activity
20182022
most citedSalience Allocation as Guidance for Abstractive Summarization

4 citations · 7 across the 5 of their papers we have counts for

collaborators

8 papers

cs.CL2022

Toward Unifying Text Segmentation and Long Document Summarization

Sangwoo Cho, Kaiqiang Song, Xiaoyang Wang +2

Text segmentation is important for signaling a document's structure. Without segmenting a long document into topically coherent sections, it is difficult for readers to comprehend…

cs.CL20224 cited

Salience Allocation as Guidance for Abstractive Summarization

Fei Wang, Kaiqiang Song, Hongming Zhang +6

Abstractive summarization models typically learn to capture the salient information from scratch implicitly. Recent literature adds extractive summaries as guidance for abstractive…

cs.CL2022

Z-LaVI: Zero-Shot Language Solver Fueled by Visual Imagination

Yue Yang, Wenlin Yao, Hongming Zhang +3

Large-scale pretrained language models have made significant advances in solving downstream language understanding tasks. However, they generally suffer from reporting bias, the ph…

cs.CL2022

Towards Abstractive Grounded Summarization of Podcast Transcripts

Kaiqiang Song, Chen Li, Xiaoyang Wang +2

Podcasts have recently shown a rapid rise in popularity. Summarization of podcast transcripts is of practical benefit to both content providers and consumers. It helps consumers to…

cs.CL20203 cited

Automatic Summarization of Open-Domain Podcast Episodes

Kaiqiang Song, Chen Li, Xiaoyang Wang +2

We present implementation details of our abstractive summarizers that achieve competitive results on the Podcast Summarization task of TREC 2020. A concise textual summary that cap…

cs.CL2020

Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints

Zhenyi Wang, Xiaoyang Wang, Bang An +2

Text generation from a knowledge base aims to translate knowledge triples to natural language descriptions. Most existing methods ignore the faithfulness between a generated text d…