26 citations · 42 across the 7 of their papers we have counts for
8 papers
Falsesum: Generating Document-level NLI Examples for Recognizing Factual Inconsistency in Summarization
Prasetya Ajie Utama, Joshua Bambrick, Nafise Sadat Moosavi +1
Neural abstractive summarization models are prone to generate summaries which are factually inconsistent with their source documents. Previous work has introduced the task of recog…
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…
Improving Robustness by Augmenting Training Sentences with Predicate-Argument Structures
Nafise Sadat Moosavi, Marcel de Boer, Prasetya Ajie Utama +1
Existing NLP datasets contain various biases, and models tend to quickly learn those biases, which in turn limits their robustness. Existing approaches to improve robustness agains…
Towards Debiasing NLU Models from Unknown Biases
Prasetya Ajie Utama, Nafise Sadat Moosavi, Iryna Gurevych
NLU models often exploit biases to achieve high dataset-specific performance without properly learning the intended task. Recently proposed debiasing methods are shown to be effect…
Mind the Trade-off: Debiasing NLU Models without Degrading the In-distribution Performance
Prasetya Ajie Utama, Nafise Sadat Moosavi, Iryna Gurevych
Models for natural language understanding (NLU) tasks often rely on the idiosyncratic biases of the dataset, which make them brittle against test cases outside the training distrib…
Improving Generalization by Incorporating Coverage in Natural Language Inference
Nafise Sadat Moosavi, Prasetya Ajie Utama, Andreas Rücklé +1
The task of natural language inference (NLI) is to identify the relation between the given premise and hypothesis. While recent NLI models achieve very high performance on individu…
DBPal: Weak Supervision for Learning a Natural Language Interface to Databases
Nathaniel Weir, Andrew Crotty, Alex Galakatos +9
This paper describes DBPal, a new system to translate natural language utterances into SQL statements using a neural machine translation model. While other recent approaches use ne…
An End-to-end Neural Natural Language Interface for Databases
Prasetya Utama, Nathaniel Weir, Fuat Basik +6
The ability to extract insights from new data sets is critical for decision making. Visual interactive tools play an important role in data exploration since they provide non-techn…