Paper accepted to EMNLP findings

Our paper “GUARD: Glocal Uncertainty-Aware Robust Decoding for Effective and Efficient Open-Ended Text Generation” has been accepted to the findings track of the (A*) conference on Empirical Methods in Natural Language Processing (EMNLP).

This was a huge team effort! Congratulations and a heartfelt Thank you go to Yuanhao Ding, Esteban Garces Arias, Meimingwei Li, Matthias Aßenmacher, Danlu Chen, Gaojuan Fan, Christian Heumann, and Chongsheng Zhang