Visit IGEN World Explore IGEN Expo

EXPLORE UPGRADE PLANS

BREAKING

Language-Guided AI Framework CLARITY Boosts Road Scene Segmentation for Autonomous Logistics When RAG Hurts: Research Identifies Attention Distraction in Vision-Language AI Models and Proposes Mitigation Strait of Hormuz Reopening: Mine Clearance Delays Threaten Weeks-Long Recovery for Oil Shipping India’s REITs and InvITs May Attract Rs 11.6 Lakh Crore Investment by 2030, Avendus Report Says DualGauge: Automated Joint Security-Functionality Benchmarking of Specification-Only Code Generation by LLMs and Coding Agents Nimble SharePower: Modular Power Bank Lets You Share a Charge With a Friend OBCache Prunes KV Cache for Efficient Long-Context LLM Inference with Output-Aware Scoring 'Dangerous' AI Models: Enterprise Leaders Must Prepare for Broad Availability Air India Launches 'Basic Fare' Option Without Complimentary Meals on Select Domestic Flights New Survey Maps How Evidence Tracing and Execution Provenance Can Make LLM Agents Trustworthy Language-Guided AI Framework CLARITY Boosts Road Scene Segmentation for Autonomous Logistics When RAG Hurts: Research Identifies Attention Distraction in Vision-Language AI Models and Proposes Mitigation Strait of Hormuz Reopening: Mine Clearance Delays Threaten Weeks-Long Recovery for Oil Shipping India’s REITs and InvITs May Attract Rs 11.6 Lakh Crore Investment by 2030, Avendus Report Says DualGauge: Automated Joint Security-Functionality Benchmarking of Specification-Only Code Generation by LLMs and Coding Agents Nimble SharePower: Modular Power Bank Lets You Share a Charge With a Friend OBCache Prunes KV Cache for Efficient Long-Context LLM Inference with Output-Aware Scoring 'Dangerous' AI Models: Enterprise Leaders Must Prepare for Broad Availability Air India Launches 'Basic Fare' Option Without Complimentary Meals on Select Domestic Flights New Survey Maps How Evidence Tracing and Execution Provenance Can Make LLM Agents Trustworthy

Home ›› Topics ›› sdflora

Topic

sdflora

1 story

SDFLoRA: Selective Decoupled Federated LoRA for Privacy-Preserving Fine-Tuning with Heterogeneous Clients

Artificial Intelligence #federated learning#lora

SDFLoRA: Selective Decoupled Federated LoRA for Privacy-Preserving Fine-Tuning with Heterogeneous Clients

Federated learning for LLMs faces challenges from heterogeneous client ranks and data distributions. SDFLoRA proposes a structure-aware LoRA framework that decouples updates into shared and private components, enabling stable aggregation, personalization, and improved differential privacy. Experiments show it outperforms existing federated LoRA baselines.

Jun 16, 2026 1 source