Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended
Text Generation
Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended
Text Generation
Decoding from the output distributions of large language models to produce high-quality text is a complex challenge in language modeling. Various approaches, such as beam search, sampling with temperature, $k-$sampling, nucleus $p-$sampling, typical decoding, contrastive decoding, and contrastive search, have been proposed to address this problem, aiming to improve coherence, …