103 citations · 330 across the 70 of their papers we have counts for
5 papers · 2 filters
: A Distribution-Aware Adversarial Attack against Language Models
Yibo Wang, Xiangjue Dong, James Caverlee +1
Language models can be manipulated by adversarial attacks, which introduce subtle perturbations to input data. While recent attack methods can achieve a relatively high attack succ…
Probing Explicit and Implicit Gender Bias through LLM Conditional Text Generation
Xiangjue Dong, Yibo Wang, Philip S. Yu +1
Large Language Models (LLMs) can generate biased and toxic responses. Yet most prior work on LLM gender bias evaluation requires predefined gender-related phrases or gender stereot…
Unsupervised Candidate Answer Extraction through Differentiable Masker-Reconstructor Model
Zhuoer Wang, Yicheng Wang, Ziwei Zhu +1
Question generation is a widely used data augmentation approach with extensive applications, and extracting qualified candidate answers from context passages is a critical step for…
CoPT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning
Xiangjue Dong, Ziwei Zhu, Zhuoer Wang +2
Pre-trained Language Models are widely used in many important real-world applications. However, recent studies show that these models can encode social biases from large pre-traini…
PromptAttack: Probing Dialogue State Trackers with Adversarial Prompts
Xiangjue Dong, Yun He, Ziwei Zhu +1
A key component of modern conversational systems is the Dialogue State Tracker (or DST), which models a user's goals and needs. Toward building more robust and reliable DSTs, we in…