174 citations · 209 across the 3 of their papers we have counts for
3 papers
cs.CR2023★ 13 cited
Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models
Xin Jin, Jonathan Larson, Weiwei Yang +1
Binary code summarization, while invaluable for understanding code semantics, is challenging due to its labor-intensive nature. This study delves into the potential of large langua…
cs.CL2023★ 174 cited
Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine
Harsha Nori, Yin Tat Lee, Sheng Zhang +15
Generalist foundation models such as GPT-4 have displayed surprising capabilities in a wide variety of domains and tasks. Yet, there is a prevalent assumption that they cannot matc…
cs.AI2023★ 22 cited
Evaluating Cognitive Maps and Planning in Large Language Models with CogEval
Ida Momennejad, Hosein Hasanbeig, Felipe Vieira +5
Recently an influx of studies claim emergent cognitive abilities in large language models (LLMs). Yet, most rely on anecdotes, overlook contamination of training sets, or lack syst…