477 citations · 841 across the 11 of their papers we have counts for
11 papers
The Good, The Bad, and Why: Unveiling Emotions in Generative AI
Cheng Li, Jindong Wang, Yixuan Zhang +7
Emotion significantly impacts our daily behaviors and interactions. While recent generative AI models, such as large language models, have shown impressive performance in various t…
Large Language Models Understand and Can be Enhanced by Emotional Stimuli
Cheng Li, Jindong Wang, Yixuan Zhang +6
Emotional intelligence significantly impacts our daily behaviors and interactions. Although Large Language Models (LLMs) are increasingly viewed as a stride toward artificial gener…
On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective
Jindong Wang, Xixu Hu, Wenxin Hou +10
ChatGPT is a recent chatbot service released by OpenAI and is receiving increasing attention over the past few months. While evaluations of various aspects of ChatGPT have been don…
Exploiting Unlabeled Data for Target-Oriented Opinion Words Extraction
Yidong Wang, Hao Wu, Ao Liu +6
Target-oriented Opinion Words Extraction (TOWE) is a fine-grained sentiment analysis task that aims to extract the corresponding opinion words of a given opinion target from the se…
USB: A Unified Semi-supervised Learning Benchmark for Classification
Yidong Wang, Hao Chen, Yue Fan +19
Semi-supervised learning (SSL) improves model generalization by leveraging massive unlabeled data to augment limited labeled samples. However, currently, popular SSL evaluation pro…
Boosting Cross-Domain Speech Recognition with Self-Supervision
Han Zhu, Gaofeng Cheng, Jindong Wang +3
The cross-domain performance of automatic speech recognition (ASR) could be severely hampered due to the mismatch between training and testing distributions. Since the target domai…
FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
Yidong Wang, Hao Chen, Qiang Heng +9
Semi-supervised Learning (SSL) has witnessed great success owing to the impressive performances brought by various methods based on pseudo labeling and consistency regularization.…
Margin Calibration for Long-Tailed Visual Recognition
Yidong Wang, Bowen Zhang, Wenxin Hou +3
The long-tailed class distribution in visual recognition tasks poses great challenges for neural networks on how to handle the biased predictions between head and tail classes, i.e…
FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling
Bowen Zhang, Yidong Wang, Wenxin Hou +4
The recently proposed FixMatch achieved state-of-the-art results on most semi-supervised learning (SSL) benchmarks. However, like other modern SSL algorithms, FixMatch uses a pre-d…
Exploiting Adapters for Cross-lingual Low-resource Speech Recognition
Wenxin Hou, Han Zhu, Yidong Wang +4
Cross-lingual speech adaptation aims to solve the problem of leveraging multiple rich-resource languages to build models for a low-resource target language. Since the low-resource…
Cross-domain Speech Recognition with Unsupervised Character-level Distribution Matching
Wenxin Hou, Jindong Wang, Xu Tan +2
End-to-end automatic speech recognition (ASR) can achieve promising performance with large-scale training data. However, it is known that domain mismatch between training and testi…