Chao Shen


2023

pdf
CoCo: Coherence-Enhanced Machine-Generated Text Detection Under Low Resource With Contrastive Learning
Xiaoming Liu | Zhaohan Zhang | Yichen Wang | Hang Pu | Yu Lan | Chao Shen
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Machine-Generated Text (MGT) detection, a task that discriminates MGT from Human-Written Text (HWT), plays a crucial role in preventing misuse of text generative models, which excel in mimicking human writing style recently. Latest proposed detectors usually take coarse text sequences as input and fine-tune pretrained models with standard cross-entropy loss. However, these methods fail to consider the linguistic structure of texts. Moreover, they lack the ability to handle the low-resource problem which could often happen in practice considering the enormous amount of textual data online. In this paper, we present a coherence-based contrastive learning model named CoCo to detect the possible MGT under low-resource scenario. To exploit the linguistic feature, we encode coherence information in form of graph into text representation. To tackle the challenges of low data resource, we employ a contrastive learning framework and propose an improved contrastive loss for preventing performance degradation brought by simple samples. The experiment results on two public datasets and two self-constructed datasets prove our approach outperforms the state-of-art methods significantly. Also, we surprisingly find that MGTs originated from up-to-date language models could be easier to detect than these from previous models, in our experiments. And we propose some preliminary explanations for this counter-intuitive phenomena. All the codes and datasets are open-sourced.

2013

pdf
A Participant-based Approach for Event Summarization Using Twitter Streams
Chao Shen | Fei Liu | Fuliang Weng | Tao Li
Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

2011

pdf
A Non-negative Matrix Factorization Based Approach for Active Dual Supervision from Document and Word Labels
Chao Shen | Tao Li
Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing

2010

pdf
Multi-Document Summarization via the Minimum Dominating Set
Chao Shen | Tao Li
Proceedings of the 23rd International Conference on Computational Linguistics (Coling 2010)