{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:XXXOD4H6DEFRJZEZKLCEGOTGYI","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":"95cccde6f8ad10001d46b2d0b939524c31c972adf8b2ee87f0c3fd4b15ac7e2b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-30T18:58:17Z","title_canon_sha256":"5479732f2e3a445d0f2110a6764e8fdbd5a1734f0fd9e51bdee81e737d169b80"},"schema_version":"1.0","source":{"id":"2311.18822","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.18822","created_at":"2026-07-05T10:28:04Z"},{"alias_kind":"arxiv_version","alias_value":"2311.18822v3","created_at":"2026-07-05T10:28:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.18822","created_at":"2026-07-05T10:28:04Z"},{"alias_kind":"pith_short_12","alias_value":"XXXOD4H6DEFR","created_at":"2026-07-05T10:28:04Z"},{"alias_kind":"pith_short_16","alias_value":"XXXOD4H6DEFRJZEZ","created_at":"2026-07-05T10:28:04Z"},{"alias_kind":"pith_short_8","alias_value":"XXXOD4H6","created_at":"2026-07-05T10:28:04Z"}],"graph_snapshots":[{"event_id":"sha256:5335eeedd4a2237e8386b17c4b2bc0df90765f9aaa25fd871fcf1f11b8d9ae59","target":"graph","created_at":"2026-07-05T10:28:04Z","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/2311.18822/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Diffusion models have revolutionized image generation in recent years, yet they are still limited to a few sizes and aspect ratios. We propose ElasticDiffusion, a novel training-free decoding method that enables pretrained text-to-image diffusion models to generate images with various sizes. ElasticDiffusion attempts to decouple the generation trajectory of a pretrained model into local and global signals. The local signal controls low-level pixel information and can be estimated on local patches, while the global signal is used to maintain overall structural consistency and is estimated with ","authors_text":"Guha Balakrishnan, Moayed Haji-Ali, Vicente Ordonez","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-30T18:58:17Z","title":"ElasticDiffusion: Training-free Arbitrary Size Image Generation through Global-Local Content Separation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.18822","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":"sha256:5f16e8977c9de63f13e8e92c2c5e797575a8525bf1894f2a3b2ff4139eb8f462","target":"record","created_at":"2026-07-05T10:28:04Z","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":"95cccde6f8ad10001d46b2d0b939524c31c972adf8b2ee87f0c3fd4b15ac7e2b","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-30T18:58:17Z","title_canon_sha256":"5479732f2e3a445d0f2110a6764e8fdbd5a1734f0fd9e51bdee81e737d169b80"},"schema_version":"1.0","source":{"id":"2311.18822","kind":"arxiv","version":3}},"canonical_sha256":"bdeee1f0fe190b14e49952c4433a66c205a22825304ffca9d8107433c1e5fa0c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bdeee1f0fe190b14e49952c4433a66c205a22825304ffca9d8107433c1e5fa0c","first_computed_at":"2026-07-05T10:28:04.361452Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:28:04.361452Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"D5TlhhECh2C9iEDsZmu0W6tPtySL1c0OeEmsyI/ikohhtrRNQizXFGGJ7iJ9wh6ElnxUXYNXXz6earqi+DVaBg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:28:04.362027Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.18822","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5f16e8977c9de63f13e8e92c2c5e797575a8525bf1894f2a3b2ff4139eb8f462","sha256:5335eeedd4a2237e8386b17c4b2bc0df90765f9aaa25fd871fcf1f11b8d9ae59"],"state_sha256":"f7e395f9d834c67435a1c5ade4af01f4815efd4f46f84bd2f5a977cbb1dde648"}