Full Potential
"Full potential" research explores maximizing the capabilities of various models and algorithms across diverse fields. Current efforts focus on improving model performance in tasks like program repair, multimodal search, and medical image segmentation, often leveraging large language models (LLMs), diffusion models, and graph neural networks. This research is significant because it aims to enhance the efficiency and accuracy of existing technologies, leading to advancements in areas such as software development, AI-assisted content creation, and healthcare diagnostics. The ultimate goal is to unlock the full capabilities of these models for practical applications and scientific discovery.
Papers
LM-IGTD: a 2D image generator for low-dimensional and mixed-type tabular data to leverage the potential of convolutional neural networks
Vanesa Gómez-Martínez, Francisco J. Lara-Abelenda, Pablo Peiro-Corbacho, David Chushig-Muzo, Conceicao Granja, Cristina Soguero-Ruiz
Unleashing the Potential of Fractional Calculus in Graph Neural Networks with FROND
Qiyu Kang, Kai Zhao, Qinxu Ding, Feng Ji, Xuhao Li, Wenfei Liang, Yang Song, Wee Peng Tay
MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies
Shengding Hu, Yuge Tu, Xu Han, Chaoqun He, Ganqu Cui, Xiang Long, Zhi Zheng, Yewei Fang, Yuxiang Huang, Weilin Zhao, Xinrong Zhang, Zheng Leng Thai, Kaihuo Zhang, Chongyi Wang, Yuan Yao, Chenyang Zhao, Jie Zhou, Jie Cai, Zhongwu Zhai, Ning Ding, Chao Jia, Guoyang Zeng, Dahai Li, Zhiyuan Liu, Maosong Sun
Exploring the True Potential: Evaluating the Black-box Optimization Capability of Large Language Models
Beichen Huang, Xingyu Wu, Yu Zhou, Jibin Wu, Liang Feng, Ran Cheng, Kay Chen Tan
Exploring the Potential of Large Foundation Models for Open-Vocabulary HOI Detection
Ting Lei, Shaofeng Yin, Yang Liu
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models
Yanwei Li, Yuechen Zhang, Chengyao Wang, Zhisheng Zhong, Yixin Chen, Ruihang Chu, Shaoteng Liu, Jiaya Jia
Will You Participate? Exploring the Potential of Robotics Competitions on Human-centric Topics
Yuchong Zhang, Miguel Vasco, Mårten Björkman, Danica Kragic
Unleashing the Potential of SAM for Medical Adaptation via Hierarchical Decoding
Zhiheng Cheng, Qingyue Wei, Hongru Zhu, Yan Wang, Liangqiong Qu, Wei Shao, Yuyin Zhou
Exploring the Potential of Large Language Models in Graph Generation
Yang Yao, Xin Wang, Zeyang Zhang, Yijian Qin, Ziwei Zhang, Xu Chu, Yuekui Yang, Wenwu Zhu, Hong Mei
From Perils to Possibilities: Understanding how Human (and AI) Biases affect Online Fora
Virginia Morini, Valentina Pansanella, Katherine Abramski, Erica Cau, Andrea Failla, Salvatore Citraro, Giulio Rossetti