53 citations · 84 across the 7 of their papers we have counts for
9 papers · 1 filter
Evaluating Parameter Efficient Learning for Generation
Peng Xu, Mostofa Patwary, Shrimai Prabhumoye +6
Parameter efficient learning methods (PERMs) have recently gained significant attention as they provide an efficient way for pre-trained language models (PLMs) to adapt to a downst…
Multi-Stage Prompting for Knowledgeable Dialogue Generation
Zihan Liu, Mostofa Patwary, Ryan Prenger +4
Existing knowledge-grounded dialogue systems typically use finetuned versions of a pretrained language model (LM) and large-scale knowledge bases. These models typically fail to ge…
End-to-End Training of Neural Retrievers for Open-Domain Question Answering
Devendra Singh Sachan, Mostofa Patwary, Mohammad Shoeybi +4
Recent work on training neural retrievers for open-domain question answering (OpenQA) has employed both supervised and unsupervised approaches. However, it remains unclear how unsu…
Local Knowledge Powered Conversational Agents
Sashank Santhanam, Wei Ping, Raul Puri +3
State-of-the-art conversational agents have advanced significantly in conjunction with the use of large transformer-based language models. However, even with these advancements, co…
Multi-Speaker End-to-End Speech Synthesis
Jihyun Park, Kexin Zhao, Kainan Peng +1
In this work, we extend ClariNet (Ping et al., 2019), a fully end-to-end speech synthesis model (i.e., text-to-wave), to generate high-fidelity speech from multiple speakers. To mo…
Non-Autoregressive Neural Text-to-Speech
Kainan Peng, Wei Ping, Zhao Song +1
In this work, we propose ParaNet, a non-autoregressive seq2seq model that converts text to spectrogram. It is fully convolutional and brings 46.7 times speed-up over the lightweigh…