3 citations · 7 across the 4 of their papers we have counts for
5 papers
Revealing the Blind Spot of Sentence Encoder Evaluation by HEROS
Cheng-Han Chiang, Yung-Sung Chuang, James Glass +1
Existing sentence textual similarity benchmark datasets only use a single number to summarize how similar the sentence encoder's decision is to humans'. However, it is unclear what…
Re-Examining Human Annotations for Interpretable NLP
Cheng-Han Chiang, Hung-yi Lee
Explanation methods in Interpretable NLP often explain the model's decision by extracting evidence (rationale) from the input texts supporting the decision. Benchmark datasets for…
Understanding, Detecting, and Separating Out-of-Distribution Samples and Adversarial Samples in Text Classification
Cheng-Han Chiang, Hung-yi Lee
In this paper, we study the differences and commonalities between statistically out-of-distribution (OOD) samples and adversarial (Adv) samples, both of which hurting a text classi…
Pre-Training a Language Model Without Human Language
Cheng-Han Chiang, Hung-yi Lee
In this paper, we study how the intrinsic nature of pre-training data contributes to the fine-tuned downstream performance. To this end, we pre-train different transformer-based ma…
Pretrained Language Model Embryology: The Birth of ALBERT
Cheng-Han Chiang, Sung-Feng Huang, Hung-yi Lee
While behaviors of pretrained language models (LMs) have been thoroughly examined, what happened during pretraining is rarely studied. We thus investigate the developmental process…