no code implementations • 14 Feb 2024 • Minho Lee, Junghyun Min, Woochul Lee, Yeonsoo Lee
Previous work in structured prediction (e. g. NER, information extraction) using single model make use of explicit dataset information, which helps boost in-distribution performance but is orthogonal to robust generalization in real-world situations.
no code implementations • 13 Feb 2024 • Junghyun Min, Minho Lee, Woochul Lee, Yeonsoo Lee
Unsupervised learning objectives like language modeling and de-noising constitute a significant part in producing pre-trained models that perform various downstream applications from natural language understanding to conversational tasks.
1 code implementation • ACL 2020 • Junghyun Min, R. Thomas McCoy, Dipanjan Das, Emily Pitler, Tal Linzen
Pretrained neural models such as BERT, when fine-tuned to perform natural language inference (NLI), often show high accuracy on standard datasets, but display a surprising lack of sensitivity to word order on controlled challenge sets.
1 code implementation • EMNLP (BlackboxNLP) 2020 • R. Thomas McCoy, Junghyun Min, Tal Linzen
If the same neural network architecture is trained multiple times on the same dataset, will it make similar linguistic generalizations across runs?