Unlocking Insight
"Unlocking Insight" encompasses research efforts to improve the performance and interpretability of various models, primarily focusing on large language models (LLMs) and their applications across diverse domains. Current research emphasizes enhancing LLMs' understanding of complex data structures (e.g., graphs, knowledge graphs), improving their robustness against adversarial attacks, and leveraging multimodal data (text, images, etc.) for more comprehensive analysis. These advancements have significant implications for fields like drug discovery, high-frequency trading, and natural language processing, enabling more efficient data analysis and more accurate predictions.
Papers
Unlocking Legal Knowledge: A Multilingual Dataset for Judicial Summarization in Switzerland
Luca Rolshoven, Vishvaksenan Rasiah, Srinanda Brügger Bose, Matthias Stürmer, Joel Niklaus
Unlocking the Capabilities of Masked Generative Models for Image Synthesis via Self-Guidance
Jiwan Hur, Dong-Jae Lee, Gyojin Han, Jaehyun Choi, Yunho Jeon, Junmo Kim