36 citations · 55 across the 11 of their papers we have counts for
4 papers · 1 filter
Image2Struct: Benchmarking Structure Extraction for Vision-Language Models
Josselin Somerville Roberts, Tony Lee, Chi Heem Wong +3
We introduce Image2Struct, a benchmark to evaluate vision-language models (VLMs) on extracting structure from images. Our benchmark 1) captures real-world use cases, 2) is fully au…
VHELM: A Holistic Evaluation of Vision Language Models
Tony Lee, Haoqin Tu, Chi Heem Wong +8
Current benchmarks for assessing vision-language models (VLMs) often focus on their perception or problem-solving capabilities and neglect other critical aspects such as fairness,…
Embodied Agent Interface: Benchmarking LLMs for Embodied Decision Making
Manling Li, Shiyu Zhao, Qineng Wang +12
We aim to evaluate Large Language Models (LLMs) for embodied decision making. While a significant body of work has been leveraging LLMs for decision making in embodied environments…
BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text
Elliot Bolton, Abhinav Venigalla, Michihiro Yasunaga +8
Models such as GPT-4 and Med-PaLM 2 have demonstrated impressive performance on a wide variety of biomedical NLP tasks. However, these models have hundreds of billions of parameter…