54 citations · 142 across the 22 of their papers we have counts for
26 papers · 1 filter
Positional Cognitive Specialization: Where Do LLMs Learn To Comprehend and Speak Your Language?
Luis Frentzen Salim, Lun-Wei Ku, Hsing-Kuo Kenneth Pao
Adapting large language models (LLMs) to new languages is an expensive and opaque process. Understanding how language models acquire new languages and multilingual abilities is key…
Beyond Many-Shot Translation: Scaling In-Context Demonstrations For Low-Resource Machine Translation
Luis Frentzen Salim, Esteban Carlin, Alexandre Morinvil +2
Building machine translation (MT) systems for low-resource languages is notably difficult due to the scarcity of high-quality data. Although Large Language Models (LLMs) have impro…
Profile-LLM: Dynamic Profile Optimization for Realistic Personality Expression in LLMs
Shi-Wei Dai, Yan-Wei Shie, Tsung-Huan Yang +2
Personalized Large Language Models (LLMs) have been shown to be an effective way to create more engaging and enjoyable user-AI interactions. While previous studies have explored us…
Do Large Multimodal Models Solve Caption Generation for Scientific Figures? Lessons Learned from SciCap Challenge 2023
Ting-Yao E. Hsu, Yi-Li Hsu, Shaurya Rohatgi +8
Since the SciCap datasets launch in 2021, the research community has made significant progress in generating captions for scientific figures in scholarly articles. In 2023, the fir…
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…
Is Explanation the Cure? Misinformation Mitigation in the Short Term and Long Term
Yi-Li Hsu, Shih-Chieh Dai, Aiping Xiong +1
With advancements in natural language processing (NLP) models, automatic explanation generation has been proposed to mitigate misinformation on social media platforms in addition t…