62 citations · 124 across the 17 of their papers we have counts for
9 papers · 1 filter
EnCBP: A New Benchmark Dataset for Finer-Grained Cultural Background Prediction in English
Weicheng Ma, Samiha Datta, Lili Wang +1
While cultural backgrounds have been shown to affect linguistic expressions, existing natural language processing (NLP) research on culture modeling is overly coarse-grained and do…
Contributions of Transformer Attention Heads in Multi- and Cross-lingual Tasks
Weicheng Ma, Kai Zhang, Renze Lou +2
This paper studies the relative importance of attention heads in Transformer-based models to aid their interpretability in cross-lingual and multi-lingual tasks. Prior research has…
Mitigating Political Bias in Language Models Through Reinforced Calibration
Ruibo Liu, Chenyan Jia, Jason Wei +3
Current large-scale language models can be politically biased as a result of the data they are trained on, potentially causing serious problems when they are deployed in real-world…
Political Depolarization of News Articles Using Attribute-aware Word Embeddings
Ruibo Liu, Lili Wang, Chenyan Jia +1
Political polarization in the US is on the rise. This polarization negatively affects the public sphere by contributing to the creation of ideological echo chambers. In this paper,…
Improvements and Extensions on Metaphor Detection
Weicheng Ma, Ruibo Liu, Lili Wang +1
Metaphors are ubiquitous in human language. The metaphor detection task (MD) aims at detecting and interpreting metaphors from written language, which is crucial in natural languag…
An Empirical Survey of Unsupervised Text Representation Methods on Twitter Data
Lili Wang, Chongyang Gao, Jason Wei +3
The field of NLP has seen unprecedented achievements in recent years. Most notably, with the advent of large-scale pre-trained Transformer-based language models, such as BERT, ther…
Data Boost: Text Data Augmentation Through Reinforcement Learning Guided Conditional Generation
Ruibo Liu, Guangxuan Xu, Chenyan Jia +3
Data augmentation is proven to be effective in many NLU tasks, especially for those suffering from data scarcity. In this paper, we present a powerful and easy to deploy text augme…
Towards Improved Model Design for Authorship Identification: A Survey on Writing Style Understanding
Weicheng Ma, Ruibo Liu, Lili Wang +1
Authorship identification tasks, which rely heavily on linguistic styles, have always been an important part of Natural Language Understanding (NLU) research. While other tasks bas…
Emoji Prediction: Extensions and Benchmarking
Weicheng Ma, Ruibo Liu, Lili Wang +1
Emojis are a succinct form of language which can express concrete meanings, emotions, and intentions. Emojis also carry signals that can be used to better understand communicative…