Home Console Docs News Papers Tutorials Datasets Wiki SOTA LLM Models GPU Leaderboard Events

English

Visual Reasoning On Nlvr2 Dev

Metrics

Accuracy

Results

Performance results of various models on this benchmark

		Paper Title	Repository
BEiT-3	91.51	Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks
X2-VLM (large)	88.7	X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks
XFM (base)	87.6	Toward Building General Foundation Models for Language, Vision, and Vision-Language Understanding Tasks
X2-VLM (base)	86.2	X$^2$-VLM: All-In-One Pre-trained Model For Vision-Language Tasks
CoCa	86.1	CoCa: Contrastive Captioners are Image-Text Foundation Models
VLMo	85.64	VLMo: Unified Vision-Language Pre-Training with Mixture-of-Modality-Experts
VK-OOD	84.6	Implicit Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis	-
SimVLM	84.53	SimVLM: Simple Visual Language Model Pretraining with Weak Supervision
X-VLM (base)	84.41	Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts
VK-OOD	83.9	Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis
ALBEF (14M)	83.14	Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
SOHO	76.37	Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning
ViLT-B/32	75.7	ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
LXMERT (Pre-train + scratch)	74.9	LXMERT: Learning Cross-Modality Encoder Representations from Transformers
VisualBERT	66.7	VisualBERT: A Simple and Performant Baseline for Vision and Language

0 of 15 row(s) selected.