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Stanford NLP announces that a linguistics-informed NLP paper titled 'The Imperfective Paradox in LLMs' has won a Best Paper Award at ACL 2026, encouraging more detailed linguistic evaluation of large language models.
BLASST, a training-free dynamic sparse attention mechanism using a single scalar threshold on online softmax statistics, won Best Paper at MLSys26. It achieves speedups of 1.52x for prefill and 1.48x for decode with over 70% sparsity while preserving accuracy.