{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:XJ54KQLKJ3QHEFFRRCN5DZAE6U","short_pith_number":"pith:XJ54KQLK","canonical_record":{"source":{"id":"2405.03003","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-05T17:15:24Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"797283006a152b890cb394dab398248201eec01b160f0b344945f2f78fd22261","abstract_canon_sha256":"b66ccbfd2055f8c452bc358f4e1e1b48841e59eb92c02daea06bba6132a80f53"},"schema_version":"1.0"},"canonical_sha256":"ba7bc5416a4ee07214b1889bd1e404f53fa65aa90811b00a34036e2886fca3bb","source":{"kind":"arxiv","id":"2405.03003","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.03003","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"arxiv_version","alias_value":"2405.03003v1","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.03003","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_12","alias_value":"XJ54KQLKJ3QH","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_16","alias_value":"XJ54KQLKJ3QHEFFR","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_8","alias_value":"XJ54KQLK","created_at":"2026-07-05T08:15:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:XJ54KQLKJ3QHEFFRRCN5DZAE6U","target":"record","payload":{"canonical_record":{"source":{"id":"2405.03003","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-05T17:15:24Z","cross_cats_sorted":["cs.AI","cs.CL"],"title_canon_sha256":"797283006a152b890cb394dab398248201eec01b160f0b344945f2f78fd22261","abstract_canon_sha256":"b66ccbfd2055f8c452bc358f4e1e1b48841e59eb92c02daea06bba6132a80f53"},"schema_version":"1.0"},"canonical_sha256":"ba7bc5416a4ee07214b1889bd1e404f53fa65aa90811b00a34036e2886fca3bb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:15:57.132383Z","signature_b64":"s/q/5gGwPusPrL8Zzd2cGreEG4i8uiCtQfRzYXrWAUWMXSiKmIK6M/+V86zYHGlLrRDbaOlvyYJqlBecuHArDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ba7bc5416a4ee07214b1889bd1e404f53fa65aa90811b00a34036e2886fca3bb","last_reissued_at":"2026-07-05T08:15:57.131938Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:15:57.131938Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.03003","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:15:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EpMjFr7b6RpjjxpaLUwiZUzukMTST1pzy/Iz0jkjc/mSYXQUE1TnjrBbh8B/rlOjr4UIT+nk9tXLFC7DHf5DBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T13:57:59.419347Z"},"content_sha256":"ddc4cd0ea24137b758e7d33c101c532a3cf93c7d86962502d689558f1a80c1c0","schema_version":"1.0","event_id":"sha256:ddc4cd0ea24137b758e7d33c101c532a3cf93c7d86962502d689558f1a80c1c0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:XJ54KQLKJ3QHEFFRRCN5DZAE6U","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Parameter-Efficient Fine-Tuning with Discrete Fourier Transform","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL"],"primary_cat":"cs.LG","authors_text":"Aochuan Chen, Bingzhe Wu, Jia Li, Liang Chen, Qichao Wang, Zijing Liu, Ziqi Gao","submitted_at":"2024-05-05T17:15:24Z","abstract_excerpt":"Low-rank adaptation~(LoRA) has recently gained much interest in fine-tuning foundation models. It effectively reduces the number of trainable parameters by incorporating low-rank matrices $A$ and $B$ to represent the weight change, i.e., $\\Delta W=BA$. Despite LoRA's progress, it faces storage challenges when handling extensive customization adaptations or larger base models. In this work, we aim to further compress trainable parameters by enjoying the powerful expressiveness of the Fourier transform. Specifically, we introduce FourierFT, which treats $\\Delta W$ as a matrix in the spatial doma"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.03003","kind":"arxiv","version":1},"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/2405.03003/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":"2026-07-05T08:15:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Cry1X1eoDXZ6MlNw8H3H/H7at1zvx2ye4MXjErLcB4ct+JvGtGmT7V+LhY5V+DPKw+6y3x4/O6JHy8t3uH1DAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T13:57:59.420141Z"},"content_sha256":"42586f4732fa8de2ec7944e90b9fbc3aec109a4764c78ad59a63b36dc94af175","schema_version":"1.0","event_id":"sha256:42586f4732fa8de2ec7944e90b9fbc3aec109a4764c78ad59a63b36dc94af175"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XJ54KQLKJ3QHEFFRRCN5DZAE6U/bundle.json","state_url":"https://pith.science/pith/XJ54KQLKJ3QHEFFRRCN5DZAE6U/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XJ54KQLKJ3QHEFFRRCN5DZAE6U/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":"2026-08-09T13:57:59Z","links":{"resolver":"https://pith.science/pith/XJ54KQLKJ3QHEFFRRCN5DZAE6U","bundle":"https://pith.science/pith/XJ54KQLKJ3QHEFFRRCN5DZAE6U/bundle.json","state":"https://pith.science/pith/XJ54KQLKJ3QHEFFRRCN5DZAE6U/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XJ54KQLKJ3QHEFFRRCN5DZAE6U/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XJ54KQLKJ3QHEFFRRCN5DZAE6U","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":"b66ccbfd2055f8c452bc358f4e1e1b48841e59eb92c02daea06bba6132a80f53","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-05T17:15:24Z","title_canon_sha256":"797283006a152b890cb394dab398248201eec01b160f0b344945f2f78fd22261"},"schema_version":"1.0","source":{"id":"2405.03003","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.03003","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"arxiv_version","alias_value":"2405.03003v1","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.03003","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_12","alias_value":"XJ54KQLKJ3QH","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_16","alias_value":"XJ54KQLKJ3QHEFFR","created_at":"2026-07-05T08:15:57Z"},{"alias_kind":"pith_short_8","alias_value":"XJ54KQLK","created_at":"2026-07-05T08:15:57Z"}],"graph_snapshots":[{"event_id":"sha256:42586f4732fa8de2ec7944e90b9fbc3aec109a4764c78ad59a63b36dc94af175","target":"graph","created_at":"2026-07-05T08:15:57Z","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/2405.03003/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Low-rank adaptation~(LoRA) has recently gained much interest in fine-tuning foundation models. It effectively reduces the number of trainable parameters by incorporating low-rank matrices $A$ and $B$ to represent the weight change, i.e., $\\Delta W=BA$. Despite LoRA's progress, it faces storage challenges when handling extensive customization adaptations or larger base models. In this work, we aim to further compress trainable parameters by enjoying the powerful expressiveness of the Fourier transform. Specifically, we introduce FourierFT, which treats $\\Delta W$ as a matrix in the spatial doma","authors_text":"Aochuan Chen, Bingzhe Wu, Jia Li, Liang Chen, Qichao Wang, Zijing Liu, Ziqi Gao","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-05T17:15:24Z","title":"Parameter-Efficient Fine-Tuning with Discrete Fourier Transform"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.03003","kind":"arxiv","version":1},"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:ddc4cd0ea24137b758e7d33c101c532a3cf93c7d86962502d689558f1a80c1c0","target":"record","created_at":"2026-07-05T08:15:57Z","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":"b66ccbfd2055f8c452bc358f4e1e1b48841e59eb92c02daea06bba6132a80f53","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-05-05T17:15:24Z","title_canon_sha256":"797283006a152b890cb394dab398248201eec01b160f0b344945f2f78fd22261"},"schema_version":"1.0","source":{"id":"2405.03003","kind":"arxiv","version":1}},"canonical_sha256":"ba7bc5416a4ee07214b1889bd1e404f53fa65aa90811b00a34036e2886fca3bb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ba7bc5416a4ee07214b1889bd1e404f53fa65aa90811b00a34036e2886fca3bb","first_computed_at":"2026-07-05T08:15:57.131938Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:15:57.131938Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"s/q/5gGwPusPrL8Zzd2cGreEG4i8uiCtQfRzYXrWAUWMXSiKmIK6M/+V86zYHGlLrRDbaOlvyYJqlBecuHArDA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:15:57.132383Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.03003","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ddc4cd0ea24137b758e7d33c101c532a3cf93c7d86962502d689558f1a80c1c0","sha256:42586f4732fa8de2ec7944e90b9fbc3aec109a4764c78ad59a63b36dc94af175"],"state_sha256":"436fa8cbd019f38064d3307db38529da4846f9d8afab7efc89f2ab59b1717a84"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8l0RdWgK2RL8AS8I0kcmql2+kEykTw101FzYDbdqy4UQHzsZTT96iUGSIrifcF/b7B8dTefINswKb6tUd6G1BA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T13:57:59.425315Z","bundle_sha256":"71c76ff8e61f9aa9c8e7eeb0fa5f18143fb5087f6506e0006963cd1b18e6c894"}}