{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:DRIH34WAF7SB54XTXVTKFUBU6B","short_pith_number":"pith:DRIH34WA","canonical_record":{"source":{"id":"2302.02284","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-02-05T02:47:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"965412178d9da3eec8fc6ad9a71fc8f9974a65f4c99c39ebf979fa8a68f89084","abstract_canon_sha256":"f8f1a740cc465ec883204626ad68063140ac1f13e381eef71437b2e47d9ece03"},"schema_version":"1.0"},"canonical_sha256":"1c507df2c02fe41ef2f3bd66a2d034f06a30c4015a962cb6ff4fcb5469a5dbf1","source":{"kind":"arxiv","id":"2302.02284","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.02284","created_at":"2026-07-05T05:38:50Z"},{"alias_kind":"arxiv_version","alias_value":"2302.02284v1","created_at":"2026-07-05T05:38:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.02284","created_at":"2026-07-05T05:38:50Z"},{"alias_kind":"pith_short_12","alias_value":"DRIH34WAF7SB","created_at":"2026-07-05T05:38:50Z"},{"alias_kind":"pith_short_16","alias_value":"DRIH34WAF7SB54XT","created_at":"2026-07-05T05:38:50Z"},{"alias_kind":"pith_short_8","alias_value":"DRIH34WA","created_at":"2026-07-05T05:38:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:DRIH34WAF7SB54XTXVTKFUBU6B","target":"record","payload":{"canonical_record":{"source":{"id":"2302.02284","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-02-05T02:47:13Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"965412178d9da3eec8fc6ad9a71fc8f9974a65f4c99c39ebf979fa8a68f89084","abstract_canon_sha256":"f8f1a740cc465ec883204626ad68063140ac1f13e381eef71437b2e47d9ece03"},"schema_version":"1.0"},"canonical_sha256":"1c507df2c02fe41ef2f3bd66a2d034f06a30c4015a962cb6ff4fcb5469a5dbf1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:38:50.938045Z","signature_b64":"ZL5VZownCI1h2p6/56HkIZJqYw2oapRpWnekvDOgRUafw7NAKoSn7thf/Ohx5xsm6PaeqhEXVqxxh30b+eznAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1c507df2c02fe41ef2f3bd66a2d034f06a30c4015a962cb6ff4fcb5469a5dbf1","last_reissued_at":"2026-07-05T05:38:50.937649Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:38:50.937649Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2302.02284","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":"2026-07-05T05:38:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iZp6RKwML3EpefW9c1fHDkgw7K5UdcYzLlsTPkldKwi6qSelv4tBIr6yVuwzNGW0VSZavyr6/e2GT4sHRq3SBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T04:48:22.099625Z"},"content_sha256":"35db769ed85dd2afe6e77902cd0754392bb2bb21ac65532f4b0234d66869292a","schema_version":"1.0","event_id":"sha256:35db769ed85dd2afe6e77902cd0754392bb2bb21ac65532f4b0234d66869292a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:DRIH34WAF7SB54XTXVTKFUBU6B","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Design Booster: A Text-Guided Diffusion Model for Image Translation with Spatial Layout Preservation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Qian He, Shancheng Fang, Shiqi Sun, Wei Liu","submitted_at":"2023-02-05T02:47:13Z","abstract_excerpt":"Diffusion models are able to generate photorealistic images in arbitrary scenes. However, when applying diffusion models to image translation, there exists a trade-off between maintaining spatial structure and high-quality content. Besides, existing methods are mainly based on test-time optimization or fine-tuning model for each input image, which are extremely time-consuming for practical applications. To address these issues, we propose a new approach for flexible image translation by learning a layout-aware image condition together with a text condition. Specifically, our method co-encodes "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.02284","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/2302.02284/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":"2026-07-05T05:38:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3tyV3hscFIs+zXszwolP8mPlvI2GEs/ryhx0KLrgCVtdSUuOpRwSD8c2K5btYmC3ZM2VmGknXqHJCHUarPXsDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T04:48:22.100002Z"},"content_sha256":"db852701e86efba8411f9626aa51b5fa0a0b945e17801fea87c418c018e766c3","schema_version":"1.0","event_id":"sha256:db852701e86efba8411f9626aa51b5fa0a0b945e17801fea87c418c018e766c3"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DRIH34WAF7SB54XTXVTKFUBU6B/bundle.json","state_url":"https://pith.science/pith/DRIH34WAF7SB54XTXVTKFUBU6B/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DRIH34WAF7SB54XTXVTKFUBU6B/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":"2026-07-09T04:48:22Z","links":{"resolver":"https://pith.science/pith/DRIH34WAF7SB54XTXVTKFUBU6B","bundle":"https://pith.science/pith/DRIH34WAF7SB54XTXVTKFUBU6B/bundle.json","state":"https://pith.science/pith/DRIH34WAF7SB54XTXVTKFUBU6B/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DRIH34WAF7SB54XTXVTKFUBU6B/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:DRIH34WAF7SB54XTXVTKFUBU6B","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":"f8f1a740cc465ec883204626ad68063140ac1f13e381eef71437b2e47d9ece03","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-02-05T02:47:13Z","title_canon_sha256":"965412178d9da3eec8fc6ad9a71fc8f9974a65f4c99c39ebf979fa8a68f89084"},"schema_version":"1.0","source":{"id":"2302.02284","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2302.02284","created_at":"2026-07-05T05:38:50Z"},{"alias_kind":"arxiv_version","alias_value":"2302.02284v1","created_at":"2026-07-05T05:38:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2302.02284","created_at":"2026-07-05T05:38:50Z"},{"alias_kind":"pith_short_12","alias_value":"DRIH34WAF7SB","created_at":"2026-07-05T05:38:50Z"},{"alias_kind":"pith_short_16","alias_value":"DRIH34WAF7SB54XT","created_at":"2026-07-05T05:38:50Z"},{"alias_kind":"pith_short_8","alias_value":"DRIH34WA","created_at":"2026-07-05T05:38:50Z"}],"graph_snapshots":[{"event_id":"sha256:db852701e86efba8411f9626aa51b5fa0a0b945e17801fea87c418c018e766c3","target":"graph","created_at":"2026-07-05T05:38:50Z","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/2302.02284/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion models are able to generate photorealistic images in arbitrary scenes. However, when applying diffusion models to image translation, there exists a trade-off between maintaining spatial structure and high-quality content. Besides, existing methods are mainly based on test-time optimization or fine-tuning model for each input image, which are extremely time-consuming for practical applications. To address these issues, we propose a new approach for flexible image translation by learning a layout-aware image condition together with a text condition. Specifically, our method co-encodes ","authors_text":"Qian He, Shancheng Fang, Shiqi Sun, Wei Liu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-02-05T02:47:13Z","title":"Design Booster: A Text-Guided Diffusion Model for Image Translation with Spatial Layout Preservation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.02284","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":"sha256:35db769ed85dd2afe6e77902cd0754392bb2bb21ac65532f4b0234d66869292a","target":"record","created_at":"2026-07-05T05:38:50Z","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":"f8f1a740cc465ec883204626ad68063140ac1f13e381eef71437b2e47d9ece03","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-02-05T02:47:13Z","title_canon_sha256":"965412178d9da3eec8fc6ad9a71fc8f9974a65f4c99c39ebf979fa8a68f89084"},"schema_version":"1.0","source":{"id":"2302.02284","kind":"arxiv","version":1}},"canonical_sha256":"1c507df2c02fe41ef2f3bd66a2d034f06a30c4015a962cb6ff4fcb5469a5dbf1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1c507df2c02fe41ef2f3bd66a2d034f06a30c4015a962cb6ff4fcb5469a5dbf1","first_computed_at":"2026-07-05T05:38:50.937649Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:38:50.937649Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZL5VZownCI1h2p6/56HkIZJqYw2oapRpWnekvDOgRUafw7NAKoSn7thf/Ohx5xsm6PaeqhEXVqxxh30b+eznAg==","signature_status":"signed_v1","signed_at":"2026-07-05T05:38:50.938045Z","signed_message":"canonical_sha256_bytes"},"source_id":"2302.02284","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:35db769ed85dd2afe6e77902cd0754392bb2bb21ac65532f4b0234d66869292a","sha256:db852701e86efba8411f9626aa51b5fa0a0b945e17801fea87c418c018e766c3"],"state_sha256":"81a96f4b0259e7ac1b2688309f46b9a4d31bbd86f1ebc328d19fe2fa81a55fda"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ikHcKh95CfKwzWwmTME10EpDCHhKSz9+hAGBo/ZziPIfeGFcOooP+qxLX3u2xYIKH84mrvyAFNscGUKNE3sxDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T04:48:22.101962Z","bundle_sha256":"0742839da627f26be7464c4621593a66bd5b1d3eda0e7f2f378bcf1cb6c3403a"}}