e874b"},"schema_version":"1.0","source":{"id":"2110.02600","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2110.02600","created_at":"2026-07-05T04:00:18Z"},{"alias_kind":"arxiv_version","alias_value":"2110.02600v3","created_at":"2026-07-05T04:00:18Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2110.02600","created_at":"2026-07-05T04:00:18Z"},{"alias_kind":"pith_short_12","alias_value":"XKXKCVDTQU6N","created_at":"2026-07-05T04:00:18Z"},{"alias_kind":"pith_short_16","alias_value":"XKXKCVDTQU6NOBJ2","created_at":"2026-07-05T04:00:18Z"},{"alias_kind":"pith_short_8","alias_value":"XKXKCVDT","created_at":"2026-07-05T04:00:18Z"}],"graph_snapshots":[{"event_id":"sha256:e2ff8aaee6d6db2fed38b8886be3f67c5995216467d40a7e0a934c2c4c20aba9","target":"graph","created_at":"2026-07-05T04:00:18Z","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/2110.02600/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multilingual models jointly pretrained on multiple languages have achieved remarkable performance on various multilingual downstream tasks. Moreover, models finetuned on a single monolingual downstream task have shown to generalize to unseen languages. In this paper, we first show that it is crucial for those tasks to align gradients between them in order to maximize knowledge transfer while minimizing negative transfer. Despite its importance, the existing methods for gradient alignment either have a completely different purpose, ignore inter-task alignment, or aim to solve continual learning","authors_text":"Hae Beom Lee, Juho Lee, Seanie Lee, Sung Ju Hwang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-10-06T09:10:10Z","title":"Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2110.02600","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:e03471be7dde7f9340d948a5b5afba9bb2dfcdc71b66553907c1790f745f52cc","target":"record","created_at":"2026-07-05T04:00:18Z","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":"9aed7da94827db2eb18ddf416abe6bd85c56103198bbc1a6ad092c77d4a67084","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-10-06T09:10:10Z","title_canon_sha256":"f5104c93a5d69bf85b7e5bf62cf795589c31bcf58f23631741397b23e13e874b"},"schema_version":"1.0","source":{"id":"2110.02600","kind":"arxiv","version":3}},"canonical_sha256":"baaea15473853cd7053af28478e6b79c913962fa299d42e65d48b542df319d54","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"baaea15473853cd7053af28478e6b79c913962fa299d42e65d48b542df319d54","first_computed_at":"2026-07-05T04:00:18.652554Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:00:18.652554Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FqjLHGK6g9a1nKgxvVWW0UxCavgMoOXm16vS+4zwgHgB2Gu1LUVpF2YuK/y0NftZsRku6uymsUMGyjHMpyWLDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:00:18.653063Z","signed_message":"canonical_sha256_bytes"},"source_id":"2110.02600","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e03471be7dde7f9340d948a5b5afba9bb2dfcdc71b66553907c1790f745f52cc","sha256:e2ff8aaee6d6db2fed38b8886be3f67c5995216467d40a7e0a934c2c4c20aba9"],"state_sha256":"eeeb80c2490699ff1ee797180c6badb62862c519e62e50b6974efc5bd22c4743"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"InIa+AxyN+/zvDffiNWxvLDoEW66csmwwK5j/oMzrLzqcE+jQ5b9/hoo3jb9EaDSQiN8pvqD94QoQCSgE9OjBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-28T10:56:02.526347Z","bundle_sha256":"4dbbfc55c474990f98c321781a564f8f9dd29df1d118c8b183d7ad45b7e86d54"}}