23 citations · 64 across the 11 of their papers we have counts for
14 papers · 1 filter
Benchmarking Gender and Political Bias in Large Language Models
Jinrui Yang, Xudong Han, Timothy Baldwin
We introduce EuroParlVote, a novel benchmark for evaluating large language models (LLMs) in politically sensitive contexts. It links European Parliament debate speeches to roll-cal…
ParlAI Vote: A Web Platform for Analyzing Gender and Political Bias in Large Language Models
Wenjie Lin, Hange Liu, Yingying Zhuang +5
We present ParlAI Vote, an interactive web platform for exploring European Parliament debates and votes, and for testing LLMs on vote prediction and bias analysis. This web system…
RuozhiBench: Evaluating LLMs with Logical Fallacies and Misleading Premises
Zenan Zhai, Hao Li, Xudong Han +4
Recent advances in large language models (LLMs) have shown that they can answer questions requiring complex reasoning. However, their ability to identify and respond to text contai…
ToolGen: Unified Tool Retrieval and Calling via Generation
Renxi Wang, Xudong Han, Lei Ji +3
As large language models (LLMs) advance, their inability to autonomously execute tasks by directly interacting with external tools remains a critical limitation. Traditional method…
Against The Achilles' Heel: A Survey on Red Teaming for Generative Models
Lizhi Lin, Honglin Mu, Zenan Zhai +9
Generative models are rapidly gaining popularity and being integrated into everyday applications, raising concerns over their safe use as various vulnerabilities are exposed. In li…
A Chinese Dataset for Evaluating the Safeguards in Large Language Models
Yuxia Wang, Zenan Zhai, Haonan Li +6
Many studies have demonstrated that large language models (LLMs) can produce harmful responses, exposing users to unexpected risks when LLMs are deployed. Previous studies have pro…