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cs.CL2024
Measuring the Groundedness of Legal Question-Answering Systems
Dietrich Trautmann, Natalia Ostapuk, Quentin Grail +4
In high-stakes domains like legal question-answering, the accuracy and trustworthiness of generative AI systems are of paramount importance. This work presents a comprehensive benc…
cs.CL2018
ReviewQA: a relational aspect-based opinion reading dataset
Quentin Grail, Julien Perez
Deep reading models for question-answering have demonstrated promising performance over the last couple of years. However current systems tend to learn how to cleverly extract a sp…