Papers by Valerio Pascucci

1 papers
Visual Interrogation of Attention-Based Models for Natural Language Inference and Machine Comprehension (D18-2)

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Challenge: Neural networks models have gained popularity due to their state-of-the-art performance but lack of interpretability hinders their deployment and refinement.
Approach: They propose a visual analytic library that provides a user with a customizable visual anallytic environment.
Outcome: The proposed visualization library provides an interactive environment in which the user can investigate and interrogate the relationships between input, model internals and output predictions.

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