{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:PNYZIUJKQ4AVNKQUXRW4BZC375","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":"c92bd735d7c7da6f3217cb7f541a20e94e59c85f17b7cef11307b2ac760edb59","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-30T04:28:55Z","title_canon_sha256":"d7a9d005bc2c01071bab8837e6eea17586eeca4c434638917d94ee21c93e7007"},"schema_version":"1.0","source":{"id":"2409.19937","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.19937","created_at":"2026-07-05T09:13:25Z"},{"alias_kind":"arxiv_version","alias_value":"2409.19937v1","created_at":"2026-07-05T09:13:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.19937","created_at":"2026-07-05T09:13:25Z"},{"alias_kind":"pith_short_12","alias_value":"PNYZIUJKQ4AV","created_at":"2026-07-05T09:13:25Z"},{"alias_kind":"pith_short_16","alias_value":"PNYZIUJKQ4AVNKQU","created_at":"2026-07-05T09:13:25Z"},{"alias_kind":"pith_short_8","alias_value":"PNYZIUJK","created_at":"2026-07-05T09:13:25Z"}],"graph_snapshots":[{"event_id":"sha256:c34af69dd3ed7047a635c2054ff25c91afc7017971b571e7a2bfc0c98a68b8ab","target":"graph","created_at":"2026-07-05T09:13:25Z","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/2409.19937/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Image generation models have encountered challenges related to scalability and quadratic complexity, primarily due to the reliance on Transformer-based backbones. In this study, we introduce MaskMamba, a novel hybrid model that combines Mamba and Transformer architectures, utilizing Masked Image Modeling for non-autoregressive image synthesis. We meticulously redesign the bidirectional Mamba architecture by implementing two key modifications: (1) replacing causal convolutions with standard convolutions to better capture global context, and (2) utilizing concatenation instead of multiplication,","authors_text":"Fandong Meng, Jie Zhou, Liqiang Niu, Wenchao Chen, Ziyao Lu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-30T04:28:55Z","title":"MaskMamba: A Hybrid Mamba-Transformer Model for Masked Image Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.19937","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":"sha256:731557c97596b8f89cdc90d8cc5f9fcab23f64423113d296304f216290ec3b06","target":"record","created_at":"2026-07-05T09:13:25Z","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":"c92bd735d7c7da6f3217cb7f541a20e94e59c85f17b7cef11307b2ac760edb59","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-30T04:28:55Z","title_canon_sha256":"d7a9d005bc2c01071bab8837e6eea17586eeca4c434638917d94ee21c93e7007"},"schema_version":"1.0","source":{"id":"2409.19937","kind":"arxiv","version":1}},"canonical_sha256":"7b7194512a870156aa14bc6dc0e45bff64848945140e7fd9d7477b5e8df263ac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7b7194512a870156aa14bc6dc0e45bff64848945140e7fd9d7477b5e8df263ac","first_computed_at":"2026-07-05T09:13:25.075919Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:13:25.075919Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/aMR4SBLwE5ZQ2rVfbZ1/AAi158O724B/hlM56Dr9j4F4/JE+UK0gyEzEs4FaMCYF5GgpvvtqQHgzNABjCboBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:13:25.076387Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.19937","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:731557c97596b8f89cdc90d8cc5f9fcab23f64423113d296304f216290ec3b06","sha256:c34af69dd3ed7047a635c2054ff25c91afc7017971b571e7a2bfc0c98a68b8ab"],"state_sha256":"a86d06385002113955f1f79630e401544f36af600a3c2d7e635a3a9e2dd885a4"}