4 papers
Rethinking Fine-Tuning: Unlocking Hidden Capabilities in Vision-Language Models
Mingyuan Zhang, Yue Bai, Yifan Wang +2
Explorations in fine-tuning Vision-Language Models (VLMs), such as Low-Rank Adaptation (LoRA) from Parameter Efficient Fine-Tuning (PEFT), have made impressive progress. However, m…
Cautious Next Token Prediction
Yizhou Wang, Lingzhi Zhang, Yue Bai +7
Next token prediction paradigm has been prevailing for autoregressive models in the era of LLMs. The current default sampling choice for popular LLMs is temperature scaling togethe…
Trajectory Prediction Meets Large Language Models: A Survey
Yi Xu, Ruining Yang, Yitian Zhang +5
Recent advances in large language models (LLMs) have sparked growing interest in integrating language-driven techniques into trajectory prediction. By leveraging their semantic and…
Boosting Large Language Models with Mask Fine-Tuning
Mingyuan Zhang, Yue Bai, Huan Wang +4
The large language model (LLM) is typically integrated into the mainstream optimization protocol. No work has questioned whether maintaining the model integrity is \textit{indispen…