Gacha Decoding is claimed to beat prior work by over 11x in sample efficiency for diverse AI responses

The Gacha Decoding announcement claims the method produces varied language-model responses with over 11x the sample efficiency of prior work. It says the approach draws on instruction following and external random-number generation rather than token entropy, and suggests using it to generate varied ideas, data and reinforcement-learning environments.