DCU Insight AQ
DCU Insight AQ is not a defined scientific topic or project readily identifiable in the provided abstracts. The abstracts cover a broad range of research using Large Language Models (LLMs) and other machine learning techniques across diverse fields, including legal reasoning, medical diagnosis, materials science, and anomaly detection. Current research focuses on improving LLM performance through techniques like multi-agent frameworks, multimodal data integration, and careful data curation, as well as addressing challenges such as hallucinations, bias, and efficient model training. These advancements have the potential to significantly improve data analysis, automate complex tasks, and enhance decision-making across numerous scientific and industrial domains.
Papers
Enhancing Apple's Defect Classification: Insights from Visible Spectrum and Narrow Spectral Band Imaging
Omar Coello, Moisés Coronel, Darío Carpio, Boris Vintimilla, Luis Chuquimarca
What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis
Weronika Ormaniec, Felix Dangel, Sidak Pal Singh
Software Engineering and Foundation Models: Insights from Industry Blogs Using a Jury of Foundation Models
Hao Li, Cor-Paul Bezemer, Ahmed E. Hassan
Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory
Aymane El Firdoussi, Mohamed El Amine Seddik, Soufiane Hayou, Reda Alami, Ahmed Alzubaidi, Hakim Hacid
Insight Over Sight? Exploring the Vision-Knowledge Conflicts in Multimodal LLMs
Xiaoyuan Liu, Wenxuan Wang, Youliang Yuan, Jen-tse Huang, Qiuzhi Liu, Pinjia He, Zhaopeng Tu
Exploring ASR-Based Wav2Vec2 for Automated Speech Disorder Assessment: Insights and Analysis
Tuan Nguyen, Corinne Fredouille, Alain Ghio, Mathieu Balaguer, Virginie Woisard
Metrics Revolutions: Groundbreaking Insights into the Implementation of Metrics for Biomedical Image Segmentation
Gašper Podobnik, Tomaž Vrtovec
Can Large Language Models Grasp Legal Theories? Enhance Legal Reasoning with Insights from Multi-Agent Collaboration
Weikang Yuan, Junjie Cao, Zhuoren Jiang, Yangyang Kang, Jun Lin, Kaisong Song, tianqianjin lin, Pengwei Yan, Changlong Sun, Xiaozhong Liu
From Facts to Insights: A Study on the Generation and Evaluation of Analytical Reports for Deciphering Earnings Calls
Tomas Goldsack, Yang Wang, Chenghua Lin, Chung-Chi Chen
Insight: A Multi-Modal Diagnostic Pipeline using LLMs for Ocular Surface Disease Diagnosis
Chun-Hsiao Yeh, Jiayun Wang, Andrew D. Graham, Andrea J. Liu, Bo Tan, Yubei Chen, Yi Ma, Meng C. Lin
MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning
Haotian Zhang, Mingfei Gao, Zhe Gan, Philipp Dufter, Nina Wenzel, Forrest Huang, Dhruti Shah, Xianzhi Du, Bowen Zhang, Yanghao Li, Sam Dodge, Keen You, Zhen Yang, Aleksei Timofeev, Mingze Xu, Hong-You Chen, Jean-Philippe Fauconnier, Zhengfeng Lai, Haoxuan You, Zirui Wang, Afshin Dehghan, Peter Grasch, Yinfei Yang
What Information Contributes to Log-based Anomaly Detection? Insights from a Configurable Transformer-Based Approach
Xingfang Wu, Heng Li, Foutse Khomh