2 citations · 3 across the 3 of their papers we have counts for
4 papers
NLI Data Sanity Check: Assessing the Effect of Data Corruption on Model Performance
Aarne Talman, Marianna Apidianaki, Stergios Chatzikyriakidis +1
Pre-trained neural language models give high performance on natural language inference (NLI) tasks. But whether they actually understand the meaning of the processed sequences rema…
FraCaS: Temporal Analysis
Jean-Philippe Bernardy, Stergios Chatzikyriakidis
In this paper, we propose an implementation of temporal semantics which is suitable for inference problems. This implementation translates syntax trees to logical formulas, suitabl…
A corpus of precise natural textual entailment problems
Jean-Philippe Bernardy, Stergios Chatzikyriakidis
In this paper, we present a new corpus of entailment problems. This corpus combines the following characteristics: 1. it is precise (does not leave out implicit hypotheses) 2. it i…
Testing the Generalization Power of Neural Network Models Across NLI Benchmarks
Aarne Talman, Stergios Chatzikyriakidis
Neural network models have been very successful in natural language inference, with the best models reaching 90% accuracy in some benchmarks. However, the success of these models t…