32 citations · 46 across the 11 of their papers we have counts for
11 papers
How to Describe Images in a More Funny Way? Towards a Modular Approach to Cross-Modal Sarcasm Generation
Jie Ruan, Yue Wu, Xiaojun Wan +1
Sarcasm generation has been investigated in previous studies by considering it as a text-to-text generation problem, i.e., generating a sarcastic sentence for an input sentence. In…
Social Biases in Automatic Evaluation Metrics for NLG
Mingqi Gao, Xiaojun Wan
Many studies have revealed that word embeddings, language models, and models for specific downstream tasks in NLP are prone to social biases, especially gender bias. Recently these…
An Empirical Study of Automatic Post-Editing
Xu Zhang, Xiaojun Wan
Automatic post-editing (APE) aims to reduce manual post-editing efforts by automatically correcting errors in machine-translated output. Due to the limited amount of human-annotate…
Nearest Neighbor Knowledge Distillation for Neural Machine Translation
Zhixian Yang, Renliang Sun, Xiaojun Wan
k-nearest-neighbor machine translation (NN-MT), proposed by Khandelwal et al. (2021), has achieved many state-of-the-art results in machine translation tasks. Although effective, N…
SimpleBERT: A Pre-trained Model That Learns to Generate Simple Words
Renliang Sun, Xiaojun Wan
Pre-trained models are widely used in the tasks of natural language processing nowadays. However, in the specific field of text simplification, the research on improving pre-traine…
Dependency-based Mixture Language Models
Zhixian Yang, Xiaojun Wan
Various models have been proposed to incorporate knowledge of syntactic structures into neural language models. However, previous works have relied heavily on elaborate components…