Zihan Min — accepted AI-conference papers

2026

Cache-to-Cache: Direct Semantic Communication Between Large Language Models

Tianyu Fu, Zihan Min, Hanling Zhang, Jichao Yan, Guohao Dai, Wanli Ouyang +1

ICLR 2026poster

Multi-LLM systems harness the complementary strengths of diverse Large Language Models, achieving performance and efficiency gains unattainable by a single model. In existing designs, LLMs communicate through text, forcing internal representations to be transformed into output token sequences. This…

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2026

FourTune: Towards Fully 4-Bit Efficient Post-Training for Diffusion Models

Bowen Xue, Zihan Min, Xingyang Li, Muyang Li, Yujun Lin, Zhekai Zhang +5

ICML 2026poster

Diffusion models have become a dominant paradigm for high-quality generative modeling, while post-training is essential for adapting them to diverse downstream applications. However, post-training of large diffusion models is still challenging due to the prohibitive memory footprints and slow traini…

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