{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:5H24XJAPXJ32FRGU343TVLBNFQ","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":"a38bb47d3bb3b15ed17d2874c5d1bcf57acd81b6cb07e7cf84a16978da6ce777","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-20T16:53:34Z","title_canon_sha256":"5bc645ca01f676f5bf534638f14911752656d440616f5ef2e0d88c4a08ffbc27"},"schema_version":"1.0","source":{"id":"2408.11001","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2408.11001","created_at":"2026-07-05T09:36:47Z"},{"alias_kind":"arxiv_version","alias_value":"2408.11001v3","created_at":"2026-07-05T09:36:47Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2408.11001","created_at":"2026-07-05T09:36:47Z"},{"alias_kind":"pith_short_12","alias_value":"5H24XJAPXJ32","created_at":"2026-07-05T09:36:47Z"},{"alias_kind":"pith_short_16","alias_value":"5H24XJAPXJ32FRGU","created_at":"2026-07-05T09:36:47Z"},{"alias_kind":"pith_short_8","alias_value":"5H24XJAP","created_at":"2026-07-05T09:36:47Z"}],"graph_snapshots":[{"event_id":"sha256:aadfebeab4d124af4623acff25ffe4f4eed31734e58f4d58a3df76ed6d9a1bf8","target":"graph","created_at":"2026-07-05T09:36:47Z","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/2408.11001/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion models have emerged as frontrunners in text-to-image generation, but their fixed image resolution during training often leads to challenges in high-resolution image generation, such as semantic deviations and object replication. This paper introduces MegaFusion, a novel approach that extends existing diffusion-based text-to-image models towards efficient higher-resolution generation without additional fine-tuning or adaptation. Specifically, we employ an innovative truncate and relay strategy to bridge the denoising processes across different resolutions, allowing for high-resolution","authors_text":"Haoning Wu, Qiang Hu, Shaocheng Shen, Xiaoyun Zhang, Yanfeng Wang, Ya Zhang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-20T16:53:34Z","title":"MegaFusion: Extend Diffusion Models towards Higher-resolution Image Generation without Further Tuning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2408.11001","kind":"arxiv","version":3},"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:af7d3ced5276122aeb6f98bb35436de4b014236dec046ed619b474dec099f424","target":"record","created_at":"2026-07-05T09:36:47Z","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":"a38bb47d3bb3b15ed17d2874c5d1bcf57acd81b6cb07e7cf84a16978da6ce777","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-08-20T16:53:34Z","title_canon_sha256":"5bc645ca01f676f5bf534638f14911752656d440616f5ef2e0d88c4a08ffbc27"},"schema_version":"1.0","source":{"id":"2408.11001","kind":"arxiv","version":3}},"canonical_sha256":"e9f5cba40fba77a2c4d4df373aac2d2c1192196a80402537d3e8f80a76a576ec","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e9f5cba40fba77a2c4d4df373aac2d2c1192196a80402537d3e8f80a76a576ec","first_computed_at":"2026-07-05T09:36:47.695490Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:36:47.695490Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/X/gW8wuFvaC3ZkmCb+J3rcn6lh2xeNx5BrZqeFTYpfKCIkcESV5k0L6vKOfzXlA/L/lubThhDoDyQhCdHD5Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:36:47.695969Z","signed_message":"canonical_sha256_bytes"},"source_id":"2408.11001","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:af7d3ced5276122aeb6f98bb35436de4b014236dec046ed619b474dec099f424","sha256:aadfebeab4d124af4623acff25ffe4f4eed31734e58f4d58a3df76ed6d9a1bf8"],"state_sha256":"c9df2b5e84e2d23fd1c2e2da3db24eea6b776cf05ecb851edca1997655b7bbe3"}