6 citations · 10 across the 10 of their papers we have counts for
12 papers
EntroRouter: Learning Efficient Model Routing via Entropy Regulation
Kaiyi Zhang, Xueliang Zhao, Zhuocheng Gong +2
Model routing balances solution accuracy and computational cost by selecting among models of varying capabilities. While recent multi-round frameworks interleave reasoning and plan…
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…
Human Decision-making is Susceptible to AI-driven Manipulation
Sahand Sabour, June M. Liu, Siyang Liu +13
AI systems are increasingly intertwined with daily life, assisting users with various tasks and guiding decision-making. This integration introduces risks of AI-driven manipulation…
2D-TPE: Two-Dimensional Positional Encoding Enhances Table Understanding for Large Language Models
Jia-Nan Li, Jian Guan, Wei Wu +2
Tables are ubiquitous across various domains for concisely representing structured information. Empowering large language models (LLMs) to reason over tabular data represents an ac…
Unlocking Reasoning Potential in Large Langauge Models by Scaling Code-form Planning
Jiaxin Wen, Jian Guan, Hongning Wang +2
Despite the remarkable success of large language models (LLMs) on traditional natural language processing tasks, their planning ability remains a critical bottleneck in tackling co…
Mixture-of-Modules: Reinventing Transformers as Dynamic Assemblies of Modules
Zhuocheng Gong, Ang Lv, Jian Guan +6
Is it always necessary to compute tokens from shallow to deep layers in Transformers? The continued success of vanilla Transformers and their variants suggests an undoubted "yes".…
AMOR: A Recipe for Building Adaptable Modular Knowledge Agents Through Process Feedback
Jian Guan, Wei Wu, Zujie Wen +3
The notable success of large language models (LLMs) has sparked an upsurge in building language agents to complete various complex tasks. We present AMOR, an agent framework based…