A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Adam Kostka, J. Chudziak
This paper introduces a novel multi-agent architecture integrating Theory of Mind, BDI-style internal beliefs, and symbolic solvers to improve collaborative decision-making in LLM-based systems.
Gokul Yenduri, M. Ramalingam, G. Chemmalar Selvi, et al.
A comprehensive review of GPT covering architecture, training, enabling technologies, applications, challenges, and future directions.
Pallavi Sethi, Smruti R. Sarangi
A comprehensive survey of IoT architectures, protocols, and applications with a novel taxonomy covering technologies from sensors to applications.
Sardar Usman, Rashid Mehmood, Iyad Katib, et al.
This paper reviews data locality in HPC, big data, and converged systems, then proposes a future system architecture for such converged environments.
Soren Kejser Jensen, Torben Bach Pedersen, Christian Thomsen
A survey classifying Time Series Management Systems by architecture, storage, querying, stream processing, and approximate query processing, with a vision for next-generation systems.
Martin Schoeberl, Sahar Abbaspour, Benny Åkesson, et al.
T-CREST proposes a time-predictable multi-core architecture optimized for worst-case execution time (WCET) rather than average-case performance, enabling static WCET analysis for real-time systems.
Sheng Li, Jung Ho Ahn, Richard Strong, et al.
McPAT is an integrated power, area, and timing modeling framework for multicore/manycore architectures, enabling design space exploration from 90nm to 22nm.
Kevin Skadron, Mircea R. Stan, Karthik Sankaranarayanan, et al.
Introduces HotSpot, a thermal model for microarchitecture, and evaluates dynamic thermal management techniques like migrating computation and hybrid policies.
Michael I. Jordan, Robert A. Jacobs
Introduces a tree-structured supervised learning architecture using hierarchical mixtures of experts with an EM algorithm for parameter estimation.
Evan Shelhamer, Jonathan Long, Trevor Darrell
Fully convolutional networks trained end-to-end for semantic segmentation achieve state-of-the-art results by adapting classification nets and using a skip architecture for detailed predictions.
Khalid Nassiri, Moulay A. Akhloufi
This survey reviews recent advances in large language models for healthcare, covering architectures, medical datasets, and applications while highlighting technical and ethical challenges.
Ajay Bandi, Bhavani Kongari, Roshini Naguru, et al.
A comprehensive review of agentic AI systems covering definitions, frameworks, architectures, evaluation metrics, and challenges, based on 143 primary studies.