Author

Zhen-Yu Liao

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Preprint Sep 2026

DIDO: Distilling Interaction-Centric Dynamics into One-Step Denoising for World Action Models

This work proposes DIDO, which distills the converged dynamics of a multi-step video model into a single denoising step and achieves an average success rate of 99.0\% on LIBERO, 76.6\% on LIBERO-Plus, and 92.0\% on RoboTwin, while also demonstrating effective transfer to long-horizon and generalization tasks in real-wo...

Jing Lyu, Shuanghao Bai, Run-Ze Xiao et al. · 2 citations

Preprint Aug 2026

Ask to Be Sure: Informative Interactions for Confident Multi-Turn LLM Recommendation

This work proposes a new approach that quantifies the effectiveness of each interaction by the reduction in the assistant's uncertainty, measured via entropy over recommendations, to fine-tune the LLM, enabling strategic interaction generation.

Cedar Site Bai, Zhen-Yu Liao, Duan Li et al. · 0 citations

#machine learning Preprint Aug 2026

Scaling Automatic Research Agents via World Models

This paper proposes World Model RL (WMRL), which replaces environment execution with a world model to remove this bottleneck and accelerates training by 3-4x on various tasks at different agent scales, while exceeding the performance of standard RL baselines.

Xi-Yuan Yang, S. Sarwar, Jingru Cheng et al. · 1 citation