25 citations · 67 across the 43 of their papers we have counts for
4 papers · 1 filter
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning
Prasetya Ajie Utama, Nafise Sadat Moosavi, Victor Sanh +1
Recent prompt-based approaches allow pretrained language models to achieve strong performances on few-shot finetuning by reformulating downstream tasks as a language modeling probl…
Learning to Reason for Text Generation from Scientific Tables
Nafise Sadat Moosavi, Andreas Rücklé, Dan Roth +1
In this paper, we introduce SciGen, a new challenge dataset for the task of reasoning-aware data-to-text generation consisting of tables from scientific articles and their correspo…
Stay Together: A System for Single and Split-antecedent Anaphora Resolution
Juntao Yu, Nafise Sadat Moosavi, Silviu Paun +1
The state-of-the-art on basic, single-antecedent anaphora has greatly improved in recent years. Researchers have therefore started to pay more attention to more complex cases of an…