{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:7TDFPHWUAJRS3ZLDTZ2NM37HRN","short_pith_number":"pith:7TDFPHWU","canonical_record":{"source":{"id":"2606.09156","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-08T07:47:53Z","cross_cats_sorted":[],"title_canon_sha256":"f564165a8ade219461a8c4aaa4c5a7443d1e81afdf0ae67d63dc944c87c6e9da","abstract_canon_sha256":"c4a88271d75649c22fd68146ad55ad8079bb37996bb592470cd207c079c16a63"},"schema_version":"1.0"},"canonical_sha256":"fcc6579ed402632de5639e74d66fe78b474877b509e18a17864eef9b0b4c11f5","source":{"kind":"arxiv","id":"2606.09156","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.09156","created_at":"2026-06-09T02:08:03Z"},{"alias_kind":"arxiv_version","alias_value":"2606.09156v1","created_at":"2026-06-09T02:08:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.09156","created_at":"2026-06-09T02:08:03Z"},{"alias_kind":"pith_short_12","alias_value":"7TDFPHWUAJRS","created_at":"2026-06-09T02:08:03Z"},{"alias_kind":"pith_short_16","alias_value":"7TDFPHWUAJRS3ZLD","created_at":"2026-06-09T02:08:03Z"},{"alias_kind":"pith_short_8","alias_value":"7TDFPHWU","created_at":"2026-06-09T02:08:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:7TDFPHWUAJRS3ZLDTZ2NM37HRN","target":"record","payload":{"canonical_record":{"source":{"id":"2606.09156","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-08T07:47:53Z","cross_cats_sorted":[],"title_canon_sha256":"f564165a8ade219461a8c4aaa4c5a7443d1e81afdf0ae67d63dc944c87c6e9da","abstract_canon_sha256":"c4a88271d75649c22fd68146ad55ad8079bb37996bb592470cd207c079c16a63"},"schema_version":"1.0"},"canonical_sha256":"fcc6579ed402632de5639e74d66fe78b474877b509e18a17864eef9b0b4c11f5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-09T02:08:03.555184Z","signature_b64":"+oL4yU2MwPrf72vg2oBfdtq7whBUPGx9sB3lfEdRxRpspZmodnqiEm1ERbAgL4S+8L1qWtlD+3eBmlbPEar9Cw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fcc6579ed402632de5639e74d66fe78b474877b509e18a17864eef9b0b4c11f5","last_reissued_at":"2026-06-09T02:08:03.554356Z","signature_status":"signed_v1","first_computed_at":"2026-06-09T02:08:03.554356Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.09156","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-09T02:08:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vrAIHdmSskdmD2cI0IobAmYEI109LKQMn4tIWkNdZDBqlXi/elpe/LexGm0SaMckzHBVH4du4nlxfvjymBdqDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T17:02:42.275918Z"},"content_sha256":"f40662437b905f8bdf8858ec24147109154d1189df2afe227f7d2af55f97a69e","schema_version":"1.0","event_id":"sha256:f40662437b905f8bdf8858ec24147109154d1189df2afe227f7d2af55f97a69e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:7TDFPHWUAJRS3ZLDTZ2NM37HRN","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"OmniGen-AR: AutoRegressive Any-to-Image Generation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Junke Wang, Peize Sun, Qiushan Guo, Weilin Huang, Xun Wang, Yu-Gang Jiang, Zuxuan Wu","submitted_at":"2026-06-08T07:47:53Z","abstract_excerpt":"Autoregressive (AR) models have demonstrated strong potential in visual generation, offering superior performance with simple architectures and optimization objectives. However, existing methods are typically limited to single-modality conditions, e.g., text, restricting their applicability in real-world scenarios that demand image synthesis from diverse controls. In this work, we present OmniGen-AR, a unified autoregressive framework for Any-to-Image generation. By discretizing various visual conditions through a shared visual tokenizer and text prompts with a text tokenizer, OmniGen-AR suppo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.09156","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2606.09156/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-06-09T02:08:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"As4UPp1a7SZdLvkxLSV9o2xxmuhPGtMVEmgmh2pgQjsp0Ca5VKtxkr7jOt/hymbn81yBXdgMdiY0mVimx7qgDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-30T17:02:42.276434Z"},"content_sha256":"9cb111d7aae4e7db46e758248cc72262283982767be1faaf1718d363e2d3ee89","schema_version":"1.0","event_id":"sha256:9cb111d7aae4e7db46e758248cc72262283982767be1faaf1718d363e2d3ee89"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7TDFPHWUAJRS3ZLDTZ2NM37HRN/bundle.json","state_url":"https://pith.science/pith/7TDFPHWUAJRS3ZLDTZ2NM37HRN/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7TDFPHWUAJRS3ZLDTZ2NM37HRN/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-30T17:02:42Z","links":{"resolver":"https://pith.science/pith/7TDFPHWUAJRS3ZLDTZ2NM37HRN","bundle":"https://pith.science/pith/7TDFPHWUAJRS3ZLDTZ2NM37HRN/bundle.json","state":"https://pith.science/pith/7TDFPHWUAJRS3ZLDTZ2NM37HRN/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7TDFPHWUAJRS3ZLDTZ2NM37HRN/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:7TDFPHWUAJRS3ZLDTZ2NM37HRN","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":"c4a88271d75649c22fd68146ad55ad8079bb37996bb592470cd207c079c16a63","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-08T07:47:53Z","title_canon_sha256":"f564165a8ade219461a8c4aaa4c5a7443d1e81afdf0ae67d63dc944c87c6e9da"},"schema_version":"1.0","source":{"id":"2606.09156","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.09156","created_at":"2026-06-09T02:08:03Z"},{"alias_kind":"arxiv_version","alias_value":"2606.09156v1","created_at":"2026-06-09T02:08:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.09156","created_at":"2026-06-09T02:08:03Z"},{"alias_kind":"pith_short_12","alias_value":"7TDFPHWUAJRS","created_at":"2026-06-09T02:08:03Z"},{"alias_kind":"pith_short_16","alias_value":"7TDFPHWUAJRS3ZLD","created_at":"2026-06-09T02:08:03Z"},{"alias_kind":"pith_short_8","alias_value":"7TDFPHWU","created_at":"2026-06-09T02:08:03Z"}],"graph_snapshots":[{"event_id":"sha256:9cb111d7aae4e7db46e758248cc72262283982767be1faaf1718d363e2d3ee89","target":"graph","created_at":"2026-06-09T02:08:03Z","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/2606.09156/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Autoregressive (AR) models have demonstrated strong potential in visual generation, offering superior performance with simple architectures and optimization objectives. However, existing methods are typically limited to single-modality conditions, e.g., text, restricting their applicability in real-world scenarios that demand image synthesis from diverse controls. In this work, we present OmniGen-AR, a unified autoregressive framework for Any-to-Image generation. By discretizing various visual conditions through a shared visual tokenizer and text prompts with a text tokenizer, OmniGen-AR suppo","authors_text":"Junke Wang, Peize Sun, Qiushan Guo, Weilin Huang, Xun Wang, Yu-Gang Jiang, Zuxuan Wu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-08T07:47:53Z","title":"OmniGen-AR: AutoRegressive Any-to-Image Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.09156","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:f40662437b905f8bdf8858ec24147109154d1189df2afe227f7d2af55f97a69e","target":"record","created_at":"2026-06-09T02:08:03Z","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":"c4a88271d75649c22fd68146ad55ad8079bb37996bb592470cd207c079c16a63","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2026-06-08T07:47:53Z","title_canon_sha256":"f564165a8ade219461a8c4aaa4c5a7443d1e81afdf0ae67d63dc944c87c6e9da"},"schema_version":"1.0","source":{"id":"2606.09156","kind":"arxiv","version":1}},"canonical_sha256":"fcc6579ed402632de5639e74d66fe78b474877b509e18a17864eef9b0b4c11f5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fcc6579ed402632de5639e74d66fe78b474877b509e18a17864eef9b0b4c11f5","first_computed_at":"2026-06-09T02:08:03.554356Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-09T02:08:03.554356Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+oL4yU2MwPrf72vg2oBfdtq7whBUPGx9sB3lfEdRxRpspZmodnqiEm1ERbAgL4S+8L1qWtlD+3eBmlbPEar9Cw==","signature_status":"signed_v1","signed_at":"2026-06-09T02:08:03.555184Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.09156","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f40662437b905f8bdf8858ec24147109154d1189df2afe227f7d2af55f97a69e","sha256:9cb111d7aae4e7db46e758248cc72262283982767be1faaf1718d363e2d3ee89"],"state_sha256":"d033ca1cca7d911883fa588f645899c08add1d50a83e3f137cbe0e154715d175"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"agVT+lbJ1aRW8xHAQzAeqooCLQ0sqHGxgP92bfWUAXStmOqhUZljvMAZBv9yT4HlCu2ibeKMF6Mj1cpxuQ6NDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-30T17:02:42.279042Z","bundle_sha256":"d6f692e301f0a52744084c910aaa74ccb1e5cdfb64d11c934df70f9a5ef75602"}}