136 citations · 331 across the 18 of their papers we have counts for
7 papers · 1 filter
Target-Guided Dialogue Response Generation Using Commonsense and Data Augmentation
Prakhar Gupta, Harsh Jhamtani, Jeffrey P. Bigham
Target-guided response generation enables dialogue systems to smoothly transition a conversation from a dialogue context toward a target sentence. Such control is useful for design…
A Survey of NLP-Related Crowdsourcing HITs: what works and what does not
Jessica Huynh, Jeffrey Bigham, Maxine Eskenazi
Crowdsourcing requesters on Amazon Mechanical Turk (AMT) have raised questions about the reliability of the workers. The AMT workforce is very diverse and it is not possible to mak…
Does Pretraining for Summarization Require Knowledge Transfer?
Kundan Krishna, Jeffrey Bigham, Zachary C. Lipton
Pretraining techniques leveraging enormous datasets have driven recent advances in text summarization. While folk explanations suggest that knowledge transfer accounts for pretrain…
Synthesizing Adversarial Negative Responses for Robust Response Ranking and Evaluation
Prakhar Gupta, Yulia Tsvetkov, Jeffrey P. Bigham
Open-domain neural dialogue models have achieved high performance in response ranking and evaluation tasks. These tasks are formulated as a binary classification of responses given…
Controlling Dialogue Generation with Semantic Exemplars
Prakhar Gupta, Jeffrey P. Bigham, Yulia Tsvetkov +1
Dialogue systems pretrained with large language models generate locally coherent responses, but lack the fine-grained control over responses necessary to achieve specific goals. A…
Investigating Evaluation of Open-Domain Dialogue Systems With Human Generated Multiple References
Prakhar Gupta, Shikib Mehri, Tiancheng Zhao +3
The aim of this paper is to mitigate the shortcomings of automatic evaluation of open-domain dialog systems through multi-reference evaluation. Existing metrics have been shown to…