IMUG-Bench is a new multi-turn interleaved image-text benchmark that exposes exposure bias in unified multimodal model generation and shows test-time scaling can mitigate it.
WEA VE: Unleashing and Benchmarking the In-context Interleaved Comprehension and Generation, November 2025
3 Pith papers cite this work. Polarity classification is still indexing.
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PlanViz is a new benchmark with three sub-tasks and PlanScore metric to evaluate planning-oriented image generation and editing by unified multimodal models for computer-use tasks.
ILLUME-X is a unified multimodal model that generates free-form interleaved text-image sequences via an expanded data pipeline, progressive self-adaptive training, and ILScore evaluation, claiming outperformance over prior unified models on style transfer, image decomposition, and storytelling.
citing papers explorer
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IMUG-Bench: Benchmarking Unified Multimodal Models on Interleaved Understanding and Generation
IMUG-Bench is a new multi-turn interleaved image-text benchmark that exposes exposure bias in unified multimodal model generation and shows test-time scaling can mitigate it.
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PlanViz: Evaluating Planning-Oriented Image Generation and Editing for Computer-Use Tasks
PlanViz is a new benchmark with three sub-tasks and PlanScore metric to evaluate planning-oriented image generation and editing by unified multimodal models for computer-use tasks.
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Illuminating Unified Multimodal Model for Free-form Interleaved Text-Image Generation
ILLUME-X is a unified multimodal model that generates free-form interleaved text-image sequences via an expanded data pipeline, progressive self-adaptive training, and ILScore evaluation, claiming outperformance over prior unified models on style transfer, image decomposition, and storytelling.