{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:SPXDELWAI7LZ64Q53LGCAPGCQX","short_pith_number":"pith:SPXDELWA","canonical_record":{"source":{"id":"2402.16842","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-26T18:59:12Z","cross_cats_sorted":[],"title_canon_sha256":"db63a0e66c9bb44b100b41733988948bb1dacb048174e1a65369801b0bd8775e","abstract_canon_sha256":"8227a86535980f4c9be610aa3663756f31617322d3e65dfa5c5fcbbd91c08c23"},"schema_version":"1.0"},"canonical_sha256":"93ee322ec047d79f721ddacc203cc285c7094f146407b80b05fe885dd24e518c","source":{"kind":"arxiv","id":"2402.16842","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.16842","created_at":"2026-07-05T07:49:56Z"},{"alias_kind":"arxiv_version","alias_value":"2402.16842v2","created_at":"2026-07-05T07:49:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.16842","created_at":"2026-07-05T07:49:56Z"},{"alias_kind":"pith_short_12","alias_value":"SPXDELWAI7LZ","created_at":"2026-07-05T07:49:56Z"},{"alias_kind":"pith_short_16","alias_value":"SPXDELWAI7LZ64Q5","created_at":"2026-07-05T07:49:56Z"},{"alias_kind":"pith_short_8","alias_value":"SPXDELWA","created_at":"2026-07-05T07:49:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:SPXDELWAI7LZ64Q53LGCAPGCQX","target":"record","payload":{"canonical_record":{"source":{"id":"2402.16842","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-26T18:59:12Z","cross_cats_sorted":[],"title_canon_sha256":"db63a0e66c9bb44b100b41733988948bb1dacb048174e1a65369801b0bd8775e","abstract_canon_sha256":"8227a86535980f4c9be610aa3663756f31617322d3e65dfa5c5fcbbd91c08c23"},"schema_version":"1.0"},"canonical_sha256":"93ee322ec047d79f721ddacc203cc285c7094f146407b80b05fe885dd24e518c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:49:56.327219Z","signature_b64":"F2DOAUeFmAybsyFQkOHRCZd+Nolcswvr0hP/MjqrR7M8xamIIZ/v8U8DbN5zPCrq4T5J+2WPD+ftv//vcp9KCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"93ee322ec047d79f721ddacc203cc285c7094f146407b80b05fe885dd24e518c","last_reissued_at":"2026-07-05T07:49:56.326628Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:49:56.326628Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.16842","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":"2026-07-05T07:49:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/THi6sihHvYq/gm+c0JM2oSZPutv/ydR7Fy7JQQeapTi8VhhJ+HcruciLxOrcwTM+pQKFs0DRkTMe2dWBK+1Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:26:32.872594Z"},"content_sha256":"0dce6c72da3d5dc486146c7c3913b328c9560d7c41c298aa2221258ec9dd5942","schema_version":"1.0","event_id":"sha256:0dce6c72da3d5dc486146c7c3913b328c9560d7c41c298aa2221258ec9dd5942"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:SPXDELWAI7LZ64Q53LGCAPGCQX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Asymmetry in Low-Rank Adapters of Foundation Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Haitz S\\'aez de Oc\\'ariz Borde, Jiacheng Zhu, Justin Solomon, Kimia Nadjahi, Kristjan Greenewald, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Rickard Br\\\"uel Gabrielsson","submitted_at":"2024-02-26T18:59:12Z","abstract_excerpt":"Parameter-efficient fine-tuning optimizes large, pre-trained foundation models by updating a subset of parameters; in this class, Low-Rank Adaptation (LoRA) is particularly effective. Inspired by an effort to investigate the different roles of LoRA matrices during fine-tuning, this paper characterizes and leverages unexpected asymmetry in the importance of low-rank adapter matrices. Specifically, when updating the parameter matrices of a neural network by adding a product $BA$, we observe that the $B$ and $A$ matrices have distinct functions: $A$ extracts features from the input, while $B$ use"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.16842","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/2402.16842/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":"2026-07-05T07:49:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bOPh1aKf43nzCcUrJk8TfXec05pIVUOu6n3L0VoTyUjpWQ7cAP7o8V5Xcc16d1FIcxFdGSYc2q5R8IbGo35jAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T17:26:32.872970Z"},"content_sha256":"6d2f6dc402db2b93e951c6b714a31e36f626555e8a0acec84fd641415a5fe93b","schema_version":"1.0","event_id":"sha256:6d2f6dc402db2b93e951c6b714a31e36f626555e8a0acec84fd641415a5fe93b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SPXDELWAI7LZ64Q53LGCAPGCQX/bundle.json","state_url":"https://pith.science/pith/SPXDELWAI7LZ64Q53LGCAPGCQX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SPXDELWAI7LZ64Q53LGCAPGCQX/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":"2026-07-06T17:26:32Z","links":{"resolver":"https://pith.science/pith/SPXDELWAI7LZ64Q53LGCAPGCQX","bundle":"https://pith.science/pith/SPXDELWAI7LZ64Q53LGCAPGCQX/bundle.json","state":"https://pith.science/pith/SPXDELWAI7LZ64Q53LGCAPGCQX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SPXDELWAI7LZ64Q53LGCAPGCQX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:SPXDELWAI7LZ64Q53LGCAPGCQX","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":"8227a86535980f4c9be610aa3663756f31617322d3e65dfa5c5fcbbd91c08c23","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-26T18:59:12Z","title_canon_sha256":"db63a0e66c9bb44b100b41733988948bb1dacb048174e1a65369801b0bd8775e"},"schema_version":"1.0","source":{"id":"2402.16842","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.16842","created_at":"2026-07-05T07:49:56Z"},{"alias_kind":"arxiv_version","alias_value":"2402.16842v2","created_at":"2026-07-05T07:49:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.16842","created_at":"2026-07-05T07:49:56Z"},{"alias_kind":"pith_short_12","alias_value":"SPXDELWAI7LZ","created_at":"2026-07-05T07:49:56Z"},{"alias_kind":"pith_short_16","alias_value":"SPXDELWAI7LZ64Q5","created_at":"2026-07-05T07:49:56Z"},{"alias_kind":"pith_short_8","alias_value":"SPXDELWA","created_at":"2026-07-05T07:49:56Z"}],"graph_snapshots":[{"event_id":"sha256:6d2f6dc402db2b93e951c6b714a31e36f626555e8a0acec84fd641415a5fe93b","target":"graph","created_at":"2026-07-05T07:49:56Z","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/2402.16842/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Parameter-efficient fine-tuning optimizes large, pre-trained foundation models by updating a subset of parameters; in this class, Low-Rank Adaptation (LoRA) is particularly effective. Inspired by an effort to investigate the different roles of LoRA matrices during fine-tuning, this paper characterizes and leverages unexpected asymmetry in the importance of low-rank adapter matrices. Specifically, when updating the parameter matrices of a neural network by adding a product $BA$, we observe that the $B$ and $A$ matrices have distinct functions: $A$ extracts features from the input, while $B$ use","authors_text":"Haitz S\\'aez de Oc\\'ariz Borde, Jiacheng Zhu, Justin Solomon, Kimia Nadjahi, Kristjan Greenewald, Leshem Choshen, Marzyeh Ghassemi, Mikhail Yurochkin, Rickard Br\\\"uel Gabrielsson","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-26T18:59:12Z","title":"Asymmetry in Low-Rank Adapters of Foundation Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.16842","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":"sha256:0dce6c72da3d5dc486146c7c3913b328c9560d7c41c298aa2221258ec9dd5942","target":"record","created_at":"2026-07-05T07:49:56Z","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":"8227a86535980f4c9be610aa3663756f31617322d3e65dfa5c5fcbbd91c08c23","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-02-26T18:59:12Z","title_canon_sha256":"db63a0e66c9bb44b100b41733988948bb1dacb048174e1a65369801b0bd8775e"},"schema_version":"1.0","source":{"id":"2402.16842","kind":"arxiv","version":2}},"canonical_sha256":"93ee322ec047d79f721ddacc203cc285c7094f146407b80b05fe885dd24e518c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"93ee322ec047d79f721ddacc203cc285c7094f146407b80b05fe885dd24e518c","first_computed_at":"2026-07-05T07:49:56.326628Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:49:56.326628Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"F2DOAUeFmAybsyFQkOHRCZd+Nolcswvr0hP/MjqrR7M8xamIIZ/v8U8DbN5zPCrq4T5J+2WPD+ftv//vcp9KCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:49:56.327219Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.16842","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0dce6c72da3d5dc486146c7c3913b328c9560d7c41c298aa2221258ec9dd5942","sha256:6d2f6dc402db2b93e951c6b714a31e36f626555e8a0acec84fd641415a5fe93b"],"state_sha256":"babe91c71cdf3efb0b57186588cde718c78d06a8e0a67d110bcd71d1b27900e1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IqcxZeBXszdU+KptEYfekYoFLtx/QdxbX9zuDAyL23gSIHmXZJ25XSHU1hgYIP4OtjveCHmOV5by5banQiCKAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T17:26:32.875049Z","bundle_sha256":"5ca8ea7738b5fe4c3ca12abf5d4d63fa31dac0e6a07d78bfff9c02fc17c2c2d0"}}