2 citations · 4 across the 4 of their papers we have counts for
5 papers
Graph Attention with Hierarchies for Multi-hop Question Answering
Yunjie He, Philip John Gorinski, Ieva Staliunaite +1
Multi-hop QA (Question Answering) is the task of finding the answer to a question across multiple documents. In recent years, a number of Deep Learning-based approaches have been p…
Relational Graph Convolutional Neural Networks for Multihop Reasoning: A Comparative Study
Ieva Staliūnaitė, Philip John Gorinski, Ignacio Iacobacci
Multihop Question Answering is a complex Natural Language Processing task that requires multiple steps of reasoning to find the correct answer to a given question. Previous researc…
AmbiFC: Fact-Checking Ambiguous Claims with Evidence
Max Glockner, Ieva Staliūnaitė, James Thorne +3
Automated fact-checking systems verify claims against evidence to predict their veracity. In real-world scenarios, the retrieved evidence may not unambiguously support or refute th…
Improving Commonsense Causal Reasoning by Adversarial Training and Data Augmentation
Ieva Staliūnaitė, Philip John Gorinski, Ignacio Iacobacci
Determining the plausibility of causal relations between clauses is a commonsense reasoning task that requires complex inference ability. The general approach to this task is to tr…
Compositional and Lexical Semantics in RoBERTa, BERT and DistilBERT: A Case Study on CoQA
Ieva Staliūnaitė, Ignacio Iacobacci
Many NLP tasks have benefited from transferring knowledge from contextualized word embeddings, however the picture of what type of knowledge is transferred is incomplete. This pape…