64 citations · 131 across the 11 of their papers we have counts for
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cs.CL2023
Recipes for Sequential Pre-training of Multilingual Encoder and Seq2Seq Models
Saleh Soltan, Andy Rosenbaum, Tobias Falke +3
Pre-trained encoder-only and sequence-to-sequence (seq2seq) models each have advantages, however training both model types from scratch is computationally expensive. We explore rec…
cs.CL2023★ 3 cited
PLACES: Prompting Language Models for Social Conversation Synthesis
Maximillian Chen, Alexandros Papangelis, Chenyang Tao +5
Collecting high quality conversational data can be very expensive for most applications and infeasible for others due to privacy, ethical, or similar concerns. A promising directio…