8 citations · 12 across the 4 of their papers we have counts for
8 papers
Counterspeech for Mitigating the Influence of Media Bias: Comparing Human and LLM-Generated Responses
Luyang Lin, Zijin Feng, Lingzhi Wang +1
Biased news contributes to societal polarization and is often reinforced by hostile reader comments, constituting a vital yet often overlooked aspect of news dissemination. Our stu…
Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception
Luyang Lin, Lingzhi Wang, Jinsong Guo +1
The pervasive spread of misinformation and disinformation in social media underscores the critical importance of detecting media bias. While robust Large Language Models (LLMs) hav…
IndiTag: An Online Media Bias Analysis System Using Fine-Grained Bias Indicators
Luyang Lin, Lingzhi Wang, Jinsong Guo +2
In the age of information overload and polarized discourse, understanding media bias has become imperative for informed decision-making and fostering a balanced public discourse. H…
Selective Forgetting: Advancing Machine Unlearning Techniques and Evaluation in Language Models
Lingzhi Wang, Xingshan Zeng, Jinsong Guo +2
This paper explores Machine Unlearning (MU), an emerging field that is gaining increased attention due to concerns about neural models unintentionally remembering personal or sensi…
IndiVec: An Exploration of Leveraging Large Language Models for Media Bias Detection with Fine-Grained Bias Indicators
Luyang Lin, Lingzhi Wang, Xiaoyan Zhao +2
This study focuses on media bias detection, crucial in today's era of influential social media platforms shaping individual attitudes and opinions. In contrast to prior work that p…
A Survey of the Evolution of Language Model-Based Dialogue Systems: Data, Task and Models
Hongru Wang, Lingzhi Wang, Yiming Du +4
Dialogue systems (DS), including the task-oriented dialogue system (TOD) and the open-domain dialogue system (ODD), have always been a fundamental task in natural language processi…