4 papers
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…