{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:QQEL5GKZ77NUB57C7YT4IMOP5A","short_pith_number":"pith:QQEL5GKZ","schema_version":"1.0","canonical_sha256":"8408be9959ffdb40f7e2fe27c431cfe814ada3d1201e971003beb4277fcf807c","source":{"kind":"arxiv","id":"2608.13043","version":1},"attestation_state":"computed","paper":{"title":"From Local Mismatch to Global Impact: Optimizing Cache Reuse Policy for Efficient Diffusion","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"cs.AI","authors_text":"Cheng Jin, Weizhong Zhang, Xiangyu Yue, Xichen Ye, Yifan Wu, Zhikang Xie","submitted_at":"2026-08-13T10:08:47Z","abstract_excerpt":"Diffusion models have achieved dominant performance in visual generation but suffer from substantial inference overhead. While cache-based acceleration has emerged as a promising solution, existing policies rely on local similarity heuristics, which we identify as being significantly misaligned with final generation quality. This discrepancy stems from the non-uniform propagation and accumulation of errors along the denoising trajectory. To address this, we propose Global-Impact Cache (GCache). We first establish a rigorous theoretical characterization of the error propagation upper bound. Rec"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2608.13043","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2026-08-13T10:08:47Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"220ec3d819f7b4000dd01b46ab889946e3e6aae7481e43f2a9dc3c8bf54427db","abstract_canon_sha256":"657a7b40068dbe7f992b507c562553c87c2cf0b498264bf417bb06d468b40c50"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-08-14T01:00:12.193364Z","signature_b64":"e5oaVXn+gOcaHMG+5X3wIrw07yc8DYTbKFgN6Kt7gFnvAVozx0jS3ELyy7wgeV5OD60fcFTgOcQA8zpdQNwaAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8408be9959ffdb40f7e2fe27c431cfe814ada3d1201e971003beb4277fcf807c","last_reissued_at":"2026-08-14T01:00:12.191238Z","signature_status":"signed_v1","first_computed_at":"2026-08-14T01:00:12.191238Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"From Local Mismatch to Global Impact: Optimizing Cache Reuse Policy for Efficient Diffusion","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"cs.AI","authors_text":"Cheng Jin, Weizhong Zhang, Xiangyu Yue, Xichen Ye, Yifan Wu, Zhikang Xie","submitted_at":"2026-08-13T10:08:47Z","abstract_excerpt":"Diffusion models have achieved dominant performance in visual generation but suffer from substantial inference overhead. While cache-based acceleration has emerged as a promising solution, existing policies rely on local similarity heuristics, which we identify as being significantly misaligned with final generation quality. This discrepancy stems from the non-uniform propagation and accumulation of errors along the denoising trajectory. To address this, we propose Global-Impact Cache (GCache). We first establish a rigorous theoretical characterization of the error propagation upper bound. Rec"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.13043","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/2608.13043/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2608.13043","created_at":"2026-08-14T01:00:12.192322+00:00"},{"alias_kind":"arxiv_version","alias_value":"2608.13043v1","created_at":"2026-08-14T01:00:12.192322+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.13043","created_at":"2026-08-14T01:00:12.192322+00:00"},{"alias_kind":"pith_short_12","alias_value":"QQEL5GKZ77NU","created_at":"2026-08-14T01:00:12.192322+00:00"},{"alias_kind":"pith_short_16","alias_value":"QQEL5GKZ77NUB57C","created_at":"2026-08-14T01:00:12.192322+00:00"},{"alias_kind":"pith_short_8","alias_value":"QQEL5GKZ","created_at":"2026-08-14T01:00:12.192322+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QQEL5GKZ77NUB57C7YT4IMOP5A","json":"https://pith.science/pith/QQEL5GKZ77NUB57C7YT4IMOP5A.json","graph_json":"https://pith.science/api/pith-number/QQEL5GKZ77NUB57C7YT4IMOP5A/graph.json","events_json":"https://pith.science/api/pith-number/QQEL5GKZ77NUB57C7YT4IMOP5A/events.json","paper":"https://pith.science/paper/QQEL5GKZ"},"agent_actions":{"view_html":"https://pith.science/pith/QQEL5GKZ77NUB57C7YT4IMOP5A","download_json":"https://pith.science/pith/QQEL5GKZ77NUB57C7YT4IMOP5A.json","view_paper":"https://pith.science/paper/QQEL5GKZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2608.13043&json=true","fetch_graph":"https://pith.science/api/pith-number/QQEL5GKZ77NUB57C7YT4IMOP5A/graph.json","fetch_events":"https://pith.science/api/pith-number/QQEL5GKZ77NUB57C7YT4IMOP5A/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QQEL5GKZ77NUB57C7YT4IMOP5A/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QQEL5GKZ77NUB57C7YT4IMOP5A/action/storage_attestation","attest_author":"https://pith.science/pith/QQEL5GKZ77NUB57C7YT4IMOP5A/action/author_attestation","sign_citation":"https://pith.science/pith/QQEL5GKZ77NUB57C7YT4IMOP5A/action/citation_signature","submit_replication":"https://pith.science/pith/QQEL5GKZ77NUB57C7YT4IMOP5A/action/replication_record"}},"created_at":"2026-08-14T01:00:12.192322+00:00","updated_at":"2026-08-14T01:00:12.192322+00:00"}