{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:QKRTTKWURHHFHRDFIVO3JBJZIJ","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":"c1a63285e1b2def489aa39ca5b0b29b0f4bfdc8a8890c8c82a976554f3d7db3f","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-07T00:34:30Z","title_canon_sha256":"d0219e28f7ee1612d0384fe31a226aa0d4cc84503fd84f87b2297836fc8dafe4"},"schema_version":"1.0","source":{"id":"2607.05711","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.05711","created_at":"2026-07-08T01:18:42Z"},{"alias_kind":"arxiv_version","alias_value":"2607.05711v1","created_at":"2026-07-08T01:18:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.05711","created_at":"2026-07-08T01:18:42Z"},{"alias_kind":"pith_short_12","alias_value":"QKRTTKWURHHF","created_at":"2026-07-08T01:18:42Z"},{"alias_kind":"pith_short_16","alias_value":"QKRTTKWURHHFHRDF","created_at":"2026-07-08T01:18:42Z"},{"alias_kind":"pith_short_8","alias_value":"QKRTTKWU","created_at":"2026-07-08T01:18:42Z"}],"graph_snapshots":[{"event_id":"sha256:fb22c8bc02bf9b02fc640ca9cac3d0a25909472549e401e2968379de2bb45c2b","target":"graph","created_at":"2026-07-08T01:18:42Z","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/2607.05711/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion models have become a dominant paradigm for high-quality generative modeling, while post-training is essential for adapting them to diverse downstream applications. However, post-training of large diffusion models is still challenging due to the prohibitive memory footprints and slow training speed, which existing parameter-efficient fine-tuning methods only partially address. To overcome these limitations, we propose FourTune, an efficient post-training framework for diffusion models based on an end-to-end W4A4G4 paradigm. FourTune introduces a triple-branch hybrid pipeline that augm","authors_text":"Bowen Xue, Haocheng Xi, Jun-Yan Zhu, Lvmin Zhang, Maneesh Agrawala, Muyang Li, Song Han, Xingyang Li, Yujun Lin, Zhekai Zhang, Zihan Min","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-07T00:34:30Z","title":"FourTune: Towards Fully 4-Bit Efficient Post-Training for Diffusion Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.05711","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":"sha256:07dfa683e5273c7d7feb68b9fc584b95910a5975b36d5a7125ed0c32ca630e1e","target":"record","created_at":"2026-07-08T01:18:42Z","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":"c1a63285e1b2def489aa39ca5b0b29b0f4bfdc8a8890c8c82a976554f3d7db3f","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-07T00:34:30Z","title_canon_sha256":"d0219e28f7ee1612d0384fe31a226aa0d4cc84503fd84f87b2297836fc8dafe4"},"schema_version":"1.0","source":{"id":"2607.05711","kind":"arxiv","version":1}},"canonical_sha256":"82a339aad489ce53c465455db485394279064df8f30751e4d03b498a431ee28b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"82a339aad489ce53c465455db485394279064df8f30751e4d03b498a431ee28b","first_computed_at":"2026-07-08T01:18:42.171027Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-08T01:18:42.171027Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wEkBRJH6aL1hBtroXqbVglUt8tqh9hLNx7K7byeAyFStcNtTxPzIo5DQu1kj64vKpsv1px5FT5M1WtVvjC+kCw==","signature_status":"signed_v1","signed_at":"2026-07-08T01:18:42.171501Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.05711","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:07dfa683e5273c7d7feb68b9fc584b95910a5975b36d5a7125ed0c32ca630e1e","sha256:fb22c8bc02bf9b02fc640ca9cac3d0a25909472549e401e2968379de2bb45c2b"],"state_sha256":"3867a718f1af00b0e813e7f1ab0181e12a068166b69ebfc849976ceeaeb23781"}