4 papers
ToC: Tree-of-Claims Search with Multi-Agent Language Models
Shuyang Yu, Jianan Liang, Hui Hu
Optimizing patent claims is a critical yet challenging task, demanding careful balance between maximizing novelty and preserving legal scope. Manual claim drafting is labor-intensi…
Low-hallucination Synthetic Captions for Large-Scale Vision-Language Model Pre-training
Xinsong Zhang, Yarong Zeng, Xinting Huang +4
In recent years, the field of vision-language model pre-training has experienced rapid advancements, driven primarily by the continuous enhancement of textual capabilities in large…
Synergistic Vision-Language Reinforcement Enables Scalable On-Demand Analysis across Diverse Clinical Tasks
Haonan Wang, Jiaji Mao, Lehan Wang +11
Accurate segmentation of tumors and organs-at-risk is essential for oncology but remains time-consuming and expertise-intensive. Existing AI systems often require manual spatial pr…
Bayesian adaptive learning to latent variables via Variational Bayes and Maximum a Posteriori
Hu Hu, Sabato Marco Siniscalchi, Chin-Hui Lee
In this work, we aim to establish a Bayesian adaptive learning framework by focusing on estimating latent variables in deep neural network (DNN) models. Latent variables indeed enc…