A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Minghao Wang, Tianqing Zhu, Tao Zhang, et al.
A survey of security and privacy challenges in 6G networks, covering real-time intelligent edge computing, distributed AI, intelligent radio, and 3D intercoms.
Shaoqing Ren, Kaiming He, Ross Girshick, et al.
Introduces a Region Proposal Network (RPN) that shares convolutional features with Fast R-CNN, enabling nearly cost-free region proposals and real-time object detection.
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RiverEcho-2.0 presents a real-time interactive system for Yellow River culture using enhanced multimodal document RAG to retrieve tables, texts, and images.
Kai Stewart, Yasunori Toshimitsu, Robert K. Katzschmann
A real-time Jacobian estimation controller enables an anthropomorphic hand to write with a grasped pen via purely in-hand motion, achieving sub-millimeter precision without simulation training or demonstrations.
Qi Sun, Edoardo Cetin, Yujin Tang
Transformer-Squared is a self-adaptive LLM framework that adjusts only the singular components of weight matrices in real-time, using a two-pass dispatch and reinforcement-learned expert vectors to outperform LoRA with fewer parameters.
Lukas Radl, Michael Steiner, Mathias Parger, et al.
StopThePop introduces a hierarchical rasterization approach for 3D Gaussian Splatting that eliminates popping artifacts and view inconsistencies with minimal overhead, enabling faster rendering and reduced memory.
Yipeng Hu, Marc Modat, Eli Gibson, et al.
This paper introduces a weakly-supervised CNN approach for multimodal image registration that learns voxel-level transformations from anatomical labels, enabling real-time, fully-automated inference without labels.
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This paper proposes a UAV-deployed deep learning network for real-time multi-class damage detection, enhanced by model quantization techniques.
Hamid Mirshekali, Mohammad Reza Shadi, Fatemehsadat Ghanadi Ladani, et al.
This review synthesizes LLM applications across energy systems, consolidates evaluation and fine-tuning methods, and analyzes deployment constraints for real-time and edge adoption.
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This paper introduces a training framework for real-time hallucination detection in LLMs using internal states, along with the HELM benchmark for evaluation.
Eduardo Romera, Jose M. Álvarez, Luis M. Bergasa, et al.
ERFNet introduces a novel efficient residual factorized convolutional layer for real-time semantic segmentation, achieving high accuracy at over 83 FPS on Titan X and 7 FPS on Jetson TX1.
Sungjae Park, Shubham Tulsiani
πR² makes large pretrained action-chunking flow policies reactive and real-time via dual-channel conditioning and a latency-adaptive flow schedule.