8 papers
DynaAct: Large Language Model Reasoning with Dynamic Action Spaces
Xueliang Zhao, Wei Wu, Jian Guan +2
In modern sequential decision-making systems, the construction of an optimal candidate action space is critical to efficient inference. However, existing approaches either rely on…
PromptCoT 2.0: Scaling Prompt Synthesis for Large Language Model Reasoning
Xueliang Zhao, Wei Wu, Jian Guan +2
Large language models (LLMs) are evolving from conversational systems into strong reasoners for tasks such as Olympiad mathematics and competitive programming. While scaling parame…
Scaling Reasoning without Attention
Xueliang Zhao, Wei Wu, Lingpeng Kong
Large language models (LLMs) have made significant advances in complex reasoning tasks, yet they remain bottlenecked by two core challenges: architectural inefficiency due to relia…
Latent Preference Coding: Aligning Large Language Models via Discrete Latent Codes
Zhuocheng Gong, Jian Guan, Wei Wu +2
Large language models (LLMs) have achieved remarkable success, yet aligning their generations with human preferences remains a critical challenge. Existing approaches to preference…
PromptCoT: Synthesizing Olympiad-level Problems for Mathematical Reasoning in Large Language Models
Xueliang Zhao, Wei Wu, Jian Guan +1
The ability of large language models to solve complex mathematical problems has progressed significantly, particularly for tasks requiring advanced reasoning. However, the scarcity…
Theoretical Benefit and Limitation of Diffusion Language Model
Guhao Feng, Yihan Geng, Jian Guan +3
Diffusion language models have emerged as a promising approach for text generation. One would naturally expect this method to be an efficient replacement for autoregressive models…