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CollabEval slashes evaluation uncertainty, achieving more accurate model assessments with less data by exploiting historical performance correlations.
Unlock granular leaderboards and precise model evaluations with a novel tensor factorization technique that slashes the need for costly human annotations by smartly leveraging cheap autorater data.
