6 citations · 14 across the 31 of their papers we have counts for
7 papers · 2 filters
FairMT-Bench: Benchmarking Fairness for Multi-turn Dialogue in Conversational LLMs
Zhiting Fan, Ruizhe Chen, Tianxiang Hu +1
The growing use of large language model (LLM)-based chatbots has raised concerns about fairness. Fairness issues in LLMs can lead to severe consequences, such as bias amplification…
PAD: Personalized Alignment of LLMs at Decoding-Time
Ruizhe Chen, Xiaotian Zhang, Meng Luo +2
Aligning with personalized preferences, which vary significantly across cultural, educational, and political differences, poses a significant challenge due to the computational cos…
DynamicNER: A Dynamic, Multilingual, and Fine-Grained Dataset for LLM-based Named Entity Recognition
Hanjun Luo, Yingbin Jin, Xinfeng Li +6
The advancements of Large Language Models (LLMs) have spurred a growing interest in their application to Named Entity Recognition (NER) methods. However, existing datasets are prim…
Identifying and Mitigating Social Bias Knowledge in Language Models
Ruizhe Chen, Yichen Li, Jianfei Yang +3
Generating fair and accurate predictions plays a pivotal role in deploying large language models (LLMs) in the real world. However, existing debiasing methods inevitably generate u…
BiasAlert: A Plug-and-play Tool for Social Bias Detection in LLMs
Zhiting Fan, Ruizhe Chen, Ruiling Xu +1
Evaluating the bias in Large Language Models (LLMs) becomes increasingly crucial with their rapid development. However, existing evaluation methods rely on fixed-form outputs and c…
Large Language Model Bias Mitigation from the Perspective of Knowledge Editing
Ruizhe Chen, Yichen Li, Zikai Xiao +1
Existing debiasing methods inevitably make unreasonable or undesired predictions as they are designated and evaluated to achieve parity across different social groups but leave asi…
Ladder: A Model-Agnostic Framework Boosting LLM-based Machine Translation to the Next Level
Zhaopeng Feng, Ruizhe Chen, Yan Zhang +2
General-purpose Large Language Models (LLMs) like GPT-4 have achieved remarkable advancements in machine translation (MT) by leveraging extensive web content. On the other hand, tr…