Author: Mohammad Asjad

Mohammad Asjad
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Asjad is an intern consultant at Marktechpost. He is persuing B.Tech in mechanical engineering at the Indian Institute of Technology, Kharagpur. Asjad is a Machine learning and deep learning enthusiast who is always researching the applications of machine learning in healthcare.

Characterizing and Mitigating Compute Express Link (CXL) Interference in Modern Memory Systems

AI Paper Summary
Compute Express Link (CXL) emerges as an innovative technological solution addressing critical memory wall challenges in modern computing infrastructures. The interconnect technology presents a...

ShowUI: A Vision-Language-Action Model for GUI Visual Agents that Addresses Key Challenges in UI Visual and Action Modeling

AI Paper Summary
Large Language Models (LLMs) have demonstrated remarkable potential in performing complex tasks by building intelligent agents. As individuals increasingly engage with the digital world,...

Geometry Distributions: Advancing Neural 3D Surface Modeling with Diffusion Models

AI Paper Summary
Geometry representations play a crucial role in solving complex 3D vision problems. The rapid evolution of deep learning has sparked significant interest in developing...

SEALONG: A Self-Improving AI Approach to Long-Context Reasoning in Large Language Models

AI Paper Summary
Large language models (LLMs) with long-context processing capabilities have revolutionized technological applications across multiple domains. Recent advancements have enabled sophisticated use cases including repository-level...

Quantum Neuromorphic Computing: Implementing Scalable Quantum Perceptrons

AI Paper Summary
Quantum and neuromorphic computing represent phenomenal computational paradigms that promise transformative technological advances. Quantum computing utilizes unique quantum phenomena like entanglement and superposition to...

Red Teaming for AI: Strengthening Safety and Trust through External Evaluation

AI Agents
Red teaming plays a pivotal role in evaluating the risks associated with AI models and systems. It uncovers novel threats, identifies gaps in current...

KuaiFormer: A Transformer-Based Architecture for Large-Scale Short-Video Recommendation Systems

AI Paper Summary
Language and vision models have experienced remarkable breakthroughs with the advent of Transformer architecture. Models like BERT and GPT have revolutionized natural language processing,...

Artificial Intelligence AI and Quantum Computing: Transforming Computational Frontiers

AI Paper Summary
Quantum computing (QC) stands at the forefront of technological innovation, promising transformative potential across scientific and industrial domains. Researchers recognize that realizing this potential...

Deep Learning Meets Cybersecurity: A Hybrid Approach to Detecting DDoS Attacks with Unmatched Accuracy

AI Paper Summary
The proliferation of websites across various domains of everyday life has led to a significant rise in cybersecurity threats. The complexity and frequency of...

Stanford Researchers Propose ‘POSR’: A Unique AI Framework for Analyzing Educational Conversations Using Joint Segmentation and Retrieval

AI Paper Summary
Effective lesson structuring remains a critical challenge in educational settings, particularly when conversations and tutoring sessions need to address predefined topics or worksheet problems....

H-DPO: Advancing Language Model Alignment through Entropy Control

AI Paper Summary
Large Language Models (LLMs) have demonstrated exceptional capabilities across diverse applications, but their widespread adoption faces significant challenges. The primary concern stems from training...

Meet OpenCoder: A Completely Open-Source Code LLM Built on the Transparent Data Process Pipeline and Reproducible Dataset

AI Paper Summary
Large Language Models (LLMs) have revolutionized various domains, with a particularly transformative impact on software development through code-related tasks. The emergence of tools like...
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