Assessing The Potential Of Mid-Sized Language Models For Clinical QA

no code implementations • 24 Apr 2024 • Elliot Bolton, Betty Xiong, Vijaytha Muralidharan, Joel Schamroth, Vivek Muralidharan, Christopher D. Manning, Roxana Daneshjou

Large language models, such as GPT-4 and Med-PaLM, have shown impressive performance on clinical tasks; however, they require access to compute, are closed-source, and cannot be deployed on device.

Question Answering

BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text

1 code implementation • 27 Mar 2024 • Elliot Bolton, Abhinav Venigalla, Michihiro Yasunaga, David Hall, Betty Xiong, Tony Lee, Roxana Daneshjou, Jonathan Frankle, Percy Liang, Michael Carbin, Christopher D. Manning

Models such as GPT-4 and Med-PaLM 2 have demonstrated impressive performance on a wide variety of biomedical NLP tasks.

Language Modelling Medical Genetics +3

Foundation Model Transparency Reports

no code implementations • 26 Feb 2024 • Rishi Bommasani, Kevin Klyman, Shayne Longpre, Betty Xiong, Sayash Kapoor, Nestor Maslej, Arvind Narayanan, Percy Liang

Foundation models are critical digital technologies with sweeping societal impact that necessitates transparency.

The Foundation Model Transparency Index

1 code implementation • 19 Oct 2023 • Rishi Bommasani, Kevin Klyman, Shayne Longpre, Sayash Kapoor, Nestor Maslej, Betty Xiong, Daniel Zhang, Percy Liang

We score 10 major foundation model developers (e. g. OpenAI, Google, Meta) against the 100 indicators to assess their transparency.