{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:LIOFACNKTFNJRJ4MW7Q4GP4IFP","short_pith_number":"pith:LIOFACNK","canonical_record":{"source":{"id":"2606.09169","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-06-08T08:08:20Z","cross_cats_sorted":["cs.CV","cs.MM"],"title_canon_sha256":"be90d15e7f05a5a0da87bcaf4b1dbd915eb47aac12d16fe02acd97895e3e46c8","abstract_canon_sha256":"de4e7b8ea3f135955ac71245b6bfe3f3e1cc623ce0f9b433a2eb5d3fab5cb64b"},"schema_version":"1.0"},"canonical_sha256":"5a1c5009aa995a98a78cb7e1c33f882be35685913755855f91a87271201429f8","source":{"kind":"arxiv","id":"2606.09169","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.09169","created_at":"2026-06-09T02:08:04Z"},{"alias_kind":"arxiv_version","alias_value":"2606.09169v1","created_at":"2026-06-09T02:08:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.09169","created_at":"2026-06-09T02:08:04Z"},{"alias_kind":"pith_short_12","alias_value":"LIOFACNKTFNJ","created_at":"2026-06-09T02:08:04Z"},{"alias_kind":"pith_short_16","alias_value":"LIOFACNKTFNJRJ4M","created_at":"2026-06-09T02:08:04Z"},{"alias_kind":"pith_short_8","alias_value":"LIOFACNK","created_at":"2026-06-09T02:08:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:LIOFACNKTFNJRJ4MW7Q4GP4IFP","target":"record","payload":{"canonical_record":{"source":{"id":"2606.09169","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-06-08T08:08:20Z","cross_cats_sorted":["cs.CV","cs.MM"],"title_canon_sha256":"be90d15e7f05a5a0da87bcaf4b1dbd915eb47aac12d16fe02acd97895e3e46c8","abstract_canon_sha256":"de4e7b8ea3f135955ac71245b6bfe3f3e1cc623ce0f9b433a2eb5d3fab5cb64b"},"schema_version":"1.0"},"canonical_sha256":"5a1c5009aa995a98a78cb7e1c33f882be35685913755855f91a87271201429f8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-09T02:08:04.396610Z","signature_b64":"dkX0kIy95OLdqYQWEqH81CKETiyqbXZ1W28I3+Q3BK9d8NQICg663PnNAOjHZ0rnc7e1KoSCCiyHKPPVb4CbDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5a1c5009aa995a98a78cb7e1c33f882be35685913755855f91a87271201429f8","last_reissued_at":"2026-06-09T02:08:04.395634Z","signature_status":"signed_v1","first_computed_at":"2026-06-09T02:08:04.395634Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.09169","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":"2026-06-09T02:08:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xNS11LBng4XWec0u1Luf0TpMsE71iX9S0gDj7uK86trNs0QoFn/JFvmgQYOxmtRkTd5H4k//HPHKRoCqevxjBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T22:56:16.880325Z"},"content_sha256":"82be343ebf994d5c66628dcdb3f320638454cc33130469d1ec9cf37a612bc128","schema_version":"1.0","event_id":"sha256:82be343ebf994d5c66628dcdb3f320638454cc33130469d1ec9cf37a612bc128"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:LIOFACNKTFNJRJ4MW7Q4GP4IFP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"IMUG-Bench: Benchmarking Unified Multimodal Models on Interleaved Understanding and Generation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV","cs.MM"],"primary_cat":"cs.AI","authors_text":"Bo Dai, Chunwei Wang, Hangshuo Cao, Haoran Li, Kaixuan Wang, Lingyi Meng, Qi Kang, Tengju Ru, Weitong Lian, Yechi Liu, Yichen Zhu, Yu-Jie Yuan, Yu Zhang, Zecong Tang, Zhejun Cui","submitted_at":"2026-06-08T08:08:20Z","abstract_excerpt":"In recent years, unified multimodal models (UMMs) have emerged to support both understanding and generation within a single framework. Mastering dynamic, multi-turn interleaved image-text dialogues is a crucial task for UMMs in real-world applications. However, existing benchmarks fail to evaluate this important task, as they are often limited to single-turn or static settings, and typically overlook exposure bias in multi-turn interactions. To bridge this gap, we propose IMUG-Bench, a comprehensive benchmark for multi-turn interleaved image-text dialogue of UMMs that jointly evaluates their u"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.09169","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/2606.09169/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":"2026-06-09T02:08:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fXvALXfSNSxE3WY1HkMAGNSNJdPBDAd1a+lf19BFA02graXPqqetGKK4uWFyClp2BevhSAkoFr1+CzD8rLr8BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T22:56:16.880706Z"},"content_sha256":"a948570831626218778e88fea65e7adbdb91a19cde2ef95e4185564517e946a2","schema_version":"1.0","event_id":"sha256:a948570831626218778e88fea65e7adbdb91a19cde2ef95e4185564517e946a2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LIOFACNKTFNJRJ4MW7Q4GP4IFP/bundle.json","state_url":"https://pith.science/pith/LIOFACNKTFNJRJ4MW7Q4GP4IFP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LIOFACNKTFNJRJ4MW7Q4GP4IFP/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":"2026-06-26T22:56:16Z","links":{"resolver":"https://pith.science/pith/LIOFACNKTFNJRJ4MW7Q4GP4IFP","bundle":"https://pith.science/pith/LIOFACNKTFNJRJ4MW7Q4GP4IFP/bundle.json","state":"https://pith.science/pith/LIOFACNKTFNJRJ4MW7Q4GP4IFP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LIOFACNKTFNJRJ4MW7Q4GP4IFP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:LIOFACNKTFNJRJ4MW7Q4GP4IFP","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":"de4e7b8ea3f135955ac71245b6bfe3f3e1cc623ce0f9b433a2eb5d3fab5cb64b","cross_cats_sorted":["cs.CV","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-06-08T08:08:20Z","title_canon_sha256":"be90d15e7f05a5a0da87bcaf4b1dbd915eb47aac12d16fe02acd97895e3e46c8"},"schema_version":"1.0","source":{"id":"2606.09169","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.09169","created_at":"2026-06-09T02:08:04Z"},{"alias_kind":"arxiv_version","alias_value":"2606.09169v1","created_at":"2026-06-09T02:08:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.09169","created_at":"2026-06-09T02:08:04Z"},{"alias_kind":"pith_short_12","alias_value":"LIOFACNKTFNJ","created_at":"2026-06-09T02:08:04Z"},{"alias_kind":"pith_short_16","alias_value":"LIOFACNKTFNJRJ4M","created_at":"2026-06-09T02:08:04Z"},{"alias_kind":"pith_short_8","alias_value":"LIOFACNK","created_at":"2026-06-09T02:08:04Z"}],"graph_snapshots":[{"event_id":"sha256:a948570831626218778e88fea65e7adbdb91a19cde2ef95e4185564517e946a2","target":"graph","created_at":"2026-06-09T02:08:04Z","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/2606.09169/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, unified multimodal models (UMMs) have emerged to support both understanding and generation within a single framework. Mastering dynamic, multi-turn interleaved image-text dialogues is a crucial task for UMMs in real-world applications. However, existing benchmarks fail to evaluate this important task, as they are often limited to single-turn or static settings, and typically overlook exposure bias in multi-turn interactions. To bridge this gap, we propose IMUG-Bench, a comprehensive benchmark for multi-turn interleaved image-text dialogue of UMMs that jointly evaluates their u","authors_text":"Bo Dai, Chunwei Wang, Hangshuo Cao, Haoran Li, Kaixuan Wang, Lingyi Meng, Qi Kang, Tengju Ru, Weitong Lian, Yechi Liu, Yichen Zhu, Yu-Jie Yuan, Yu Zhang, Zecong Tang, Zhejun Cui","cross_cats":["cs.CV","cs.MM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-06-08T08:08:20Z","title":"IMUG-Bench: Benchmarking Unified Multimodal Models on Interleaved Understanding and Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.09169","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":"sha256:82be343ebf994d5c66628dcdb3f320638454cc33130469d1ec9cf37a612bc128","target":"record","created_at":"2026-06-09T02:08:04Z","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":"de4e7b8ea3f135955ac71245b6bfe3f3e1cc623ce0f9b433a2eb5d3fab5cb64b","cross_cats_sorted":["cs.CV","cs.MM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-06-08T08:08:20Z","title_canon_sha256":"be90d15e7f05a5a0da87bcaf4b1dbd915eb47aac12d16fe02acd97895e3e46c8"},"schema_version":"1.0","source":{"id":"2606.09169","kind":"arxiv","version":1}},"canonical_sha256":"5a1c5009aa995a98a78cb7e1c33f882be35685913755855f91a87271201429f8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5a1c5009aa995a98a78cb7e1c33f882be35685913755855f91a87271201429f8","first_computed_at":"2026-06-09T02:08:04.395634Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-09T02:08:04.395634Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"dkX0kIy95OLdqYQWEqH81CKETiyqbXZ1W28I3+Q3BK9d8NQICg663PnNAOjHZ0rnc7e1KoSCCiyHKPPVb4CbDw==","signature_status":"signed_v1","signed_at":"2026-06-09T02:08:04.396610Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.09169","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:82be343ebf994d5c66628dcdb3f320638454cc33130469d1ec9cf37a612bc128","sha256:a948570831626218778e88fea65e7adbdb91a19cde2ef95e4185564517e946a2"],"state_sha256":"76ce228c884da6d42431b2baafc619b10639ba6efbca35377f93dca83eb817bd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CfvrqfKRezDQqIuLAgOJ5AaXThPtMqofSpiSD9yq6tIW3kBXHNCJnSWEYXXGpSSAFIPM22Eim59n1pOVc2bhBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-26T22:56:16.882696Z","bundle_sha256":"c5ad1640fc1a9162de417938f065f3a9b1157c9ba08a754daa39099eda2b3575"}}