{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:5A5SKOQABL3NTBOJ6T4AX2RS6S","short_pith_number":"pith:5A5SKOQA","canonical_record":{"source":{"id":"2507.21627","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-29T09:36:52Z","cross_cats_sorted":[],"title_canon_sha256":"84ed4e8f9db6251862a66466038de5e22eec9cd0cc82e35ed20b517bf0f37ca1","abstract_canon_sha256":"785ebd6f1d0e1962ffd89c29f403dbb5baea6ed748373d088ce9c4082e991e33"},"schema_version":"1.0"},"canonical_sha256":"e83b253a000af6d985c9f4f80bea32f4a315e77b941407ff7ef5bcf3d864fd93","source":{"kind":"arxiv","id":"2507.21627","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.21627","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"arxiv_version","alias_value":"2507.21627v1","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.21627","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"pith_short_12","alias_value":"5A5SKOQABL3N","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"pith_short_16","alias_value":"5A5SKOQABL3NTBOJ","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"pith_short_8","alias_value":"5A5SKOQA","created_at":"2026-07-05T11:45:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:5A5SKOQABL3NTBOJ6T4AX2RS6S","target":"record","payload":{"canonical_record":{"source":{"id":"2507.21627","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-29T09:36:52Z","cross_cats_sorted":[],"title_canon_sha256":"84ed4e8f9db6251862a66466038de5e22eec9cd0cc82e35ed20b517bf0f37ca1","abstract_canon_sha256":"785ebd6f1d0e1962ffd89c29f403dbb5baea6ed748373d088ce9c4082e991e33"},"schema_version":"1.0"},"canonical_sha256":"e83b253a000af6d985c9f4f80bea32f4a315e77b941407ff7ef5bcf3d864fd93","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:45:03.432805Z","signature_b64":"XfN/2tgF1aOvyNm55gMmwrkA2k1ubbOPWVby69WAEQKK/3n9/w0EqvrxMvBaoXeanfoArcIDh24CeB7VpA1vDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e83b253a000af6d985c9f4f80bea32f4a315e77b941407ff7ef5bcf3d864fd93","last_reissued_at":"2026-07-05T11:45:03.432176Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:45:03.432176Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.21627","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":"2026-07-05T11:45:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TgpS92L/bZTE/MMKxIhXbnb6RNF1qDoLBezau9EMGaHdI6X0bePhIpW6/7W65XiE3Q7dDswzD8E0c4lHgPTyDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T05:17:10.209099Z"},"content_sha256":"155da4855c3bd5beb0c56edddadc7bdec692552eb9c93747185dde6b878e66e1","schema_version":"1.0","event_id":"sha256:155da4855c3bd5beb0c56edddadc7bdec692552eb9c93747185dde6b878e66e1"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:5A5SKOQABL3NTBOJ6T4AX2RS6S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GuidPaint: Class-Guided Image Inpainting with Diffusion Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Guohua Geng, Qimin Wang, Xinda Liu","submitted_at":"2025-07-29T09:36:52Z","abstract_excerpt":"In recent years, diffusion models have been widely adopted for image inpainting tasks due to their powerful generative capabilities, achieving impressive results. Existing multimodal inpainting methods based on diffusion models often require architectural modifications and retraining, resulting in high computational cost. In contrast, context-aware diffusion inpainting methods leverage the model's inherent priors to adjust intermediate denoising steps, enabling high-quality inpainting without additional training and significantly reducing computation. However, these methods lack fine-grained c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.21627","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/2507.21627/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":"2026-07-05T11:45:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OM+WQONtCqPwSfETBMS8Usnw75vmySUFizq8RASC8ppzQtbehgPc5LMStdv2f7tRYBjokFECybVliXmzO85MAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T05:17:10.209601Z"},"content_sha256":"b319dc25388dd73bf464f0c22a3e0be228d47669bb86b7629e48d2e16d06595b","schema_version":"1.0","event_id":"sha256:b319dc25388dd73bf464f0c22a3e0be228d47669bb86b7629e48d2e16d06595b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5A5SKOQABL3NTBOJ6T4AX2RS6S/bundle.json","state_url":"https://pith.science/pith/5A5SKOQABL3NTBOJ6T4AX2RS6S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5A5SKOQABL3NTBOJ6T4AX2RS6S/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":"2026-08-09T05:17:10Z","links":{"resolver":"https://pith.science/pith/5A5SKOQABL3NTBOJ6T4AX2RS6S","bundle":"https://pith.science/pith/5A5SKOQABL3NTBOJ6T4AX2RS6S/bundle.json","state":"https://pith.science/pith/5A5SKOQABL3NTBOJ6T4AX2RS6S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5A5SKOQABL3NTBOJ6T4AX2RS6S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:5A5SKOQABL3NTBOJ6T4AX2RS6S","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":"785ebd6f1d0e1962ffd89c29f403dbb5baea6ed748373d088ce9c4082e991e33","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-29T09:36:52Z","title_canon_sha256":"84ed4e8f9db6251862a66466038de5e22eec9cd0cc82e35ed20b517bf0f37ca1"},"schema_version":"1.0","source":{"id":"2507.21627","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.21627","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"arxiv_version","alias_value":"2507.21627v1","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.21627","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"pith_short_12","alias_value":"5A5SKOQABL3N","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"pith_short_16","alias_value":"5A5SKOQABL3NTBOJ","created_at":"2026-07-05T11:45:03Z"},{"alias_kind":"pith_short_8","alias_value":"5A5SKOQA","created_at":"2026-07-05T11:45:03Z"}],"graph_snapshots":[{"event_id":"sha256:b319dc25388dd73bf464f0c22a3e0be228d47669bb86b7629e48d2e16d06595b","target":"graph","created_at":"2026-07-05T11:45:03Z","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/2507.21627/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, diffusion models have been widely adopted for image inpainting tasks due to their powerful generative capabilities, achieving impressive results. Existing multimodal inpainting methods based on diffusion models often require architectural modifications and retraining, resulting in high computational cost. In contrast, context-aware diffusion inpainting methods leverage the model's inherent priors to adjust intermediate denoising steps, enabling high-quality inpainting without additional training and significantly reducing computation. However, these methods lack fine-grained c","authors_text":"Guohua Geng, Qimin Wang, Xinda Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-29T09:36:52Z","title":"GuidPaint: Class-Guided Image Inpainting with Diffusion Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.21627","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":"sha256:155da4855c3bd5beb0c56edddadc7bdec692552eb9c93747185dde6b878e66e1","target":"record","created_at":"2026-07-05T11:45:03Z","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":"785ebd6f1d0e1962ffd89c29f403dbb5baea6ed748373d088ce9c4082e991e33","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-07-29T09:36:52Z","title_canon_sha256":"84ed4e8f9db6251862a66466038de5e22eec9cd0cc82e35ed20b517bf0f37ca1"},"schema_version":"1.0","source":{"id":"2507.21627","kind":"arxiv","version":1}},"canonical_sha256":"e83b253a000af6d985c9f4f80bea32f4a315e77b941407ff7ef5bcf3d864fd93","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e83b253a000af6d985c9f4f80bea32f4a315e77b941407ff7ef5bcf3d864fd93","first_computed_at":"2026-07-05T11:45:03.432176Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:45:03.432176Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XfN/2tgF1aOvyNm55gMmwrkA2k1ubbOPWVby69WAEQKK/3n9/w0EqvrxMvBaoXeanfoArcIDh24CeB7VpA1vDw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:45:03.432805Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.21627","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:155da4855c3bd5beb0c56edddadc7bdec692552eb9c93747185dde6b878e66e1","sha256:b319dc25388dd73bf464f0c22a3e0be228d47669bb86b7629e48d2e16d06595b"],"state_sha256":"525ddca6c3733f7253e2ed6ada292cbaf4499d3a89dad0c76445473ef546f61a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"52zvxJ/7jJiU8F5PBjtIctBxBagQQtsiHVvY5Kb/gTygK0BC3Y71R6tNc7VwIbfxE4u6eZvd1B/J5NcG7B3CCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T05:17:10.212957Z","bundle_sha256":"f77e4dd15e1d65d389524257183896445fbdbe1b3e4eed6fa1fae440e60cba1e"}}