38 citations · 122 across the 17 of their papers we have counts for
24 papers
Uncertainty Calibration for Ensemble-Based Debiasing Methods
Ruibin Xiong, Yimeng Chen, Liang Pang +2
Ensemble-based debiasing methods have been shown effective in mitigating the reliance of classifiers on specific dataset bias, by exploiting the output of a bias-only model to adju…
Transductive Learning for Unsupervised Text Style Transfer
Fei Xiao, Liang Pang, Yanyan Lan +3
Unsupervised style transfer models are mainly based on an inductive learning approach, which represents the style as embeddings, decoder parameters, or discriminator parameters and…
Adaptive Information Seeking for Open-Domain Question Answering
Yunchang Zhu, Liang Pang, Yanyan Lan +2
Information seeking is an essential step for open-domain question answering to efficiently gather evidence from a large corpus. Recently, iterative approaches have been proven to b…
Toward the Understanding of Deep Text Matching Models for Information Retrieval
Lijuan Chen, Yanyan Lan, Liang Pang +2
Semantic text matching is a critical problem in information retrieval. Recently, deep learning techniques have been widely used in this area and obtained significant performance im…
Modeling Relevance Ranking under the Pre-training and Fine-tuning Paradigm
Lin Bo, Liang Pang, Gang Wang +3
Recently, pre-trained language models such as BERT have been applied to document ranking for information retrieval, which first pre-train a general language model on an unlabeled l…
Sketch and Customize: A Counterfactual Story Generator
Changying Hao, Liang Pang, Yanyan Lan +3
Recent text generation models are easy to generate relevant and fluent text for the given text, while lack of causal reasoning ability when we change some parts of the given text.…