Parth Asawa presents continual learning benchmark with 'gain' metric
UC Berkeley's Parth Asawa critiques static leaderboards that test models on isolated tasks, proposing a benchmark that measures continual learning via a 'gain' metric. The talk was given at AI Engineer.
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