MASH: Modeling Abstention via Selective Help-Seeking
MASH：通过选择性求助进行模型退避建模
机构 * Department of Computer Science, Cornell University（康奈尔大学计算机科学系）
AI总结 本文提出MASH框架，通过强化学习实现LLM退避决策，提升多跳问答准确率7.6%，展示出优于传统方法的退避性能。
Comments 25 pages, with 15 dedicated to citations and appendix. 17 tables and 11 figures. Preprint, under review. Paper updated to reflect new title and results
