{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:WDGLKT35WXWQ7XCHYRUXI42RSG","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":"3255beba83dc91f716460366f6e6ac8c06c9fb63a11bcba349c90237f646fee9","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2026-07-10T18:32:27Z","title_canon_sha256":"fde28414f8176576aeca0cde63e96df3672a23555d4a26ff3224b288a9ad649e"},"schema_version":"1.0","source":{"id":"2607.09892","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.09892","created_at":"2026-07-14T00:18:41Z"},{"alias_kind":"arxiv_version","alias_value":"2607.09892v1","created_at":"2026-07-14T00:18:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.09892","created_at":"2026-07-14T00:18:41Z"},{"alias_kind":"pith_short_12","alias_value":"WDGLKT35WXWQ","created_at":"2026-07-14T00:18:41Z"},{"alias_kind":"pith_short_16","alias_value":"WDGLKT35WXWQ7XCH","created_at":"2026-07-14T00:18:41Z"},{"alias_kind":"pith_short_8","alias_value":"WDGLKT35","created_at":"2026-07-14T00:18:41Z"}],"graph_snapshots":[{"event_id":"sha256:d8e991839f79421d373931e2d81a6bef534fe473eb248ca84482241bafb6f355","target":"graph","created_at":"2026-07-14T00:18:41Z","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/2607.09892/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We introduce DenseAR, a new generative paradigm that reformulates autoregressive image generation as coarse-to-fine next-dense-stride prediction using a compact single-scale tokenizer. Our key insight is that traversing a single-scale latent grid with progressively denser strides naturally captures the transition from global structure to fine detail. This addresses two limitations of existing autoregressive models at once: the slow inference of raster-order autoregression, which DenseAR avoids by predicting multiple tokens in parallel, and the heavy cost of multi-scale approaches, which need l","authors_text":"Cao Xiao, Chicago Y. Park, Jialin Mao, Taha Kass-hout, Ulugbek S. Kamilov, Xiaojian Xu","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2026-07-10T18:32:27Z","title":"Next-Dense-Stride Prediction for Multimodal Autoregressive Visual Modeling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.09892","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":"sha256:61b3c62a1285b16ca111467d855cb34d2eccbb2eed28aa5f25b17f362b8a5225","target":"record","created_at":"2026-07-14T00:18:41Z","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":"3255beba83dc91f716460366f6e6ac8c06c9fb63a11bcba349c90237f646fee9","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2026-07-10T18:32:27Z","title_canon_sha256":"fde28414f8176576aeca0cde63e96df3672a23555d4a26ff3224b288a9ad649e"},"schema_version":"1.0","source":{"id":"2607.09892","kind":"arxiv","version":1}},"canonical_sha256":"b0ccb54f7db5ed0fdc47c4697473519196862696286d6168eabd85809ed17f70","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b0ccb54f7db5ed0fdc47c4697473519196862696286d6168eabd85809ed17f70","first_computed_at":"2026-07-14T00:18:41.829125Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-14T00:18:41.829125Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rzbuuVA5Yc6ww86jaGmjdiWolKzHe2c6k8uO53b57PfDTQJXvW+Cp8Ob17sYUGo2V9eIpECJ5qcm5RXsLisaCg==","signature_status":"signed_v1","signed_at":"2026-07-14T00:18:41.829952Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.09892","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:61b3c62a1285b16ca111467d855cb34d2eccbb2eed28aa5f25b17f362b8a5225","sha256:d8e991839f79421d373931e2d81a6bef534fe473eb248ca84482241bafb6f355"],"state_sha256":"f9d27a89885edcd8d57ad6811abedfb592d4ad24a67e7880b1e5539291038dba"}