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Found 3 papers, 1 papers with code
PathFinder: Guided Search over Multi-Step Reasoning Paths
Using constrained reasoning, PathFinder integrates novel quality constraints, pruning, and exploration methods to enhance the efficiency and the quality of generation.
Contrastive Decoding Improves Reasoning in Large Language Models
We demonstrate that Contrastive Decoding -- a simple, computationally light, and training-free text generation method proposed by Li et al 2022 -- achieves large out-of-the-box improvements over greedy decoding on a variety of reasoning tasks.
Shepherd: A Critic for Language Model Generation
As large language models improve, there is increasing interest in techniques that leverage these models' capabilities to refine their own outputs.
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