Soft Reasoning improves LLM accuracy on reasoning benchmarks by perturbing the embedding of the first generated token and searching the perturbation space with Bayesian optimization guided by the model's own verifier.
So, 1 liter of seawater has 20%×1 liter = ⟨⟨20×0.1 = 0.2⟩⟩0.2 liters of salt
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Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration
Soft Reasoning improves LLM accuracy on reasoning benchmarks by perturbing the embedding of the first generated token and searching the perturbation space with Bayesian optimization guided by the model's own verifier.