182 citations · 191 across the 11 of their papers we have counts for
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cs.CL2021
Training Dynamics for Text Summarization Models
Tanya Goyal, Jiacheng Xu, Junyi Jessy Li +1
Pre-trained language models (e.g. BART) have shown impressive results when fine-tuned on large summarization datasets. However, little is understood about this fine-tuning process,…
cs.CL2021
HydraSum: Disentangling Stylistic Features in Text Summarization using Multi-Decoder Models
Tanya Goyal, Nazneen Fatema Rajani, Wenhao Liu +1
Summarization systems make numerous "decisions" about summary properties during inference, e.g. degree of copying, specificity and length of outputs, etc. However, these are implic…
cs.CL2021
Annotating and Modeling Fine-grained Factuality in Summarization
Tanya Goyal, Greg Durrett
Recent pre-trained abstractive summarization systems have started to achieve credible performance, but a major barrier to their use in practice is their propensity to output summar…