Search Results for author: Mengzhou Xia

Found 9 papers, 6 papers with code

Structured Pruning Learns Compact and Accurate Models

1 code implementation ACL 2022 Mengzhou Xia, Zexuan Zhong, Danqi Chen

The growing size of neural language models has led to increased attention in model compression.

Model Compression

Non-Parametric Few-Shot Learning for Word Sense Disambiguation

1 code implementation NAACL 2021 Howard Chen, Mengzhou Xia, Danqi Chen

One significant challenge in supervised all-words WSD is to classify among senses for a majority of words that lie in the long-tail distribution.

Few-Shot Learning Word Sense Disambiguation

MetaXL: Meta Representation Transformation for Low-resource Cross-lingual Learning

1 code implementation NAACL 2021 Mengzhou Xia, Guoqing Zheng, Subhabrata Mukherjee, Milad Shokouhi, Graham Neubig, Ahmed Hassan Awadallah

Extensive experiments on real-world low-resource languages - without access to large-scale monolingual corpora or large amounts of labeled data - for tasks like cross-lingual sentiment analysis and named entity recognition show the effectiveness of our approach.

Cross-Lingual Transfer Meta-Learning +3

Demoting Racial Bias in Hate Speech Detection

no code implementations WS 2020 Mengzhou Xia, Anjalie Field, Yulia Tsvetkov

In current hate speech datasets, there exists a high correlation between annotators' perceptions of toxicity and signals of African American English (AAE).

Hate Speech Detection

Predicting Performance for Natural Language Processing Tasks

1 code implementation ACL 2020 Mengzhou Xia, Antonios Anastasopoulos, Ruochen Xu, Yiming Yang, Graham Neubig

Given the complexity of combinations of tasks, languages, and domains in natural language processing (NLP) research, it is computationally prohibitive to exhaustively test newly proposed models on each possible experimental setting.

Generalized Data Augmentation for Low-Resource Translation

no code implementations ACL 2019 Mengzhou Xia, Xiang Kong, Antonios Anastasopoulos, Graham Neubig

Translation to or from low-resource languages LRLs poses challenges for machine translation in terms of both adequacy and fluency.

Data Augmentation Translation +1

Choosing Transfer Languages for Cross-Lingual Learning

1 code implementation ACL 2019 Yu-Hsiang Lin, Chian-Yu Chen, Jean Lee, Zirui Li, Yuyan Zhang, Mengzhou Xia, Shruti Rijhwani, Junxian He, Zhisong Zhang, Xuezhe Ma, Antonios Anastasopoulos, Patrick Littell, Graham Neubig

Cross-lingual transfer, where a high-resource transfer language is used to improve the accuracy of a low-resource task language, is now an invaluable tool for improving performance of natural language processing (NLP) on low-resource languages.

Cross-Lingual Transfer

Cannot find the paper you are looking for? You can Submit a new open access paper.