26 citations · 26 across the 3 of their papers we have counts for
3 papers
cs.CL2023
Few-shot Unified Question Answering: Tuning Models or Prompts?
Srijan Bansal, Semih Yavuz, Bo Pang +2
Question-answering (QA) tasks often investigate specific question types, knowledge domains, or reasoning skills, leading to specialized models catering to specific categories of QA…
cs.CL2022
Improving the Faithfulness of Abstractive Summarization via Entity Coverage Control
Haopeng Zhang, Semih Yavuz, Wojciech Kryscinski +2
Abstractive summarization systems leveraging pre-training language models have achieved superior results on benchmark datasets. However, such models have been shown to be more pron…
stat.ML2014★ 26 cited
Is Joint Training Better for Deep Auto-Encoders?
Yingbo Zhou, Devansh Arpit, Ifeoma Nwogu +1
Traditionally, when generative models of data are developed via deep architectures, greedy layer-wise pre-training is employed. In a well-trained model, the lower layer of the arch…