Generative retrieval models lose large amounts of accuracy under out-of-distribution queries and tasks in KILT experiments, showing their robustness needs improvement.
Advances in Neural Information Processing Systems 35, 31668–31683 (2022)
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On the Robustness of Generative Information Retrieval Models
Generative retrieval models lose large amounts of accuracy under out-of-distribution queries and tasks in KILT experiments, showing their robustness needs improvement.