19 citations · 35 across the 12 of their papers we have counts for
6 papers · 1 filter
Learning Generalizable Agents via Saliency-Guided Features Decorrelation
Sili Huang, Yanchao Sun, Jifeng Hu +5
In visual-based Reinforcement Learning (RL), agents often struggle to generalize well to environmental variations in the state space that were not observed during training. The var…
Benchmarking and Analyzing Robust Point Cloud Recognition: Bag of Tricks for Defending Adversarial Examples
Qiufan Ji, Lin Wang, Cong Shi +3
Deep Neural Networks (DNNs) for 3D point cloud recognition are vulnerable to adversarial examples, threatening their practical deployment. Despite the many research endeavors have…
MM-LIMA: Less Is More for Alignment in Multi-Modal Datasets
Lai Wei, Xiaozhe Li, Zihao Jiang +2
Multimodal large language models are typically trained in two stages: first pre-training on image-text pairs, and then fine-tuning using supervised vision-language instruction data…
Evaluating Large Language Models for Radiology Natural Language Processing
Zhengliang Liu, Tianyang Zhong, Yiwei Li +43
The rise of large language models (LLMs) has marked a pivotal shift in the field of natural language processing (NLP). LLMs have revolutionized a multitude of domains, and they hav…
Instructed Diffuser with Temporal Condition Guidance for Offline Reinforcement Learning
Jifeng Hu, Yanchao Sun, Sili Huang +6
Recent works have shown the potential of diffusion models in computer vision and natural language processing. Apart from the classical supervised learning fields, diffusion models…
A Simple Unified Uncertainty-Guided Framework for Offline-to-Online Reinforcement Learning
Siyuan Guo, Yanchao Sun, Jifeng Hu +5
Offline reinforcement learning (RL) provides a promising solution to learning an agent fully relying on a data-driven paradigm. However, constrained by the limited quality of the o…