{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:64MRHGFVU7IAKI7HYMM56HJALV","short_pith_number":"pith:64MRHGFV","canonical_record":{"source":{"id":"2504.01521","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-02T09:07:55Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"9d5c714bd3aebbb3c20fc14a9702d4c9acefac9da393066809286dcc25750210","abstract_canon_sha256":"68923eec08db94d6b9939af0d15f2a775bda81a1208b51a0dee11b0ae438d275"},"schema_version":"1.0"},"canonical_sha256":"f7191398b5a7d00523e7c319df1d205d5ef0e5102d85e66f6ec04f512a337dc2","source":{"kind":"arxiv","id":"2504.01521","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.01521","created_at":"2026-07-05T10:43:16Z"},{"alias_kind":"arxiv_version","alias_value":"2504.01521v1","created_at":"2026-07-05T10:43:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.01521","created_at":"2026-07-05T10:43:16Z"},{"alias_kind":"pith_short_12","alias_value":"64MRHGFVU7IA","created_at":"2026-07-05T10:43:16Z"},{"alias_kind":"pith_short_16","alias_value":"64MRHGFVU7IAKI7H","created_at":"2026-07-05T10:43:16Z"},{"alias_kind":"pith_short_8","alias_value":"64MRHGFV","created_at":"2026-07-05T10:43:16Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:64MRHGFVU7IAKI7HYMM56HJALV","target":"record","payload":{"canonical_record":{"source":{"id":"2504.01521","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-02T09:07:55Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"9d5c714bd3aebbb3c20fc14a9702d4c9acefac9da393066809286dcc25750210","abstract_canon_sha256":"68923eec08db94d6b9939af0d15f2a775bda81a1208b51a0dee11b0ae438d275"},"schema_version":"1.0"},"canonical_sha256":"f7191398b5a7d00523e7c319df1d205d5ef0e5102d85e66f6ec04f512a337dc2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:43:16.666163Z","signature_b64":"sUO+2eT4YICWTl+6RfLfLkZ2strqGm+bjLLTzwv+iB365AF6OiAQNDMlqjU9TA9N5CjtE5UoyOsDPXlQN2kjBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f7191398b5a7d00523e7c319df1d205d5ef0e5102d85e66f6ec04f512a337dc2","last_reissued_at":"2026-07-05T10:43:16.665625Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:43:16.665625Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.01521","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":"2026-07-05T10:43:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2xR7WVgUflfZTnQhoC22KUmWgLdbDAwusDOfSthrhBMvacIAvy6zwxdDEXMni6l+3sFRnT5PC0I1l1+TeCk9Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-26T17:44:05.237799Z"},"content_sha256":"438c89262d9a4a1903f2b00c35ec87d864616a50129533ce08273cd0f69211e3","schema_version":"1.0","event_id":"sha256:438c89262d9a4a1903f2b00c35ec87d864616a50129533ce08273cd0f69211e3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:64MRHGFVU7IAKI7HYMM56HJALV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Jianmin Wang, Jincheng Zhong, Mingsheng Long, Xiangcheng Zhang","submitted_at":"2025-04-02T09:07:55Z","abstract_excerpt":"Recent advancements in diffusion models have revolutionized generative modeling. However, the impressive and vivid outputs they produce often come at the cost of significant model scaling and increased computational demands. Consequently, building personalized diffusion models based on off-the-shelf models has emerged as an appealing alternative. In this paper, we introduce a novel perspective on conditional generation for transferring a pre-trained model. From this viewpoint, we propose *Domain Guidance*, a straightforward transfer approach that leverages pre-trained knowledge to guide the sa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.01521","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/2504.01521/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":"2026-07-05T10:43:16Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vTP93WWyUVPleU+XtgeZ8+vjqviMtt9dK3VGFZm5DrUUToXAS0YxqFUtZGZf5w1COF/+opEI1HejS7VQ+Kd8Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-26T17:44:05.238175Z"},"content_sha256":"ff07c4f8705ad91cb4b11f83f48553727fe7d2221e13412b3766f7efe2e43e71","schema_version":"1.0","event_id":"sha256:ff07c4f8705ad91cb4b11f83f48553727fe7d2221e13412b3766f7efe2e43e71"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/64MRHGFVU7IAKI7HYMM56HJALV/bundle.json","state_url":"https://pith.science/pith/64MRHGFVU7IAKI7HYMM56HJALV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/64MRHGFVU7IAKI7HYMM56HJALV/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":"2026-07-26T17:44:05Z","links":{"resolver":"https://pith.science/pith/64MRHGFVU7IAKI7HYMM56HJALV","bundle":"https://pith.science/pith/64MRHGFVU7IAKI7HYMM56HJALV/bundle.json","state":"https://pith.science/pith/64MRHGFVU7IAKI7HYMM56HJALV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/64MRHGFVU7IAKI7HYMM56HJALV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:64MRHGFVU7IAKI7HYMM56HJALV","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":"68923eec08db94d6b9939af0d15f2a775bda81a1208b51a0dee11b0ae438d275","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-02T09:07:55Z","title_canon_sha256":"9d5c714bd3aebbb3c20fc14a9702d4c9acefac9da393066809286dcc25750210"},"schema_version":"1.0","source":{"id":"2504.01521","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.01521","created_at":"2026-07-05T10:43:16Z"},{"alias_kind":"arxiv_version","alias_value":"2504.01521v1","created_at":"2026-07-05T10:43:16Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.01521","created_at":"2026-07-05T10:43:16Z"},{"alias_kind":"pith_short_12","alias_value":"64MRHGFVU7IA","created_at":"2026-07-05T10:43:16Z"},{"alias_kind":"pith_short_16","alias_value":"64MRHGFVU7IAKI7H","created_at":"2026-07-05T10:43:16Z"},{"alias_kind":"pith_short_8","alias_value":"64MRHGFV","created_at":"2026-07-05T10:43:16Z"}],"graph_snapshots":[{"event_id":"sha256:ff07c4f8705ad91cb4b11f83f48553727fe7d2221e13412b3766f7efe2e43e71","target":"graph","created_at":"2026-07-05T10:43:16Z","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/2504.01521/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advancements in diffusion models have revolutionized generative modeling. However, the impressive and vivid outputs they produce often come at the cost of significant model scaling and increased computational demands. Consequently, building personalized diffusion models based on off-the-shelf models has emerged as an appealing alternative. In this paper, we introduce a novel perspective on conditional generation for transferring a pre-trained model. From this viewpoint, we propose *Domain Guidance*, a straightforward transfer approach that leverages pre-trained knowledge to guide the sa","authors_text":"Jianmin Wang, Jincheng Zhong, Mingsheng Long, Xiangcheng Zhang","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-02T09:07:55Z","title":"Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.01521","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":"sha256:438c89262d9a4a1903f2b00c35ec87d864616a50129533ce08273cd0f69211e3","target":"record","created_at":"2026-07-05T10:43:16Z","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":"68923eec08db94d6b9939af0d15f2a775bda81a1208b51a0dee11b0ae438d275","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-04-02T09:07:55Z","title_canon_sha256":"9d5c714bd3aebbb3c20fc14a9702d4c9acefac9da393066809286dcc25750210"},"schema_version":"1.0","source":{"id":"2504.01521","kind":"arxiv","version":1}},"canonical_sha256":"f7191398b5a7d00523e7c319df1d205d5ef0e5102d85e66f6ec04f512a337dc2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f7191398b5a7d00523e7c319df1d205d5ef0e5102d85e66f6ec04f512a337dc2","first_computed_at":"2026-07-05T10:43:16.665625Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:43:16.665625Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sUO+2eT4YICWTl+6RfLfLkZ2strqGm+bjLLTzwv+iB365AF6OiAQNDMlqjU9TA9N5CjtE5UoyOsDPXlQN2kjBw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:43:16.666163Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.01521","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:438c89262d9a4a1903f2b00c35ec87d864616a50129533ce08273cd0f69211e3","sha256:ff07c4f8705ad91cb4b11f83f48553727fe7d2221e13412b3766f7efe2e43e71"],"state_sha256":"dfd87e38adc0cfdd6bae4e372cdbe1547760c34b9d94eac07d7d6daee202140e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"bkzvwMZc7Vq8FXw304YH2WWCOskgA6vaf7GXppPjzQq/tjq2/xqUWhWyyRA4eyVrAdKbZYN988w9g0GkKvqdAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-26T17:44:05.240675Z","bundle_sha256":"3e961dcc1d96ad81cf372f3a818da63262d8e8c57731e329ce659006f7687189"}}