Collection by
May 13
May 13
Collections
Discover the best community collections!
Collections including paper arxiv:2402.05008
Collection by
Mar 19
Mar 19
Collection by
Mar 5
Mar 5
Collection by
3 days ago
3 days ago
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 25 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 12 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 36 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 19
Collection by
Mar 25
Mar 25
Collection by
Apr 10
Apr 10
-
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 19 -
PALO: A Polyglot Large Multimodal Model for 5B People
Paper • 2402.14818 • Published • 23 -
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 124 -
InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD
Paper • 2404.06512 • Published • 29
Collection by
May 28
May 28
-
DiarizationLM: Speaker Diarization Post-Processing with Large Language Models
Paper • 2401.03506 • Published • 13 -
CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution
Paper • 2401.03065 • Published • 10 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 19 -
Beyond A*: Better Planning with Transformers via Search Dynamics Bootstrapping
Paper • 2402.14083 • Published • 43
Collection by
Mar 4
Mar 4
-
Let's Go Shopping (LGS) -- Web-Scale Image-Text Dataset for Visual Concept Understanding
Paper • 2401.04575 • Published • 14 -
Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
Paper • 2401.09417 • Published • 58 -
VMamba: Visual State Space Model
Paper • 2401.10166 • Published • 37 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 19