Haokun Liu

Git-Theta: A Git Extension for Collaborative Development of Machine Learning Models

2023 · arXiv (Cornell University)

Currently, most machine learning models are trained by centralized teams and are rarely updated. In contrast, open-source software development involves the iterative development of a shared artifact through distributed collaboration using a version control system. …

BLiMP: The Benchmark of Linguistic Minimal Pairs for English (Electronic Resources)

2020 · Faculty Digital Archive (New York University Florence)

We introduce The Benchmark of Linguistic Minimal Pairs (BLiMP),1 a challenge set for evaluating the linguistic knowledge of language models (LMs) on major grammatical phenomena in English. BLiMP consists of 67 individual datasets, each containing …

Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work?

2020 · arXiv (Cornell University)

While pretrained models such as BERT have shown large gains across natural language understanding tasks, their performance can be improved by further training the model on a data-rich intermediate task, before fine-tuning it on a …

Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?

2020

Yada Pruksachatkun, Jason Phang, Haokun Liu, Phu Mon Htut, Xiaoyi Zhang, Richard Yuanzhe Pang, Clara Vania, Katharina Kann, Samuel R. Bowman. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. 2020.