4 citations · 7 across the 7 of their papers we have counts for
8 papers · 1 filter
CoDial: Interpretable Task-Oriented Dialogue Systems Through Dialogue Flow Alignment
Radin Shayanfar, Chu Fei Luo, Rohan Bhambhoria +2
Building Task-Oriented Dialogue (TOD) systems that generalize across different tasks remains a challenging problem. Data-driven approaches often struggle to transfer effectively to…
Misinformation with Legal Consequences (MisLC): A New Task Towards Harnessing Societal Harm of Misinformation
Chu Fei Luo, Radin Shayanfar, Rohan Bhambhoria +2
Misinformation, defined as false or inaccurate information, can result in significant societal harm when it is spread with malicious or even innocuous intent. The rapid online info…
Experimenting with Legal AI Solutions: The Case of Question-Answering for Access to Justice
Jonathan Li, Rohan Bhambhoria, Samuel Dahan +1
Generative AI models, such as the GPT and Llama series, have significant potential to assist laypeople in answering legal questions. However, little prior work focuses on the data…
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…