← Search

Xueyan Li

2 accepted papers

2026

Sample Smart, Not Hard: Correctness-First Decoding for Better Reasoning in LLMs

ICLR 2026poster

Large Language Models (LLMs) are increasingly applied to complex tasks that require extended reasoning. In such settings, models often benefit from diverse chains-of-thought to arrive at multiple candidate solutions. This requires two competing objectives: to inject enough stochasticity to explore m…

Cited by 0SourceScholar
2023

LightZero: A Unified Benchmark for Monte Carlo Tree Search in General Sequential Decision Scenarios

NeurIPS 2023spotlight

Building agents based on tree-search planning capabilities with learned models has achieved remarkable success in classic decision-making problems, such as Go and Atari. However, it has been deemed challenging or even infeasible to extend Monte Carlo Tree Search (MCTS) based algorithms to diverse re…