8 papers
From Reward-Free Representations to Preferences: Rethinking Offline Preference-Based Reinforcement Learning
Jun-Jie Yang, Chia-Heng Hsu, Kui-Yuan Chen +1
Preference-based reinforcement learning (PbRL) avoids explicit reward engineering by learning from pairwise human preference feedback. Existing offline PbRL methods typically follo…
Towards Alignment-Centric Paradigm: A Survey of Instruction Tuning in Large Language Models
Xudong Han, Junjie Yang, Tianyang Wang +4
Instruction tuning is a pivotal technique for aligning large language models (LLMs) with human intentions, safety constraints, and domain-specific requirements. This survey provide…
Feature Alignment and Representation Transfer in Knowledge Distillation for Large Language Models
Junjie Yang, Junhao Song, Xudong Han +9
Knowledge distillation (KD) is a technique for transferring knowledge from complex teacher models to simpler student models, significantly enhancing model efficiency and accuracy.…
Advanced Deep Learning Methods for Protein Structure Prediction and Design
Yichao Zhang, Ningyuan Deng, Xinyuan Song +25
After AlphaFold won the Nobel Prize, protein prediction with deep learning once again became a hot topic. We comprehensively explore advanced deep learning methods applied to prote…
Generative Adversarial Networks Bridging Art and Machine Intelligence
Junhao Song, Yichao Zhang, Ziqian Bi +25
Generative Adversarial Networks (GAN) have greatly influenced the development of computer vision and artificial intelligence in the past decade and also connected art and machine i…
Deep Learning Model Security: Threats and Defenses
Tianyang Wang, Ziqian Bi, Yichao Zhang +24
Deep learning has transformed AI applications but faces critical security challenges, including adversarial attacks, data poisoning, model theft, and privacy leakage. This survey e…