64 citations · 76 across the 7 of their papers we have counts for
13 papers · 1 filter
Language Models Are Poor Learners of Directional Inference
Tianyi Li, Mohammad Javad Hosseini, Sabine Weber +1
We examine LMs' competence of directional predicate entailments by supervised fine-tuning with prompts. Our analysis shows that contrary to their apparent success on standard NLI,…
Cross-lingual Inference with A Chinese Entailment Graph
Tianyi Li, Sabine Weber, Mohammad Javad Hosseini +2
Predicate entailment detection is a crucial task for question-answering from text, where previous work has explored unsupervised learning of entailment graphs from typed open relat…
Cross-lingual Intermediate Fine-tuning improves Dialogue State Tracking
Nikita Moghe, Mark Steedman, Alexandra Birch
Recent progress in task-oriented neural dialogue systems is largely focused on a handful of languages, as annotation of training data is tedious and expensive. Machine translation…
Blindness to Modality Helps Entailment Graph Mining
Liane Guillou, Sander Bijl de Vroe, Mark Johnson +1
Understanding linguistic modality is widely seen as important for downstream tasks such as Question Answering and Knowledge Graph Population. Entailment Graph learning might also b…
Incorporating Temporal Information in Entailment Graph Mining
Liane Guillou, Sander Bijl de Vroe, Mohammad Javad Hosseini +2
We present a novel method for injecting temporality into entailment graphs to address the problem of spurious entailments, which may arise from similar but temporally distinct even…
Modality and Negation in Event Extraction
Sander Bijl de Vroe, Liane Guillou, Miloš Stanojević +2
Language provides speakers with a rich system of modality for expressing thoughts about events, without being committed to their actual occurrence. Modality is commonly used in the…