{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:BFMMEQPRXNLVHRUPLGTXCQGM5P","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":"f1d2881e13fd13b6e08d7b26a7d43f4678f08af2654fd5f91b53b3df216698d3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-08-02T14:56:13Z","title_canon_sha256":"8eaf339cc4d6a53af297a5cbba925b16451231d44548ec80d886f0b281e5dba6"},"schema_version":"1.0","source":{"id":"2608.01288","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.01288","created_at":"2026-08-04T02:03:06Z"},{"alias_kind":"arxiv_version","alias_value":"2608.01288v1","created_at":"2026-08-04T02:03:06Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.01288","created_at":"2026-08-04T02:03:06Z"},{"alias_kind":"pith_short_12","alias_value":"BFMMEQPRXNLV","created_at":"2026-08-04T02:03:06Z"},{"alias_kind":"pith_short_16","alias_value":"BFMMEQPRXNLVHRUP","created_at":"2026-08-04T02:03:06Z"},{"alias_kind":"pith_short_8","alias_value":"BFMMEQPR","created_at":"2026-08-04T02:03:06Z"}],"graph_snapshots":[{"event_id":"sha256:272a30b64190e035cc980b081b56502d56d84a4aa4222a8c8f7cb975ce461aee","target":"graph","created_at":"2026-08-04T02:03:06Z","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/2608.01288/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, diffusion-based removal methods have achieved promising visual quality in removing both target objects and their associated effects. However, they typically rely on multi-step denoising, leading to high inference cost. Directly applying existing one-step distillation methods is also suboptimal, since their global objectives lack explicit region-wise calibration and may weaken the asymmetric edit-and-preserve behavior required by object-effect removal. To address these challenges, we propose TurboClear, a one-step SDXL-based object-effect removal model. During training, we design Regi","authors_text":"Bingya Zhang, Jiawei Guo, Jiaxin Lu, Junxian Li, Shangchen Zhou, Yixin Tang, Yulun Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-08-02T14:56:13Z","title":"TurboClear: One-Step Object-Effect Removal via Region-Calibrated Distribution Matching and Fusion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.01288","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":"sha256:402b239686e7c5a8fc8b4162b8830a9a9f11885052b752a95faba2b41affeafa","target":"record","created_at":"2026-08-04T02:03:06Z","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":"f1d2881e13fd13b6e08d7b26a7d43f4678f08af2654fd5f91b53b3df216698d3","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-08-02T14:56:13Z","title_canon_sha256":"8eaf339cc4d6a53af297a5cbba925b16451231d44548ec80d886f0b281e5dba6"},"schema_version":"1.0","source":{"id":"2608.01288","kind":"arxiv","version":1}},"canonical_sha256":"0958c241f1bb5753c68f59a77140ccebf1f2d9ffc57e58207d1b074333f9cb0f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0958c241f1bb5753c68f59a77140ccebf1f2d9ffc57e58207d1b074333f9cb0f","first_computed_at":"2026-08-04T02:03:06.792502Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-04T02:03:06.792502Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LqIBaxIzHfpHpBtQ3E9kF4wf+Y+2lzViL6cmIuc8hRFJp1h1PDrsSCtO5q/tMW+Glp3RpF1TL7ji1JLybiZ9Dw==","signature_status":"signed_v1","signed_at":"2026-08-04T02:03:06.794002Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.01288","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:402b239686e7c5a8fc8b4162b8830a9a9f11885052b752a95faba2b41affeafa","sha256:272a30b64190e035cc980b081b56502d56d84a4aa4222a8c8f7cb975ce461aee"],"state_sha256":"769e5d2ad8c63bdd5167053044452526d5c0644db8e82a840b8bc61a1cab9f42"}