5 papers
LePREC: Reasoning as Classification over Structured Factors for Assessing Relevance of Legal Issues
Fanyu Wang, Xiaoxi Kang, Paul Burgess +6
More than half of the global population struggles to meet their civil justice needs due to limited legal resources. While Large Language Models (LLMs) have demonstrated impressive…
On the Reliability of Large Language Models for Causal Discovery
Tao Feng, Lizhen Qu, Niket Tandon +3
This study investigates the efficacy of Large Language Models (LLMs) in causal discovery. Using newly available open-source LLMs, OLMo and BLOOM, which provide access to their pre-…
Automating IRAC Analysis in Malaysian Contract Law using a Semi-Structured Knowledge Base
Xiaoxi Kang, Lizhen Qu, Lay-Ki Soon +2
The effectiveness of Large Language Models (LLMs) in legal reasoning is often limited due to the unique legal terminologies and the necessity for highly specialized knowledge. Thes…
NAP^2: A Benchmark for Naturalness and Privacy-Preserving Text Rewriting by Learning from Human
Shuo Huang, William MacLean, Xiaoxi Kang +5
The widespread use of cloud-based Large Language Models (LLMs) has heightened concerns over user privacy, as sensitive information may be inadvertently exposed during interactions…
ACCESS : A Benchmark for Abstract Causal Event Discovery and Reasoning
Vy Vo, Lizhen Qu, Tao Feng +6
Identifying cause-and-effect relationships is critical to understanding real-world dynamics and ultimately causal reasoning. Existing methods for identifying event causality in NLP…