5 citations · 15 across the 8 of their papers we have counts for
9 papers
STRUDEL: Structured Dialogue Summarization for Dialogue Comprehension
Borui Wang, Chengcheng Feng, Arjun Nair +6
Abstractive dialogue summarization has long been viewed as an important standalone task in natural language processing, but no previous work has explored the possibility of whether…
Improving Faithfulness of Abstractive Summarization by Controlling Confounding Effect of Irrelevant Sentences
Asish Ghoshal, Arash Einolghozati, Ankit Arun +6
Lack of factual correctness is an issue that still plagues state-of-the-art summarization systems despite their impressive progress on generating seemingly fluent summaries. In thi…
ED-FAITH: Evaluating Dialogue Summarization on Faithfulness
Sicong Huang, Asli Celikyilmaz, Haoran Li
Abstractive summarization models typically generate content unfaithful to the input, thus highlighting the significance of evaluating the faithfulness of generated summaries. Most…
AnswerSumm: A Manually-Curated Dataset and Pipeline for Answer Summarization
Alexander R. Fabbri, Xiaojian Wu, Srini Iyer +2
Community Question Answering (CQA) fora such as Stack Overflow and Yahoo! Answers contain a rich resource of answers to a wide range of community-based questions. Each question thr…
The JDDC 2.0 Corpus: A Large-Scale Multimodal Multi-Turn Chinese Dialogue Dataset for E-commerce Customer Service
Nan Zhao, Haoran Li, Youzheng Wu +2
With the development of the Internet, more and more people get accustomed to online shopping. When communicating with customer service, users may express their requirements by mean…
Investigating Crowdsourcing Protocols for Evaluating the Factual Consistency of Summaries
Xiangru Tang, Alexander Fabbri, Haoran Li +6
Current pre-trained models applied to summarization are prone to factual inconsistencies which either misrepresent the source text or introduce extraneous information. Thus, compar…
Syntax-augmented Multilingual BERT for Cross-lingual Transfer
Wasi Uddin Ahmad, Haoran Li, Kai-Wei Chang +1
In recent years, we have seen a colossal effort in pre-training multilingual text encoders using large-scale corpora in many languages to facilitate cross-lingual transfer learning…
EASE: Extractive-Abstractive Summarization with Explanations
Haoran Li, Arash Einolghozati, Srinivasan Iyer +4
Current abstractive summarization systems outperform their extractive counterparts, but their widespread adoption is inhibited by the inherent lack of interpretability. To achieve…
K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-Commerce
Song Xu, Haoran Li, Peng Yuan +5
Existing pre-trained language models (PLMs) have demonstrated the effectiveness of self-supervised learning for a broad range of natural language processing (NLP) tasks. However, m…