{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:SOBATLE4VQE7WIGJMCPY2VFSSO","short_pith_number":"pith:SOBATLE4","schema_version":"1.0","canonical_sha256":"938209ac9cac09fb20c9609f8d54b293bcef9e26ad43bf7587306ef498f5b9ad","source":{"kind":"arxiv","id":"2503.06676","version":1},"attestation_state":"computed","paper":{"title":"Seeing Delta Parameters as JPEG Images: Data-Free Delta Compression with Discrete Cosine Transform","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","eess.IV"],"primary_cat":"cs.CV","authors_text":"Biqing Qi, Chenyu Huang, Lei Bai, Peng Ye, Shenghe Zheng, Tao Chen, Wanli Ouyang, Xiaohui Wang","submitted_at":"2025-03-09T16:03:48Z","abstract_excerpt":"With transformer-based models and the pretrain-finetune paradigm becoming mainstream, the high storage and deployment costs of individual finetuned models on multiple tasks pose critical challenges. Delta compression attempts to lower the costs by reducing the redundancy of delta parameters (i.e., the difference between the finetuned and pre-trained model weights). However, existing methods usually face problems including data accessibility and training requirements. To tackle this issue, we introduce Delta-DCT, the first data-free delta compression method inspired by classic JPEG image compre"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2503.06676","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-03-09T16:03:48Z","cross_cats_sorted":["cs.LG","eess.IV"],"title_canon_sha256":"f5ba6902a1ba587864663fa80f6776cbe3fbb16450804ea6ff847c1e5d98c0ec","abstract_canon_sha256":"908e278b1c7475fe2c5dcf5546a459b899cda1cae7b5ed951458cc2617e1b3df"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:27:39.993640Z","signature_b64":"wOg904eXB4yP6d6yAos8m7XUZc70b4uhUua0acNtyF2JVIkpu3pGldK3YCGBX5rDokd74f68bnxwBf/wGgXhBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"938209ac9cac09fb20c9609f8d54b293bcef9e26ad43bf7587306ef498f5b9ad","last_reissued_at":"2026-07-05T10:27:39.992953Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:27:39.992953Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Seeing Delta Parameters as JPEG Images: Data-Free Delta Compression with Discrete Cosine Transform","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","eess.IV"],"primary_cat":"cs.CV","authors_text":"Biqing Qi, Chenyu Huang, Lei Bai, Peng Ye, Shenghe Zheng, Tao Chen, Wanli Ouyang, Xiaohui Wang","submitted_at":"2025-03-09T16:03:48Z","abstract_excerpt":"With transformer-based models and the pretrain-finetune paradigm becoming mainstream, the high storage and deployment costs of individual finetuned models on multiple tasks pose critical challenges. Delta compression attempts to lower the costs by reducing the redundancy of delta parameters (i.e., the difference between the finetuned and pre-trained model weights). However, existing methods usually face problems including data accessibility and training requirements. To tackle this issue, we introduce Delta-DCT, the first data-free delta compression method inspired by classic JPEG image compre"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.06676","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/2503.06676/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2503.06676","created_at":"2026-07-05T10:27:39.993025+00:00"},{"alias_kind":"arxiv_version","alias_value":"2503.06676v1","created_at":"2026-07-05T10:27:39.993025+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.06676","created_at":"2026-07-05T10:27:39.993025+00:00"},{"alias_kind":"pith_short_12","alias_value":"SOBATLE4VQE7","created_at":"2026-07-05T10:27:39.993025+00:00"},{"alias_kind":"pith_short_16","alias_value":"SOBATLE4VQE7WIGJ","created_at":"2026-07-05T10:27:39.993025+00:00"},{"alias_kind":"pith_short_8","alias_value":"SOBATLE4","created_at":"2026-07-05T10:27:39.993025+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2505.11344","citing_title":"Dynamic Base model Shift for Delta Compression","ref_index":17,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/SOBATLE4VQE7WIGJMCPY2VFSSO","json":"https://pith.science/pith/SOBATLE4VQE7WIGJMCPY2VFSSO.json","graph_json":"https://pith.science/api/pith-number/SOBATLE4VQE7WIGJMCPY2VFSSO/graph.json","events_json":"https://pith.science/api/pith-number/SOBATLE4VQE7WIGJMCPY2VFSSO/events.json","paper":"https://pith.science/paper/SOBATLE4"},"agent_actions":{"view_html":"https://pith.science/pith/SOBATLE4VQE7WIGJMCPY2VFSSO","download_json":"https://pith.science/pith/SOBATLE4VQE7WIGJMCPY2VFSSO.json","view_paper":"https://pith.science/paper/SOBATLE4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2503.06676&json=true","fetch_graph":"https://pith.science/api/pith-number/SOBATLE4VQE7WIGJMCPY2VFSSO/graph.json","fetch_events":"https://pith.science/api/pith-number/SOBATLE4VQE7WIGJMCPY2VFSSO/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/SOBATLE4VQE7WIGJMCPY2VFSSO/action/timestamp_anchor","attest_storage":"https://pith.science/pith/SOBATLE4VQE7WIGJMCPY2VFSSO/action/storage_attestation","attest_author":"https://pith.science/pith/SOBATLE4VQE7WIGJMCPY2VFSSO/action/author_attestation","sign_citation":"https://pith.science/pith/SOBATLE4VQE7WIGJMCPY2VFSSO/action/citation_signature","submit_replication":"https://pith.science/pith/SOBATLE4VQE7WIGJMCPY2VFSSO/action/replication_record"}},"created_at":"2026-07-05T10:27:39.993025+00:00","updated_at":"2026-07-05T10:27:39.993025+00:00"}