Bridging Text
"Bridging" in scientific research refers to the integration of disparate data modalities or concepts to improve model performance or understanding. Current research focuses on bridging text and other modalities (images, sound, code, tabular data) using various techniques, including multimodal VAEs, diffusion models, and large language models (LLMs) adapted for specific tasks like automatic speech recognition or computer-aided design. This work aims to improve efficiency, accuracy, and explainability in diverse applications ranging from medical image analysis and robotics to legal reasoning and social science. The ultimate goal is to create more robust, versatile, and human-centered AI systems.
Papers
Bridging and Modeling Correlations in Pairwise Data for Direct Preference Optimization
Yuxin Jiang, Bo Huang, Yufei Wang, Xingshan Zeng, Liangyou Li, Yasheng Wang, Xin Jiang, Lifeng Shang, Ruiming Tang, Wei Wang
Bridging Training and Execution via Dynamic Directed Graph-Based Communication in Cooperative Multi-Agent Systems
Zhuohui Zhang, Bin He, Bin Cheng, Gang Li