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Explore the impact of coordinated evaluations in natural language processing research through this insightful talk by Jonathan May. Delve into the world of bake-offs, shared tasks, and evaluations, examining their role in exposing algorithms and models to unseen data. Discover how these high-stress periods, often criticized for metrics, procedures, and score-chasing, can actually benefit NLP research and lead to significant accomplishments. Gain valuable insights into recent evaluation-grounded work, including rapid generation of translation and information extraction for low-resource surprise languages (DARPA LORELEI) and the organization of SemEval shared tasks in semantic parsing and generation. Learn from May's extensive experience as a Research Assistant Professor at USC's Information Sciences Institute and his previous roles at SDL Research and Raytheon BBN Technologies.
