1 citations · 2 across the 22 of their papers we have counts for
14 papers · 1 filter
x1: Learning to Think Adaptively Across Languages and Cultures
Yangfan Ye, Xiaocheng Feng, Xiachong Feng +8
Languages encode distinct abstractions and inductive priors, yet most large language models (LLMs) overlook this diversity by reasoning in a single dominant language. In this work,…
Can Large Language Models Simulate Human Cognition Beyond Behavioral Imitation?
Yuxuan Gu, Lunjun Liu, Xiaocheng Feng +4
An essential problem in artificial intelligence is whether LLMs can simulate human cognition or merely imitate surface-level behaviors, while existing datasets suffer from either s…
Bootstrapping Exploration with Group-Level Natural Language Feedback in Reinforcement Learning
Lei Huang, Xiang Cheng, Chenxiao Zhao +6
Large language models (LLMs) typically receive diverse natural language (NL) feedback through interaction with the environment. However, current reinforcement learning (RL) algorit…
Fine-Mem: Fine-Grained Feedback Alignment for Long-Horizon Memory Management
Weitao Ma, Xiaocheng Feng, Lei Huang +7
Effective memory management is essential for large language model agents to navigate long-horizon tasks. Recent research has explored using Reinforcement Learning to develop specia…
LangGPS: Language Separability Guided Data Pre-Selection for Joint Multilingual Instruction Tuning
Yangfan Ye, Xiaocheng Feng, Xiachong Feng +7
Joint multilingual instruction tuning is a widely adopted approach to improve the multilingual instruction-following ability and downstream performance of large language models (LL…
Context-Aware Hierarchical Taxonomy Generation for Scientific Papers via LLM-Guided Multi-Aspect Clustering
Kun Zhu, Lizi Liao, Yuxuan Gu +3
The rapid growth of scientific literature demands efficient methods to organize and synthesize research findings. Existing taxonomy construction methods, leveraging unsupervised cl…