5 papers
Micro-Macro Retrieval: Reducing Long-Form Hallucination in Large Language Models
Yujie Feng, Jian Li, Zhihan Zhou +7
Large Language Models (LLMs) achieve impressive performance across many tasks but remain prone to hallucination, especially in long-form generation where redundant retrieved contex…
Ambiguity Awareness Optimization: Towards Semantic Disambiguation for Direct Preference Optimization
Jian Li, Shenglin Yin, Yujia Zhang +4
Direct Preference Optimization (DPO) is a widely used reinforcement learning from human feedback (RLHF) method across various domains. Recent research has increasingly focused on t…
AIMMerging: Adaptive Iterative Model Merging Using Training Trajectories for Language Model Continual Learning
Yujie Feng, Jian Li, Xiaoyu Dong +8
Continual learning (CL) is essential for deploying large language models (LLMs) in dynamic real-world environments without the need for costly retraining. Recent model merging-base…
Self-supervised Preference Optimization: Enhance Your Language Model with Preference Degree Awareness
Jian Li, Haojing Huang, Yujia Zhang +6
Recently, there has been significant interest in replacing the reward model in Reinforcement Learning with Human Feedback (RLHF) methods for Large Language Models (LLMs), such as D…
Large-scale road network partitioning: a deep learning method based on convolutional autoencoder model
Pengfei Xu, Weifeng Li, Chenjie Xu +1
With the development of urbanization, the scale of urban road network continues to expand, especially in some Asian countries. Short-term traffic state prediction is one of the bas…