7 citations · 19 across the 7 of their papers we have counts for
3 papers · 1 filter
Rel-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliance
Kaitlyn Zhou, Jena D. Hwang, Xiang Ren +3
The ability to communicate uncertainty, risk, and limitation is crucial for the safety of large language models. However, current evaluations of these abilities rely on simple cali…
Training LLMs over Neurally Compressed Text
Brian Lester, Jaehoon Lee, Alex Alemi +4
In this paper, we explore the idea of training large language models (LLMs) over highly compressed text. While standard subword tokenizers compress text by a small factor, neural t…
Transfer Learning for Text Diffusion Models
Kehang Han, Kathleen Kenealy, Aditya Barua +2
In this report, we explore the potential for text diffusion to replace autoregressive (AR) decoding for the training and deployment of large language models (LLMs). We are particul…