ArXiv TLDR

Yaxuan Li

3 papers · Latest:

Robotics

dWorldEval: Scalable Robotic Policy Evaluation via Discrete Diffusion World Model

dWorldEval introduces a discrete diffusion world model for scalable robotic policy evaluation, unifying modalities and outperforming prior methods.

2604.22152
Robotics

Hi-WM: Human-in-the-World-Model for Scalable Robot Post-Training

Hi-WM enables scalable robot post-training by allowing human intervention directly within a learned world model, reducing real-world execution needs.

2604.21741
Machine Learning

Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe

This paper investigates on-policy distillation (OPD) dynamics in LLMs, identifying success conditions, token-level mechanisms, and practical recovery strategies.

2604.13016

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