2 citations · 3 across the 4 of their papers we have counts for
4 papers
Script Fragmentation and Format: What Drives the English-Bengali Performance Gap in Open LLMs?
Shimanto Bhowmik, Tawsif Tashwar Dipto, Md Sazzad Islam +2
Bengali is spoken by more than 230 million people, yet no standardized instrument evaluates large language models (LLMs) on Bengali across the task categories used to benchmark fro…
FSPO: Few-Shot Optimization of Synthetic Preferences Personalizes to Real Users
Anikait Singh, Sheryl Hsu, Kyle Hsu +5
Effective personalization of LLMs is critical for a broad range of user-interfacing applications such as virtual assistants and content curation. Inspired by the strong in-context…
Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval
Sheryl Hsu, Omar Khattab, Chelsea Finn +1
The hallucinations of large language models (LLMs) are increasingly mitigated by allowing LLMs to search for information and to ground their answers in real sources. Unfortunately,…
RLVF: Learning from Verbal Feedback without Overgeneralization
Moritz Stephan, Alexander Khazatsky, Eric Mitchell +4
The diversity of contexts in which large language models (LLMs) are deployed requires the ability to modify or customize default model behaviors to incorporate nuanced requirements…