8 citations · 15 across the 10 of their papers we have counts for
11 papers
Anticipating Social Consequences with Distributional World Models
Viet-Thanh Pham, Thuy-Trang Vu, Zhuang Li +2
Social world models predict how interactions develop after an action, helping agents negotiate, cooperate and mediate. In these situations, one action can lead to several plausible…
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…
TAB-AUDIT: Detecting AI-Fabricated Scientific Tables via Multi-View Likelihood Mismatch
Shuo Huang, Yan Pen, Lizhen Qu
AI-generated fabricated scientific manuscripts raise growing concerns with large-scale breaches of academic integrity. In this work, we present the first systematic study on detect…
Evidence-based Distributional Alignment for Large Language Models
Viet-Thanh Pham, Lizhen Qu, Zhuang Li +1
Distributional alignment enables large language models (LLMs) to predict how a target population distributes its responses across answer options, rather than collapsing disagreemen…
DiscoSG: Towards Discourse-Level Text Scene Graph Parsing through Iterative Graph Refinement
Shaoqing Lin, Chong Teng, Fei Li +3
Vision-Language Models (VLMs) generate discourse-level, multi-sentence visual descriptions, challenging text scene graph parsers built for single-sentence caption-to-graph mapping.…
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…
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…
RENOVI: A Benchmark Towards Remediating Norm Violations in Socio-Cultural Conversations
Haolan Zhan, Zhuang Li, Xiaoxi Kang +14
Norm violations occur when individuals fail to conform to culturally accepted behaviors, which may lead to potential conflicts. Remediating norm violations requires social awarenes…
TMID: A Comprehensive Real-world Dataset for Trademark Infringement Detection in E-Commerce
Tongxin Hu, Zhuang Li, Xin Jin +2
Annually, e-commerce platforms incur substantial financial losses due to trademark infringements, making it crucial to identify and mitigate potential legal risks tied to merchant…
Can ChatGPT Perform Reasoning Using the IRAC Method in Analyzing Legal Scenarios Like a Lawyer?
Xiaoxi Kang, Lizhen Qu, Lay-Ki Soon +4
Large Language Models (LLMs), such as ChatGPT, have drawn a lot of attentions recently in the legal domain due to its emergent ability to tackle a variety of legal tasks. However,…