iGEN
Visit IGEN World Explore IGEN Expo
EXPLORE UPGRADE PLANS
BREAKING
Retrieval-Augmented Generation Boosts LLM Personalization for Enterprise Reading Content Unassigned Agents in Multi-Agent Path Finding Addressed by Compilation-Based Solvers New Framework Reduces Visual Hallucinations in Multimodal AI Systems Without Retraining MAF Framework Dynamically Optimizes Prompting for Multimodal Sentiment Analysis Study on Pedestrian Attribute Recognition Identifies Sparsity Wall and Optimizes Edge Deployment AI Framework Targets 50% Water Loss in Jordan with LLM and Digital Twin Integration AnonShield: Scalable On-Premise Pseudonymization Cuts Vulnerability Data Processing from 92 Hours to Under 10 Minutes MoFore: A New Self-Supervised Framework Learns Video Representations by Forecasting Future Latent Embeddings Do LLMs Reliably Identify Correct Information Units in Aphasic Discourse? A New Study Evaluates Four Models AI Video Generation Method for Cardiac MRI Addresses Data Scarcity with Latent Motion Modeling Retrieval-Augmented Generation Boosts LLM Personalization for Enterprise Reading Content Unassigned Agents in Multi-Agent Path Finding Addressed by Compilation-Based Solvers New Framework Reduces Visual Hallucinations in Multimodal AI Systems Without Retraining MAF Framework Dynamically Optimizes Prompting for Multimodal Sentiment Analysis Study on Pedestrian Attribute Recognition Identifies Sparsity Wall and Optimizes Edge Deployment AI Framework Targets 50% Water Loss in Jordan with LLM and Digital Twin Integration AnonShield: Scalable On-Premise Pseudonymization Cuts Vulnerability Data Processing from 92 Hours to Under 10 Minutes MoFore: A New Self-Supervised Framework Learns Video Representations by Forecasting Future Latent Embeddings Do LLMs Reliably Identify Correct Information Units in Aphasic Discourse? A New Study Evaluates Four Models AI Video Generation Method for Cardiac MRI Addresses Data Scarcity with Latent Motion Modeling
Home ›› Topics ›› foundation models

Topic

foundation models

2 stories
A Theoretical Roadmap to Fuse Foundation Models and Knowledge Graphs Technology
Artificial Intelligence #foundation models#knowledge graphs

A Theoretical Roadmap to Fuse Foundation Models and Knowledge Graphs

A new theoretical paper formalizes the 'Impedance Mismatch' between Foundation Models and Knowledge Graphs, arguing that current approaches like RAG are superficial. The authors propose a roadmap including Structured Residual Streams, Vector Symbolic Architectures, and Orthogonal Subspace Editing for true semantic fusion.

Jun 16, 2026 1 source
GeoRoPE: Ground-Aware Rotary Adaptation Enhances Remote Sensing Foundation Models Technology
Artificial Intelligence #remote sensing#foundation models

GeoRoPE: Ground-Aware Rotary Adaptation Enhances Remote Sensing Foundation Models

A new research paper introduces GeoRoPE, a ground-aware rotary adaptation method for remote sensing foundation models. It addresses scale mismatch by recalibrating token-level positional interactions, improving cross-resolution robustness and scale-sensitive representation learning. The method is parameter-efficient and compatible with existing models.

Jun 16, 2026 1 source