8 citations · 23 across the 11 of their papers we have counts for
11 papers
Gender Bias in Vision-Language In-Context Learning
Tong Xiang, Noa Garcia, Yuta Nakashima
In-context learning (ICL) enables large vision-language models (LVLMs) to perform tasks by following patterns from in-context examples, yet its potential to amplify societal biases…
Cracking the Code: Enhancing Implicit Hate Speech Detection through Coding Classification
Lu Wei, Liangzhi Li, Tong Xiang +2
The internet has become a hotspot for hate speech (HS), threatening societal harmony and individual well-being. While automatic detection methods perform well in identifying explic…
Imposter.AI: Adversarial Attacks with Hidden Intentions towards Aligned Large Language Models
Xiao Liu, Liangzhi Li, Tong Xiang +4
With the development of large language models (LLMs) like ChatGPT, both their vast applications and potential vulnerabilities have come to the forefront. While developers have inte…
Can multiple-choice questions really be useful in detecting the abilities of LLMs?
Wangyue Li, Liangzhi Li, Tong Xiang +3
Multiple-choice questions (MCQs) are widely used in the evaluation of large language models (LLMs) due to their simplicity and efficiency. However, there are concerns about whether…
Concatenated Masked Autoencoders as Spatial-Temporal Learner
Zhouqiang Jiang, Bowen Wang, Tong Xiang +4
Learning representations from videos requires understanding continuous motion and visual correspondences between frames. In this paper, we introduce the Concatenated Masked Autoenc…
TCRA-LLM: Token Compression Retrieval Augmented Large Language Model for Inference Cost Reduction
Junyi Liu, Liangzhi Li, Tong Xiang +2
Since ChatGPT released its API for public use, the number of applications built on top of commercial large language models (LLMs) increase exponentially. One popular usage of such…
CARE-MI: Chinese Benchmark for Misinformation Evaluation in Maternity and Infant Care
Tong Xiang, Liangzhi Li, Wangyue Li +4
The recent advances in natural language processing (NLP), have led to a new trend of applying large language models (LLMs) to real-world scenarios. While the latest LLMs are astoni…
Tell Me How to Survey: Literature Review Made Simple with Automatic Reading Path Generation
Jiayuan Ding, Tong Xiang, Zijing Ou +5
Recent years have witnessed the dramatic growth of paper volumes with plenty of new research papers published every day, especially in the area of computer science. How to glean pa…
Linguistic Characterization of Divisive Topics Online: Case Studies on Contentiousness in Abortion, Climate Change, and Gun Control
Jacob Beel, Tong Xiang, Sandeep Soni +1
As public discourse continues to move and grow online, conversations about divisive topics on social media platforms have also increased. These divisive topics prompt both contenti…
ToxCCIn: Toxic Content Classification with Interpretability
Tong Xiang, Sean MacAvaney, Eugene Yang +1
Despite the recent successes of transformer-based models in terms of effectiveness on a variety of tasks, their decisions often remain opaque to humans. Explanations are particular…
GUIR at SemEval-2020 Task 12: Domain-Tuned Contextualized Models for Offensive Language Detection
Sajad Sotudeh, Tong Xiang, Hao-Ren Yao +4
Offensive language detection is an important and challenging task in natural language processing. We present our submissions to the OffensEval 2020 shared task, which includes thre…