1 citations · 1 across the 5 of their papers we have counts for
5 papers
SINC: Self-Supervised In-Context Learning for Vision-Language Tasks
Yi-Syuan Chen, Yun-Zhu Song, Cheng Yu Yeo +3
Large Pre-trained Transformers exhibit an intriguing capacity for in-context learning. Without gradient updates, these models can rapidly construct new predictors from demonstratio…
Shilling Black-box Review-based Recommender Systems through Fake Review Generation
Hung-Yun Chiang, Yi-Syuan Chen, Yun-Zhu Song +2
Review-Based Recommender Systems (RBRS) have attracted increasing research interest due to their ability to alleviate well-known cold-start problems. RBRS utilizes reviews to const…
SPEC: Summary Preference Decomposition for Low-Resource Abstractive Summarization
Yi-Syuan Chen, Yun-Zhu Song, Hong-Han Shuai
Neural abstractive summarization has been widely studied and achieved great success with large-scale corpora. However, the considerable cost of annotating data motivates the need f…
Improving Multi-Document Summarization through Referenced Flexible Extraction with Credit-Awareness
Yun-Zhu Song, Yi-Syuan Chen, Hong-Han Shuai
A notable challenge in Multi-Document Summarization (MDS) is the extremely-long length of the input. In this paper, we present an extract-then-abstract Transformer framework to ove…
Attractive or Faithful? Popularity-Reinforced Learning for Inspired Headline Generation
Yun-Zhu Song, Hong-Han Shuai, Sung-Lin Yeh +3
With the rapid proliferation of online media sources and published news, headlines have become increasingly important for attracting readers to news articles, since users may be ov…