8 citations · 13 across the 15 of their papers we have counts for
4 papers · 1 filter
Forking Paths in Neural Text Generation
Eric Bigelow, Ari Holtzman, Hidenori Tanaka +1
Estimating uncertainty in Large Language Models (LLMs) is important for properly evaluating LLMs, and ensuring safety for users. However, prior approaches to uncertainty estimation…
The Illusion-Illusion: Vision Language Models See Illusions Where There Are None
Tomer Ullman
Illusions are entertaining, but they are also a useful diagnostic tool in cognitive science, philosophy, and neuroscience. A typical illusion shows a gap between how something `rea…
Relations, Negations, and Numbers: Looking for Logic in Generative Text-to-Image Models
Colin Conwell, Rupert Tawiah-Quashie, Tomer Ullman
Despite remarkable progress in multi-modal AI research, there is a salient domain in which modern AI continues to lag considerably behind even human children: the reliable deployme…
One fish, two fish, but not the whole sea: Alignment reduces language models' conceptual diversity
Sonia K. Murthy, Tomer Ullman, Jennifer Hu
Researchers in social science and psychology have recently proposed using large language models (LLMs) as replacements for humans in behavioral research. In addition to arguments a…