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cs.CL2022
Looking at the Overlooked: An Analysis on the Word-Overlap Bias in Natural Language Inference
Sara Rajaee, Yadollah Yaghoobzadeh, Mohammad Taher Pilehvar
It has been shown that NLI models are usually biased with respect to the word-overlap between premise and hypothesis; they take this feature as a primary cue for predicting the ent…
cs.CL2022
On the Importance of Data Size in Probing Fine-tuned Models
Houman Mehrafarin, Sara Rajaee, Mohammad Taher Pilehvar
Several studies have investigated the reasons behind the effectiveness of fine-tuning, usually through the lens of probing. However, these studies often neglect the role of the siz…