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Making state-of-the-art generalisation testing the new status-quo in NLP
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GenBench Skip to primary navigation Skip to content Skip to footer Home The taxonomy Visual exploration Get references Eval Cards Workshop Collaborative benchmarking task Contribute Team Toggle menu GenBench Making state-of-the-art generalisation testing the new status-quo in NLP The ability to generalise is one of the primary desiderata of natural language processing (NLP). Yet, how "good generalisation" should be defined and evaluated is not well understood, nor are there common standards to evaluate generalisation. As a consequence, newly proposed models are usually not systematically tested for their ability to generalise. GenBench 's mission is to make state-of-the-art generalisation testing the new status-quo in NLP. As a first step, we present a generalisation taxonomy , describing the underlying building blocks of generalisation in NLP. We use the taxonomy to do an elaborate review of over 400 generali...
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