4 citations · 7 across the 5 of their papers we have counts for
5 papers
Evaluating AI for Law: Bridging the Gap with Open-Source Solutions
Rohan Bhambhoria, Samuel Dahan, Jonathan Li +1
This study evaluates the performance of general-purpose AI, like ChatGPT, in legal question-answering tasks, highlighting significant risks to legal professionals and clients. It s…
A Simple and Effective Framework for Strict Zero-Shot Hierarchical Classification
Rohan Bhambhoria, Lei Chen, Xiaodan Zhu
In recent years, large language models (LLMs) have achieved strong performance on benchmark tasks, especially in zero or few-shot settings. However, these benchmarks often do not a…
Prototype-Based Interpretability for Legal Citation Prediction
Chu Fei Luo, Rohan Bhambhoria, Samuel Dahan +1
Deep learning has made significant progress in the past decade, and demonstrates potential to solve problems with extensive social impact. In high-stakes decision making areas such…
Prefix Propagation: Parameter-Efficient Tuning for Long Sequences
Jonathan Li, Will Aitken, Rohan Bhambhoria +1
Parameter-efficient tuning aims to mitigate the large memory requirements of adapting pretrained language models for downstream tasks. For example, one popular method, prefix-tunin…
Interpretable Low-Resource Legal Decision Making
Rohan Bhambhoria, Hui Liu, Samuel Dahan +1
Over the past several years, legal applications of deep learning have been on the rise. However, as with other high-stakes decision making areas, the requirement for interpretabili…