44 citations · 76 across the 4 of their papers we have counts for
4 papers
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
Neel Guha, Julian Nyarko, Daniel E. Ho +37
The advent of large language models (LLMs) and their adoption by the legal community has given rise to the question: what types of legal reasoning can LLMs perform? To enable great…
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
Neel Guha, Mayee F. Chen, Kush Bhatia +3
Recent work has shown that language models' (LMs) prompt-based learning capabilities make them well suited for automating data labeling in domains where manual annotation is expens…
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset
Peter Henderson, Mark S. Krass, Lucia Zheng +4
One concern with the rise of large language models lies with their potential for significant harm, particularly from pretraining on biased, obscene, copyrighted, and private inform…
Semantic Identification Attacks on Web Browsing
Neel Guha
We introduce a Semantic Identification Attack, in which an adversary uses semantic signals about the pages visited in one browsing session to identify other browsing sessions launc…