3 papers
cs.CL2020
Why do you think that? Exploring Faithful Sentence-Level Rationales Without Supervision
Max Glockner, Ivan Habernal, Iryna Gurevych
Evaluating the trustworthiness of a model's prediction is essential for differentiating between `right for the right reasons' and `right for the wrong reasons'. Identifying textual…
cs.LG2020
AdapterDrop: On the Efficiency of Adapters in Transformers
Andreas Rücklé, Gregor Geigle, Max Glockner +4
Massively pre-trained transformer models are computationally expensive to fine-tune, slow for inference, and have large storage requirements. Recent approaches tackle these shortco…
cs.CL2018
Breaking NLI Systems with Sentences that Require Simple Lexical Inferences
Max Glockner, Vered Shwartz, Yoav Goldberg
We create a new NLI test set that shows the deficiency of state-of-the-art models in inferences that require lexical and world knowledge. The new examples are simpler than the SNLI…