58 citations · 153 across the 66 of their papers we have counts for
9 papers · 1 filter
HyperPatch: Sequential Knowledge Editing Under n-ary Structural Drift
Yu-Kai Chan, Wen-Sheng Lien, Dong-Ting Yao +4
Large Language Models (LLMs) rely on Knowledge Editing (KE) to maintain temporal validity, yet real-world knowledge is inherently n-ary. We demonstrate that in non-stationary envir…
HyperRAG: Reasoning N-ary Facts over Hypergraphs for Retrieval Augmented Generation
Wen-Sheng Lien, Yu-Kai Chan, Hao-Lung Hsiao +5
Graph-based retrieval-augmented generation (RAG) methods, typically built on knowledge graphs (KGs) with binary relational facts, have shown promise in multi-hop open-domain QA. Ho…
Breaking the Reviewer: Assessing the Vulnerability of Large Language Models in Automated Peer Review Under Textual Adversarial Attacks
Tzu-Ling Lin, Wei-Chih Chen, Teng-Fang Hsiao +7
Peer review is essential for maintaining academic quality, but the increasing volume of submissions places a significant burden on reviewers. Large language models (LLMs) offer pot…
SocialNLP Fake-EmoReact 2021 Challenge Overview: Predicting Fake Tweets from Their Replies and GIFs
Chien-Kun Huang, Yi-Ting Chang, Lun-Wei Ku +2
This paper provides an overview of the Fake-EmoReact 2021 Challenge, held at the 9th SocialNLP Workshop, in conjunction with NAACL 2021. The challenge requires predicting the authe…
An Improved Traditional Chinese Evaluation Suite for Foundation Model
Zhi-Rui Tam, Ya-Ting Pai, Yen-Wei Lee +4
We present TMMLU+, a new benchmark designed for Traditional Chinese language understanding. TMMLU+ is a multi-choice question-answering dataset with 66 subjects from elementary to…
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…
Meta-Transfer Learning for Low-Resource Abstractive Summarization
Yi-Syuan Chen, Hong-Han Shuai
Neural abstractive summarization has been studied in many pieces of literature and achieves great success with the aid of large corpora. However, when encountering novel tasks, one…
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…