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CritICL consistently outperforms standard in-context learning and achieves performance competitive with or superior to test-time scaling methods while requiring significantly fewer generations and lower token cost

Experimental results show that CritICL consistently outperforms standard in-context learning and achieves performance competitive with or superior to test-time scaling methods, while requiring significantly fewer generations and lower token cost
Computation and Language30 Aug 2026

http://arxiv.org/abs/2608.27455v1