11 papers
Trust-Region Adaptive Policy Optimization
Mingyu Su, Jian Guan, Yuxian Gu +2
Post-training methods, especially Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL), play an important role in improving large language models' (LLMs) complex reasoning…
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…
Scaling Video-Language Models to 10K Frames via Hierarchical Differential Distillation
Chuanqi Cheng, Jian Guan, Wei Wu +1
Long-form video processing fundamentally challenges vision-language models (VLMs) due to the high computational costs of handling extended temporal sequences. Existing token prunin…
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…
From 1,000,000 Users to Every User: Scaling Up Personalized Preference for User-level Alignment
Jia-Nan Li, Jian Guan, Songhao Wu +2
Large language models (LLMs) have traditionally been aligned through one-size-fits-all approaches that assume uniform human preferences, fundamentally overlooking the diversity in…
A Survey on Personalized Alignment -- The Missing Piece for Large Language Models in Real-World Applications
Jian Guan, Junfei Wu, Jia-Nan Li +2
Large Language Models (LLMs) have demonstrated remarkable capabilities, yet their transition to real-world applications reveals a critical limitation: the inability to adapt to ind…