24 citations · 40 across the 5 of their papers we have counts for
5 papers
Report from the NSF Future Directions Workshop on Automatic Evaluation of Dialog: Research Directions and Challenges
Shikib Mehri, Jinho Choi, Luis Fernando D'Haro +13
This is a report on the NSF Future Directions Workshop on Automatic Evaluation of Dialog. The workshop explored the current state of the art along with its limitations and suggeste…
MDD-Eval: Self-Training on Augmented Data for Multi-Domain Dialogue Evaluation
Chen Zhang, Luis Fernando D'Haro, Thomas Friedrichs +1
Chatbots are designed to carry out human-like conversations across different domains, such as general chit-chat, knowledge exchange, and persona-grounded conversations. To measure…
Investigating the Impact of Pre-trained Language Models on Dialog Evaluation
Chen Zhang, Luis Fernando D'Haro, Yiming Chen +2
Recently, there is a surge of interest in applying pre-trained language models (Pr-LM) in automatic open-domain dialog evaluation. Pr-LMs offer a promising direction for addressing…
Revisiting Self-Training for Few-Shot Learning of Language Model
Yiming Chen, Yan Zhang, Chen Zhang +3
As unlabeled data carry rich task-relevant information, they are proven useful for few-shot learning of language model. The question is how to effectively make use of such data. In…
DynaEval: Unifying Turn and Dialogue Level Evaluation
Chen Zhang, Yiming Chen, Luis Fernando D'Haro +4
A dialogue is essentially a multi-turn interaction among interlocutors. Effective evaluation metrics should reflect the dynamics of such interaction. Existing automatic metrics are…