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All SourcesarXiv
#training-free methods

Scalable Power Sampling: Unlocking Efficient, Training-Free Reasoning for LLMs via Distribution Sharpening

Intermediate
Xiaotong Ji, Rasul Tutunov et al.Jan 29arXiv

The paper shows a fast, training-free way to boost an LLM’s step-by-step reasoning by smartly reusing the model’s own probabilities.

#power distribution sampling#distribution sharpening#low-temperature sampling

VOYAGER: A Training Free Approach for Generating Diverse Datasets using LLMs

Intermediate
Avinash Amballa, Yashas Malur Saidutta et al.Dec 12arXiv

VOYAGER is a training-free way to make large language models (LLMs) create data that is truly different, not just slightly reworded.

#VOYAGER#determinantal point process#dataset diversity