3 papers
cs.LG2025
Entropy After </Think> for reasoning model early exiting
Xi Wang, James McInerney, Lequn Wang +1
Reasoning LLMs show improved performance with longer chains of thought. However, recent work has highlighted their tendency to overthink, continuing to revise answers even after re…
cs.CV2025
Are vision language models robust to uncertain inputs?
Xi Wang, Eric Nalisnick
Robustness against uncertain and ambiguous inputs is a critical challenge for deep learning models. While recent advancements in large scale vision language models (VLMs, e.g. GPT4…
cs.AI2024
KBLaM: Knowledge Base augmented Language Model
Xi Wang, Taketomo Isazawa, Liana Mikaelyan +1
In this paper, we propose Knowledge Base augmented Language Model (KBLaM), a new method for augmenting Large Language Models (LLMs) with external knowledge. KBLaM works with a know…