14 citations · 16 across the 3 of their papers we have counts for
6 papers · 1 filter
Dynatask: A Framework for Creating Dynamic AI Benchmark Tasks
Tristan Thrush, Kushal Tirumala, Anmol Gupta +7
We introduce Dynatask: an open source system for setting up custom NLP tasks that aims to greatly lower the technical knowledge and effort required for hosting and evaluating state…
Contrasting Human- and Machine-Generated Word-Level Adversarial Examples for Text Classification
Maximilian Mozes, Max Bartolo, Pontus Stenetorp +2
Research shows that natural language processing models are generally considered to be vulnerable to adversarial attacks; but recent work has drawn attention to the issue of validat…
Dynabench: Rethinking Benchmarking in NLP
Douwe Kiela, Max Bartolo, Yixin Nie +16
We introduce Dynabench, an open-source platform for dynamic dataset creation and model benchmarking. Dynabench runs in a web browser and supports human-and-model-in-the-loop datase…
Undersensitivity in Neural Reading Comprehension
Johannes Welbl, Pasquale Minervini, Max Bartolo +2
Current reading comprehension models generalise well to in-distribution test sets, yet perform poorly on adversarially selected inputs. Most prior work on adversarial inputs studie…
Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension
Max Bartolo, Alastair Roberts, Johannes Welbl +2
Innovations in annotation methodology have been a catalyst for Reading Comprehension (RC) datasets and models. One recent trend to challenge current RC models is to involve a model…
Interpretation of Natural Language Rules in Conversational Machine Reading
Marzieh Saeidi, Max Bartolo, Patrick Lewis +5
Most work in machine reading focuses on question answering problems where the answer is directly expressed in the text to read. However, many real-world question answering problems…