2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CL2023
Critic-Driven Decoding for Mitigating Hallucinations in Data-to-text Generation
Mateusz Lango, Ondřej Dušek
Hallucination of text ungrounded in the input is a well-known problem in neural data-to-text generation. Many methods have been proposed to mitigate it, but they typically require…
cs.CL2023
With a Little Help from the Authors: Reproducing Human Evaluation of an MT Error Detector
Ondřej Plátek, Mateusz Lango, Ondřej Dušek
This work presents our efforts to reproduce the results of the human evaluation experiment presented in the paper of Vamvas and Sennrich (2022), which evaluated an automatic system…
cs.CL2023★ 2 cited
Three Ways of Using Large Language Models to Evaluate Chat
Ondřej Plátek, Vojtěch Hudeček, Patricia Schmidtová +2
This paper describes the systems submitted by team6 for ChatEval, the DSTC 11 Track 4 competition. We present three different approaches to predicting turn-level qualities of chatb…