Real World
Research on "real-world" applications focuses on bridging the gap between simulated and real-world environments, particularly for complex tasks like robotics, autonomous driving, and natural language processing. Current efforts utilize various model architectures, including large language models (LLMs), diffusion models, reinforcement learning (RL), and graph neural networks, to improve robustness, generalization, and efficiency in diverse real-world scenarios. This research is crucial for advancing AI capabilities beyond controlled settings and enabling practical applications in areas such as healthcare, manufacturing, and transportation, while also addressing challenges like data scarcity, safety, and bias.
442papers
Papers - Page 11
May 30, 2024
Aquatic Navigation: A Challenging Benchmark for Deep Reinforcement Learning
Davide Corsi, Davide Camponogara, Alessandro FarinelliDiffPhysBA: Diffusion-based Physical Backdoor Attack against Person Re-Identification in Real-World
Wenli Sun, Xinyang Jiang, Dongsheng Li, Cairong ZhaoDevEval: A Manually-Annotated Code Generation Benchmark Aligned with Real-World Code Repositories
Jia Li, Ge Li, Yunfei Zhao, Yongmin Li, Huanyu Liu, Hao Zhu, Lecheng Wang, Kaibo Liu, Zheng Fang, Lanshen Wang, Jiazheng Ding, Xuanming Zhang+6LED: A Large-scale Real-world Paired Dataset for Event Camera Denoising
Yuxing Duan, Shihan Peng, Lin Zhu, Wei Zhang, Yi Chang, Sheng Zhong, Luxin YanSMPLX-Lite: A Realistic and Drivable Avatar Benchmark with Rich Geometry and Texture Annotations
Yujiao Jiang, Qingmin Liao, Zhaolong Wang, Xiangru Lin, Zongqing Lu, Yuxi Zhao, Hanqing Wei, Jingrui Ye, Yu Zhang, Zhijing Shao
May 28, 2024
RealitySummary: Exploring On-Demand Mixed Reality Text Summarization and Question Answering using Large Language Models
Aditya Gunturu, Shivesh Jadon, Nandi Zhang, Morteza Faraji, Jarin Thundathil, Tafreed Ahmad, Wesley Willett, Ryo SuzukiNotPlaNET: Removing False Positives from Planet Hunters TESS with Machine Learning
Valentina Tardugno Poleo, Nora Eisner, David W. Hogg
May 26, 2024
Higher-Order Transformer Derivative Estimates for Explicit Pathwise Learning Guarantees
Yannick Limmer, Anastasis Kratsios, Xuwei Yang, Raeid Saqur, Blanka HorvathReCODE: Modeling Repeat Consumption with Neural ODE
Sunhao Dai, Changle Qu, Sirui Chen, Xiao Zhang, Jun XuAssessing Empathy in Large Language Models with Real-World Physician-Patient Interactions
Man Luo, Christopher J. Warren, Lu Cheng, Haidar M. Abdul-Muhsin, Imon Banerjee
May 23, 2024
May 22, 2024