Jingjing Liu · PaperMetrix

InfoBERT: Improving Robustness of Language Models from An Information\n Theoretic Perspective

2020 · arXiv (Cornell University)

Large-scale language models such as BERT have achieved state-of-the-art\nperformance across a wide range of NLP tasks. Recent studies, however, show\nthat such BERT-based models are vulnerable facing the threats of textual\nadversarial attacks. We aim to address …

TVT: Transferable Vision Transformer for Unsupervised Domain Adaptation

2023 · 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

Unsupervised domain adaptation (UDA) aims to transfer the knowledge learnt from a labeled source domain to an unlabeled target domain. Previous work is mainly built upon convolutional neural networks (CNNs) to learn domain-invariant representations. With …

Refining Translations with Large Language Models: A Constraint-Aware Iterative Prompting Approach

2025 · Data Intelligence

Large Language Models (LLMs) have shown impressive capabilities in Machine Translation (MT), even when translating languages not specifically included in their training data. However, accurately translating rare words in lowresource or domain-specific contexts remains a …

Patient Knowledge Distillation for BERT Model Compression

2019

Siqi Sun, Yu Cheng, Zhe Gan, Jingjing Liu. Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). 2019.

DIALOGPT : Large-Scale Generative Pre-training for Conversational Response Generation

2020

Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, Bill Dolan. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations. 2020.

FreeLB: Enhanced Adversarial Training for Natural Language Understanding

2019 · arXiv (Cornell University)

Adversarial training, which minimizes the maximal risk for label-preserving input perturbations, has proved to be effective for improving the generalization of language models. In this work, we propose a novel adversarial training algorithm, FreeLB, that …

DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation