A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Shen Nie, Fengqi Zhu, Zebin You, et al.
This paper demonstrates that diffusion models can achieve competitive performance with autoregressive LLMs on core language tasks at scale, challenging the assumption that such capabilities inherently require autoregressive architectures.
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A comprehensive survey and guide to multimodal large language models (MLLMs) for vision-language tasks, covering architectures, training, and applications.
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This paper introduces a dynamic early exit method for reasoning models that reduces inference cost while maintaining performance across eleven model architectures.
Tianhong Li, Qinyi Sun, Lijie Fan, et al.
Introduces fractal generative models, recursively composing atomic generative modules into self-similar architectures, demonstrating strong performance in pixel-by-pixel image generation.
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This paper investigates in-context learning of regular languages generated by random finite automata, comparing architectures and algorithms.
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This paper provides a comprehensive survey of Agentic AI, covering architectures, applications, and future directions, contrasting AI agents with Agentic AI systems.
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Proposes A-mem, an agentic memory system that dynamically organizes memories for LLM agents to address limitations in fixed memory architectures.
Peng Xu, Xiatian Zhu, David A. Clifton
A comprehensive survey of Transformer techniques for multimodal learning, covering architectures, 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.
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.
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.