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Discarding irrelevant reasoning tokens can make language models up to 3x faster at test time without sacrificing performance.
LLMs may outperform embedding models in reasoning, but the cost difference is staggering鈥攗p to 1,431 times more expensive for marginal gains.
Training domain-specific coding LLMs with realistic environments and large-scale RL can yield substantial gains in practical software engineering tasks.
