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Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Akhil Pandey

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4 papers indexed here

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#federated learning Open access Oct 2026

Federated Fine-Tuning of Foundation Models (Fed-LLMs): Parameter-Efficient Adapters, Split Learning, and Gradient Privacy Bounds

Abstract—Fine-tuning Large Language Models (LLMs) and Vision Foundation Models on private, decentralized domain data is essential for specialized healthcare, legal, and financial enterprise applications. However, centralizing domain-specific text corpora triggers catastrophic data privacy violations under stringent reg...

Rohit Kumar, Inderkumawat, Vishal Shrivastava et al. · 0 citations
#large language models Open access Oct 2026

Neuro-Symbolic Artificial Intelligence: Integrating Large Language Models with SMT Solvers, Knowledge Graphs, and Formal Automated Theorem Provers

Abstract—Modern deep neural networks, particularly autoregressive Large Language Models (LLMs), have achieved state-of-the-art empirical performance across natural language generation, semantic translation, and broad pattern recognition. However, pure statistical connectionist architectures suffer from fundamental epis...

Pratiyush, Mayank Singh, Vishal Shrivastava et al. · 0 citations
#explainable ai Open access Oct 2026

Explainable Artificial Intelligence for Computer Vision: A Comprehensive Study on Interpretability Techniques, and Applications

Abstract Convolutional neural networks (CNNs) have achieved state-of-the-art performance across computer vision tasks, including image classification, object detection, and medical image analysis. However, the opaque, black-box nature of these models limits their adoption in high-stakes domains such as healthcare, auto...

Ishan Gupta, Gaurav Jangid, Vishal Shrivastava et al. · 0 citations
#explainable ai Open access Oct 2026

Explainable Artificial Intelligence for Computer Vision: A Comprehensive Study on Interpretability Techniques, and Applications

Abstract Convolutional neural networks (CNNs) have achieved state-of-the-art performance across computer vision tasks, including image classification, object detection, and medical image analysis. However, the opaque, black-box nature of these models limits their adoption in high-stakes domains such as healthcare, auto...

Ishan Gupta, Gaurav Jangid, Vishal Shrivastava et al. · 0 citations

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