REAL-MM-RAG-Bench Collection REAL-MM-RAG-Bench is a benchmark designed to evaluate multi-modal retrieval models under realistic and challenging conditions. • 4 items • Updated about 17 hours ago • 3
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks Paper • 1811.10597 • Published Nov 26, 2018
Semantic Photo Manipulation with a Generative Image Prior Paper • 2005.07727 • Published May 15, 2020
Understanding the Role of Individual Units in a Deep Neural Network Paper • 2009.05041 • Published Sep 10, 2020
The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics Paper • 2102.01672 • Published Feb 2, 2021
LeGrad: An Explainability Method for Vision Transformers via Feature Formation Sensitivity Paper • 2404.03214 • Published Apr 4, 2024 • 2
Detectors for Safe and Reliable LLMs: Implementations, Uses, and Limitations Paper • 2403.06009 • Published Mar 9, 2024
Granite Vision: a lightweight, open-source multimodal model for enterprise Intelligence Paper • 2502.09927 • Published 28 days ago
Ladder-residual: parallelism-aware architecture for accelerating large model inference with communication overlapping Paper • 2501.06589 • Published Jan 11