{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:SXOCCZB2NJWVDK3PUTH4TRS2K4","short_pith_number":"pith:SXOCCZB2","canonical_record":{"source":{"id":"2410.21966","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-29T11:49:39Z","cross_cats_sorted":[],"title_canon_sha256":"b15aebb195757b85a501357506c030cf53885bf2d15e072b12807d9ca6759616","abstract_canon_sha256":"4e665e0152e07dc4a81b20f5b3cabdc5b47ab066f47d9eb71ec784d9445900ef"},"schema_version":"1.0"},"canonical_sha256":"95dc21643a6a6d51ab6fa4cfc9c65a572eec51201eaa181e4cd55d188369dc00","source":{"kind":"arxiv","id":"2410.21966","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.21966","created_at":"2026-07-05T09:30:23Z"},{"alias_kind":"arxiv_version","alias_value":"2410.21966v2","created_at":"2026-07-05T09:30:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.21966","created_at":"2026-07-05T09:30:23Z"},{"alias_kind":"pith_short_12","alias_value":"SXOCCZB2NJWV","created_at":"2026-07-05T09:30:23Z"},{"alias_kind":"pith_short_16","alias_value":"SXOCCZB2NJWVDK3P","created_at":"2026-07-05T09:30:23Z"},{"alias_kind":"pith_short_8","alias_value":"SXOCCZB2","created_at":"2026-07-05T09:30:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:SXOCCZB2NJWVDK3PUTH4TRS2K4","target":"record","payload":{"canonical_record":{"source":{"id":"2410.21966","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-29T11:49:39Z","cross_cats_sorted":[],"title_canon_sha256":"b15aebb195757b85a501357506c030cf53885bf2d15e072b12807d9ca6759616","abstract_canon_sha256":"4e665e0152e07dc4a81b20f5b3cabdc5b47ab066f47d9eb71ec784d9445900ef"},"schema_version":"1.0"},"canonical_sha256":"95dc21643a6a6d51ab6fa4cfc9c65a572eec51201eaa181e4cd55d188369dc00","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:30:23.733251Z","signature_b64":"dnOiBRb83uzHpWtRkXUgYcyza3cT6ZRHll7RX8gxYjPOfMsfMoF5FHcvKjmCzNw3eDb7k1zdpiVJXg93X6c2BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"95dc21643a6a6d51ab6fa4cfc9c65a572eec51201eaa181e4cd55d188369dc00","last_reissued_at":"2026-07-05T09:30:23.732753Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:30:23.732753Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.21966","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:30:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3L/VjIPu3n54OMSpfVD5WbK6fZzBbhSCOLtQOAeat+aa8AWONz73qQJMkVHzvl7/nArxrzFUMi1LclCckyvLAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T07:50:59.684589Z"},"content_sha256":"2f2f57c87a6a9e5fc6091b201a5af20139349a2b35ba87c450288c2d5114b387","schema_version":"1.0","event_id":"sha256:2f2f57c87a6a9e5fc6091b201a5af20139349a2b35ba87c450288c2d5114b387"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:SXOCCZB2NJWVDK3PUTH4TRS2K4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PrefPaint: Aligning Image Inpainting Diffusion Model with Human Preference","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chuanhao Li, Huanqiang Zeng, Hui Liu, Junhui Hou, Kendong Liu, Zhiyu Zhu","submitted_at":"2024-10-29T11:49:39Z","abstract_excerpt":"In this paper, we make the first attempt to align diffusion models for image inpainting with human aesthetic standards via a reinforcement learning framework, significantly improving the quality and visual appeal of inpainted images. Specifically, instead of directly measuring the divergence with paired images, we train a reward model with the dataset we construct, consisting of nearly 51,000 images annotated with human preferences. Then, we adopt a reinforcement learning process to fine-tune the distribution of a pre-trained diffusion model for image inpainting in the direction of higher rewa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.21966","kind":"arxiv","version":2},"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/2410.21966/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":"2026-07-05T09:30:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NT6cXBBDI8HSrrofeEwu1qDzUE1C8y78xrc20sDmgEn/g3XQ/yLp3Ni1uwITnFuxOIRmJRJClzEiW5OkvWelCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T07:50:59.685096Z"},"content_sha256":"a595fb0c6590ab7aa05450b06f589a422abe2de9f87df19cf2c49cabb23cb606","schema_version":"1.0","event_id":"sha256:a595fb0c6590ab7aa05450b06f589a422abe2de9f87df19cf2c49cabb23cb606"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SXOCCZB2NJWVDK3PUTH4TRS2K4/bundle.json","state_url":"https://pith.science/pith/SXOCCZB2NJWVDK3PUTH4TRS2K4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SXOCCZB2NJWVDK3PUTH4TRS2K4/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":"2026-08-06T07:50:59Z","links":{"resolver":"https://pith.science/pith/SXOCCZB2NJWVDK3PUTH4TRS2K4","bundle":"https://pith.science/pith/SXOCCZB2NJWVDK3PUTH4TRS2K4/bundle.json","state":"https://pith.science/pith/SXOCCZB2NJWVDK3PUTH4TRS2K4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SXOCCZB2NJWVDK3PUTH4TRS2K4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:SXOCCZB2NJWVDK3PUTH4TRS2K4","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":"4e665e0152e07dc4a81b20f5b3cabdc5b47ab066f47d9eb71ec784d9445900ef","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-29T11:49:39Z","title_canon_sha256":"b15aebb195757b85a501357506c030cf53885bf2d15e072b12807d9ca6759616"},"schema_version":"1.0","source":{"id":"2410.21966","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.21966","created_at":"2026-07-05T09:30:23Z"},{"alias_kind":"arxiv_version","alias_value":"2410.21966v2","created_at":"2026-07-05T09:30:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.21966","created_at":"2026-07-05T09:30:23Z"},{"alias_kind":"pith_short_12","alias_value":"SXOCCZB2NJWV","created_at":"2026-07-05T09:30:23Z"},{"alias_kind":"pith_short_16","alias_value":"SXOCCZB2NJWVDK3P","created_at":"2026-07-05T09:30:23Z"},{"alias_kind":"pith_short_8","alias_value":"SXOCCZB2","created_at":"2026-07-05T09:30:23Z"}],"graph_snapshots":[{"event_id":"sha256:a595fb0c6590ab7aa05450b06f589a422abe2de9f87df19cf2c49cabb23cb606","target":"graph","created_at":"2026-07-05T09:30:23Z","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/2410.21966/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we make the first attempt to align diffusion models for image inpainting with human aesthetic standards via a reinforcement learning framework, significantly improving the quality and visual appeal of inpainted images. Specifically, instead of directly measuring the divergence with paired images, we train a reward model with the dataset we construct, consisting of nearly 51,000 images annotated with human preferences. Then, we adopt a reinforcement learning process to fine-tune the distribution of a pre-trained diffusion model for image inpainting in the direction of higher rewa","authors_text":"Chuanhao Li, Huanqiang Zeng, Hui Liu, Junhui Hou, Kendong Liu, Zhiyu Zhu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-29T11:49:39Z","title":"PrefPaint: Aligning Image Inpainting Diffusion Model with Human Preference"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.21966","kind":"arxiv","version":2},"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":"sha256:2f2f57c87a6a9e5fc6091b201a5af20139349a2b35ba87c450288c2d5114b387","target":"record","created_at":"2026-07-05T09:30:23Z","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":"4e665e0152e07dc4a81b20f5b3cabdc5b47ab066f47d9eb71ec784d9445900ef","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-29T11:49:39Z","title_canon_sha256":"b15aebb195757b85a501357506c030cf53885bf2d15e072b12807d9ca6759616"},"schema_version":"1.0","source":{"id":"2410.21966","kind":"arxiv","version":2}},"canonical_sha256":"95dc21643a6a6d51ab6fa4cfc9c65a572eec51201eaa181e4cd55d188369dc00","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"95dc21643a6a6d51ab6fa4cfc9c65a572eec51201eaa181e4cd55d188369dc00","first_computed_at":"2026-07-05T09:30:23.732753Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:30:23.732753Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dnOiBRb83uzHpWtRkXUgYcyza3cT6ZRHll7RX8gxYjPOfMsfMoF5FHcvKjmCzNw3eDb7k1zdpiVJXg93X6c2BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:30:23.733251Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.21966","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2f2f57c87a6a9e5fc6091b201a5af20139349a2b35ba87c450288c2d5114b387","sha256:a595fb0c6590ab7aa05450b06f589a422abe2de9f87df19cf2c49cabb23cb606"],"state_sha256":"638b7b36f167e3ca56ac96d4ff174575994e765d644464be1c4105cc87221ce3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GXmt2gxJAhCAiHwa1z7uADoghLqsJ32K4i2eeZgy1MLA+eOSTlqMv8hIzbzmdRmFuAo8QrrfnKM1kEGAOCMxBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T07:50:59.691432Z","bundle_sha256":"7f8b52d6ad1ee3369fabf70fb253bb1dce92048ee6739b5206267b87b4ab130d"}}