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Dynamic language understanding: adaptation to new knowledge in parametric and semi-parametric models

Many recent successes in language models (LMs) have been achieved within a ‘static paradigm’, where the focus is on improving performance on the benchmarks that are created without considering the temporal aspect of data. For instance, answering questions on events that the model could learn about during training, or evaluating on text sub-sampled from the…

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