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Training LLMs on incorrect outputs can yield better reasoning performance than focusing solely on correct ones, challenging conventional wisdom in model distillation.
Unlock a 6x boost in hit rates for novel anti-cancer agents by infusing chemical structures with biological insights, even without biological data at inference time.