Feng Zhang

LLMs can now be trained to prioritize task constraints intrinsically, resulting in a dramatic improvement in planning reliability.

Trajectory neglect in LLM agents can be significantly reduced using a novel reward mechanism that enhances focus on task goals without sacrificing training stability.

A new tensor completion method achieves superior performance by leveraging a flexible nonconvex surrogate that accurately captures tensor structure.