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Research & Development
Advancing Diabetic Retinopathy Screening Through Responsible AI Development
TLDR: A new Responsible AI System (RAIS-DR) has been developed and validated for diabetic retinopathy (DR) screening. It integrates ethical principles throughout its design,...
Research & Development
Fine-tuning LLMs: Safety Through Smarter Training
TLDR: A new research paper challenges the common belief that fine-tuning inevitably harms LLM safety. Instead, it argues that poor optimization choices are often...
Research & Development
OS-R1: Reinforcement Learning Powers Intelligent Linux Kernel Optimization
TLDR: OS-R1 is a new framework that uses rule-based reinforcement learning to automate Linux kernel tuning. It models kernel configuration as an RL environment,...
Research & Development
Network Width Reduces Data Heterogeneity Impact in Federated Learning
TLDR: A new research paper demonstrates that increasing the width of neural networks significantly reduces the negative impact of data heterogeneity in Federated Learning...
Research & Development
Bridging the Language Divide: How Code-Switching Improves LLM Performance
TLDR: A research paper demonstrates that fine-tuning Large Language Models (LLMs) on synthetic code-switched text (mixing languages like Hindi and English) significantly improves their...
Research & Development
A New Defense Against Adversarial Attacks in Federated Learning
TLDR: A new Federated Learning (FL) algorithm, 'Loss-Based Client Clustering,' enhances robustness against adversarial attacks like label flipping, sign flipping, and Gaussian noise. It...