A hierarchical joint optimization algorithm is developed within a multi-agent deep reinforcement learning (MADRL) framework to coordinate UAVs and MTs in a distributed manner and outperforms other benchmarks under varying network scales and capabilities by jointly optimizing UAV operations and resource utilization.
Tian-Kui Zhang, Wenlong Xu, Tian-Yi Shi et al.· IEEE Internet of Things Jour...· 0 citations
A compact and configurable event-driven autoencoder that efficiently compresses neuromorphic data while preserving essential spatiotemporal structure for downstream inference and demonstrates the potential of compact event-driven models to advance environmentally conscious, low-power AI systems for high-speed perceptio...
Riadul Islam, Joey Mulé, Dhandeep Challagundla et al.· 0 citations
PRISM, a prediction-guided runtime framework that jointly selects model variants and CPU allocations for containerized edge microservices, and adapts each pipeline stage in place and minimizes predicted CPU-package energy under deadline, resource, and offline model-level Quality of Result constraints is presented.
Uwe Gropengießer, Thomas Reuter, Dominik Schön et al.· 0 citations
A complete FPGA-validated RISC-V SoC in which a five-stage RV32IM processor works alongside a custom systolic MAC array, and two propositions are formally proved that the output-stationary schedule reduces computation cycles by a naïve, unblocked sequential CPU execution.
Srujan Sateesh Kalagi, K. R. Vinay Kumar, Shashank Dharamshetty et al.· Discover Artificial Intellig...· 0 citations
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A systems vision for AI infrastructure in space is developed as the systems layer that manages AI capabilities across spacecraft, orbital networks, ground stations, and cloud backends, while treating orbital and physical state as part of the resource model.
Qing Li, Qi-Yang Zhang, Da-Liang Xu et al.· 0 citations
Quản lý động tài nguyên trong hệ thống điện toán biên đa truy cập (Multi- Access Edge Computing - MEC) phục vụ ứng dụng thực tế ảo và thực tế tăng cường (AR/ VR) đặt ra nhiều thách thức lớn do yêu cầu khắt khe về độ trễ thấp và hiệu quả năng lượng. Học tăng cường sâu (Deep Reinforcement Learning - DRL) đã trở thành các...
Hoàng Trọng Nghĩa· Tạp chí Khoa học Trường Đại...· 0 citations
These findings show that reliable evaluation of LLM-generated code requires validated ground truth, protected tests, and multiple explicitly interpreted measures, and that CodeAssay provides a reproducible basis for evidence-based model evaluation in AI-augmented software development.
Shahbaz Siddeeq, Muhammad Waseem, Umar Subhan Malhi et al.· 0 citations
The first comprehensive benchmarking framework specifically designed to accommodate inter-dataset heterogeneity is presented, finding that well-designed small datasets can match or even surpass the performance of larger benchmarks, suggesting that different metrics are applicable to different datasets/testing scenarios...
Yingjuan Cheng, Qing Ye, Linlong Jiang et al.· Journal of Cheminformatics· 0 citations
A novel committor learning framework grounded in the AlphaFold 3 paradigm is proposed that elucidates how ligand substituents regulate the ratio between distinct binding pathways, offering new perspectives for structure-based drug design.
Jintu Zhang, Zichang Jin, Huifeng Zhao et al.· 0 citations
A novel approach for distinguishing individuals with Autism Spectrum Disorder (ASD) using Intuitionistic Fuzzy Set (IFS) theory and Multi-Scale Enhanced Graph Convolutional Networks (MSE-GCNs), which represents a substantial improvement over existing models for ASD and potentially for other neurological disorders.
S. Rajaprakash, C. Basha, K. Manivanan et al.· Discover Artificial Intellig...· 0 citations
This paper introduces Caduceus, a family of MoE-enhanced foundation models built with a hierarchical pre-training paradigm to jointly integrate biological and natural language, and incorporates a multi-task instruction tuning phase, enabling robust protein parsing and natural language question answering.
Mingze Yin, Yiheng Zhu, Jialu Wu et al.· Proceedings of the 32nd ACM...· 0 citations
This work presents a multi-mode energy harvesting-assisted edge computing architecture, integrated with a joint optimization of energy consumption and communication behaviour, aimed at enhancing the sustainability, reliability and autonomy of operation in an industrial IoT context.
Dr. Deepa, M. Mehfooza, Padmavathy Thiruppathi Raj· Microsystem Technologies· 0 citations
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Microsoft Research Blog· microsoft.comOct 15, 2026
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
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