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cs.CL2025
CANDY: Benchmarking LLMs' Limitations and Assistive Potential in Chinese Misinformation Fact-Checking
Ruiling Guo, Xinwei Yang, Chen Huang +2
The effectiveness of large language models (LLMs) to fact-check misinformation remains uncertain, despite their growing use. To this end, we present CANDY, a benchmark designed to…
cs.CL2024★ 2 cited
CLAMBER: A Benchmark of Identifying and Clarifying Ambiguous Information Needs in Large Language Models
Tong Zhang, Peixin Qin, Yang Deng +6
Large language models (LLMs) are increasingly used to meet user information needs, but their effectiveness in dealing with user queries that contain various types of ambiguity rema…
cs.CL2024
Strength Lies in Differences! Improving Strategy Planning for Non-collaborative Dialogues via Diversified User Simulation
Tong Zhang, Chen Huang, Yang Deng +5
We investigate non-collaborative dialogue agents, which are expected to engage in strategic conversations with diverse users, for securing a mutual agreement that leans favorably t…