Zhaojiang Lin

Hierarchical Meta-Embeddings for Code-Switching Named Entity Recognition

2019

Genta Indra Winata, Zhaojiang Lin, Jamin Shin, Zihan Liu, Pascale Fung. 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.

MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems

2020 · arXiv (Cornell University)

In this paper, we propose Minimalist Transfer Learning (MinTL) to simplify the system design process of task-oriented dialogue systems and alleviate the over-dependency on annotated data. MinTL is a simple yet effective transfer learning framework, …

Plug-and-Play Conversational Models

2020

There has been considerable progress made towards conversational models that generate coherent and fluent responses; however, this often involves training large language models on large dialogue datasets, such as Reddit. These large conversational models provide …

Learning Multilingual Meta-Embeddings for Code-Switching Named Entity Recognition

2019

In this paper, we propose Multilingual Meta-Embeddings (MME), an effective method to learn multilingual representations by leveraging monolingual pre-trained embeddings. MME learns to utilize information from these embeddings via a self-attention mechanism without explicit language …

Exploring Versatile Generative Language Model Via Parameter-Efficient Transfer Learning

2020

Fine-tuning pre-trained generative language models to down-stream language generation tasks has shown promising results. However, this comes with the cost of having a single, large model for each task, which is not ideal in low-memory/power …