{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:VY5A7LIYUIVIO5TPR4THUKIE4S","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":"0309ad1a8fc30a709bb59e4e00c142d87574f06ed9d59eb4578b6cbe9dfff822","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-05T10:57:08Z","title_canon_sha256":"3c58737ec084ff67e86bd7ab4db5334f666256e5da4c6e73df8be395bd7bc621"},"schema_version":"1.0","source":{"id":"2412.04062","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.04062","created_at":"2026-07-05T11:29:04Z"},{"alias_kind":"arxiv_version","alias_value":"2412.04062v3","created_at":"2026-07-05T11:29:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.04062","created_at":"2026-07-05T11:29:04Z"},{"alias_kind":"pith_short_12","alias_value":"VY5A7LIYUIVI","created_at":"2026-07-05T11:29:04Z"},{"alias_kind":"pith_short_16","alias_value":"VY5A7LIYUIVIO5TP","created_at":"2026-07-05T11:29:04Z"},{"alias_kind":"pith_short_8","alias_value":"VY5A7LIY","created_at":"2026-07-05T11:29:04Z"}],"graph_snapshots":[{"event_id":"sha256:7710023bb7f3955223c81de0d7e59300910033ddeaee1f133f2bf1683a359756","target":"graph","created_at":"2026-07-05T11:29:04Z","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/2412.04062/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this paper, we propose ZipAR, a training-free, plug-and-play parallel decoding framework for accelerating auto-regressive (AR) visual generation. The motivation stems from the observation that images exhibit local structures, and spatially distant regions tend to have minimal interdependence. Given a partially decoded set of visual tokens, in addition to the original next-token prediction scheme in the row dimension, the tokens corresponding to spatially adjacent regions in the column dimension can be decoded in parallel, enabling the ``next-set prediction'' paradigm. By decoding multiple t","authors_text":"Bohan Zhuang, Feng Chen, Hong Zhou, Kaipeng Zhang, Shaoxuan He, Yefei He, Yuanyu He","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-05T10:57:08Z","title":"ZipAR: Parallel Auto-regressive Image Generation through Spatial Locality"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.04062","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":"sha256:7c543adf8b001e072374705a484068d108f9cc42bb4d42011a58fcd289089a5b","target":"record","created_at":"2026-07-05T11:29:04Z","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":"0309ad1a8fc30a709bb59e4e00c142d87574f06ed9d59eb4578b6cbe9dfff822","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-12-05T10:57:08Z","title_canon_sha256":"3c58737ec084ff67e86bd7ab4db5334f666256e5da4c6e73df8be395bd7bc621"},"schema_version":"1.0","source":{"id":"2412.04062","kind":"arxiv","version":3}},"canonical_sha256":"ae3a0fad18a22a87766f8f267a2904e4a71a3b9d3b046b749c23e84bcdd8094e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ae3a0fad18a22a87766f8f267a2904e4a71a3b9d3b046b749c23e84bcdd8094e","first_computed_at":"2026-07-05T11:29:04.382526Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:29:04.382526Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"CDlr9mx1GQwUBGzG77aEUaPSvUECh022Dhv6yFJHiSSbYVGXQD8jucHcaCJ6TNaqBcK0adqlHi7MVgejTPLnBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:29:04.383067Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.04062","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7c543adf8b001e072374705a484068d108f9cc42bb4d42011a58fcd289089a5b","sha256:7710023bb7f3955223c81de0d7e59300910033ddeaee1f133f2bf1683a359756"],"state_sha256":"daaabed4e77657d1b3783c6a30f5e7619aad0332ff60a9838665aaf2afe1caeb"}