5 citations · 6 across the 3 of their papers we have counts for
3 papers
Beyond Opinion Mining: Summarizing Opinions of Customer Reviews
Reinald Kim Amplayo, Arthur Bražinskas, Yoshi Suhara +2
Customer reviews are vital for making purchasing decisions in the Information Age. Such reviews can be automatically summarized to provide the user with an overview of opinions. In…
Efficient Few-Shot Fine-Tuning for Opinion Summarization
Arthur Bražinskas, Ramesh Nallapati, Mohit Bansal +1
Abstractive summarization models are typically pre-trained on large amounts of generic texts, then fine-tuned on tens or hundreds of thousands of annotated samples. However, in opi…
Transductive Learning for Abstractive News Summarization
Arthur Bražinskas, Mengwen Liu, Ramesh Nallapati +2
Pre-trained and fine-tuned news summarizers are expected to generalize to news articles unseen in the fine-tuning (training) phase. However, these articles often contain specifics,…