Unverified50% confidenceFactExact time
Unified multimodal models (UMMs) perform poorly when using language chain-of-thought (CoT) to assist image generation, and cannot inherit the test-time scaling and fine-grained controllability of large language models.
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11/2/2026
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UnverifiedThe core characteristic of unified multimodal models (UMMs) is that a single model simultaneously possesses multi-task capabilities such as visual understanding, text understanding, and image generation; representative works include Chameleon, Transfusion, Janus, and others.71% similarUnverified大语言模型采用自回归生成机制，在生成token时使用单向前向注意力，无法进行全局类型校验，易产生API幻觉67% similarUnverifiedThe research concludes that models can capture local formal patterns but struggle to perform the global hierarchical planning required for robust linguistic-aesthetic reasoning.66% similarUnverifiedEven with chain-of-thought (CoT) prompting, models still cannot stably ignore irrelevant images, demonstrating that making a model explain its reasoning is not equivalent to making it comply with annotation constraints.66% similarUnverifiedThis arXiv paper points out that if large language models are trained on isolated triples, they tend not to learn the surrounding context of those triples, which is necessary for multi-hop reasoning.64% similar
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