18 citations · 50 across the 12 of their papers we have counts for
12 papers
ZARA: Improving Few-Shot Self-Rationalization for Small Language Models
Wei-Lin Chen, An-Zi Yen, Cheng-Kuang Wu +2
Language models (LMs) that jointly generate end-task answers as well as free-text rationales are known as self-rationalization models. Recent works demonstrate great performance ga…
LED: A Dataset for Life Event Extraction from Dialogs
Yi-Pei Chen, An-Zi Yen, Hen-Hsen Huang +2
Lifelogging has gained more attention due to its wide applications, such as personalized recommendations or memory assistance. The issues of collecting and extracting personal life…
Entity-Aware Dual Co-Attention Network for Fake News Detection
Sin-Han Yang, Chung-Chi Chen, Hen-Hsen Huang +1
Fake news and misinformation spread rapidly on the Internet. How to identify it and how to interpret the identification results have become important issues. In this paper, we prop…
FinTech for Social Good: A Research Agenda from NLP Perspective
Chung-Chi Chen, Hiroya Takamura, Hsin-Hsi Chen
Making our research results positively impact on society and environment is one of the goals our community has been pursuing recently. Although financial technology (FinTech) is on…
Fine-grained Financial Opinion Mining: A Survey and Research Agenda
Chung-Chi Chen, Hen-Hsen Huang, Hsin-Hsi Chen
Opinion mining is a prevalent research issue in many domains. In the financial domain, however, it is still in the early stages. Most of the researches on this topic only focus on…
Ten Questions in Lifelog Mining and Information Recall
An-Zi Yen, Hen-Hsen Huang, Hsin-Hsi Chen
With the advance of science and technology, people are used to record their daily life events via writing blogs, uploading social media posts, taking photos, or filming videos. Suc…
NLP in FinTech Applications: Past, Present and Future
Chung-Chi Chen, Hen-Hsen Huang, Hsin-Hsi Chen
Financial Technology (FinTech) is one of the worldwide rapidly-rising topics in the past five years according to the statistics of FinTech from Google Trends. In this position pape…
Novel Word Embedding and Translation-based Language Modeling for Extractive Speech Summarization
Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen +2
Word embedding methods revolve around learning continuous distributed vector representations of words with neural networks, which can capture semantic and/or syntactic cues, and in…
Leveraging Word Embeddings for Spoken Document Summarization
Kuan-Yu Chen, Shih-Hung Liu, Hsin-Min Wang +2
Owing to the rapidly growing multimedia content available on the Internet, extractive spoken document summarization, with the purpose of automatically selecting a set of representa…
Approximate N-Gram Markov Model for Natural Language Generation
Hsin-Hsi Chen, Yue-Shi Lee
This paper proposes an Approximate n-gram Markov Model for bag generation. Directed word association pairs with distances are used to approximate (n-1)-gram and n-gram training tab…
A Corrective Training Algorithm for Adaptive Learning in Bag Generation
Hsin-Hsi Chen, Yue-Shi Lee
The sampling problem in training corpus is one of the major sources of errors in corpus-based applications. This paper proposes a corrective training algorithm to best-fit the run-…
Extracting Noun Phrases from Large-Scale Texts: A Hybrid Approach and Its Automatic Evaluation
Kuang-hua Chen, Hsin-Hsi Chen
To acquire noun phrases from running texts is useful for many applications, such as word grouping,terminology indexing, etc. The reported literatures adopt pure probabilistic appro…