71 citations · 102 across the 10 of their papers we have counts for
5 papers · 1 filter
InferES : A Natural Language Inference Corpus for Spanish Featuring Negation-Based Contrastive and Adversarial Examples
Venelin Kovatchev, Mariona Taulé
In this paper, we present InferES - an original corpus for Natural Language Inference (NLI) in European Spanish. We propose, implement, and analyze a variety of corpus-creating str…
Paraphrasing, textual entailment, and semantic similarity above word level
Venelin Kovatchev
This dissertation explores the linguistic and computational aspects of the meaning relations that can hold between two or more complex linguistic expressions (phrases, clauses, sen…
longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks
Venelin Kovatchev, Trina Chatterjee, Venkata S Govindarajan +9
Developing methods to adversarially challenge NLP systems is a promising avenue for improving both model performance and interpretability. Here, we describe the approach of the tea…
ProtoTEx: Explaining Model Decisions with Prototype Tensors
Anubrata Das, Chitrank Gupta, Venelin Kovatchev +2
We present ProtoTEx, a novel white-box NLP classification architecture based on prototype networks. ProtoTEx faithfully explains model decisions based on prototype tensors that enc…
Finding Pareto Trade-offs in Fair and Accurate Detection of Toxic Speech
Soumyajit Gupta, Venelin Kovatchev, Anubrata Das +2
Optimizing NLP models for fairness poses many challenges. Lack of differentiable fairness measures prevents gradient-based loss training or requires surrogate losses that diverge f…