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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 24 -
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
Collections
Discover the best community collections!
Collections including paper arxiv:2407.01284
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RLHF Workflow: From Reward Modeling to Online RLHF
Paper • 2405.07863 • Published • 65 -
Chameleon: Mixed-Modal Early-Fusion Foundation Models
Paper • 2405.09818 • Published • 125 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 52 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 84
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SpreadsheetLLM: Encoding Spreadsheets for Large Language Models
Paper • 2407.09025 • Published • 120 -
Human-like Episodic Memory for Infinite Context LLMs
Paper • 2407.09450 • Published • 56 -
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models
Paper • 2407.05131 • Published • 22 -
We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?
Paper • 2407.01284 • Published • 75
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Unlocking Continual Learning Abilities in Language Models
Paper • 2406.17245 • Published • 27 -
A Closer Look into Mixture-of-Experts in Large Language Models
Paper • 2406.18219 • Published • 15 -
Symbolic Learning Enables Self-Evolving Agents
Paper • 2406.18532 • Published • 10 -
Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Paper • 2406.18629 • Published • 38
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CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs
Paper • 2406.18521 • Published • 25 -
We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?
Paper • 2407.01284 • Published • 75 -
ChartGemma: Visual Instruction-tuning for Chart Reasoning in the Wild
Paper • 2407.04172 • Published • 22
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BLINK: Multimodal Large Language Models Can See but Not Perceive
Paper • 2404.12390 • Published • 24 -
SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension
Paper • 2404.16790 • Published • 7 -
Plot2Code: A Comprehensive Benchmark for Evaluating Multi-modal Large Language Models in Code Generation from Scientific Plots
Paper • 2405.07990 • Published • 16 -
MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding
Paper • 2406.09411 • Published • 18
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CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data
Paper • 2404.15653 • Published • 26 -
MoDE: CLIP Data Experts via Clustering
Paper • 2404.16030 • Published • 12 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 45 -
Reducing Transformer Key-Value Cache Size with Cross-Layer Attention
Paper • 2405.12981 • Published • 28
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Advancing LLM Reasoning Generalists with Preference Trees
Paper • 2404.02078 • Published • 43 -
ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline
Paper • 2404.02893 • Published • 19 -
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Paper • 2309.12284 • Published • 18 -
Premise Order Matters in Reasoning with Large Language Models
Paper • 2402.08939 • Published • 24
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MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?
Paper • 2403.14624 • Published • 50 -
Challenge LLMs to Reason About Reasoning: A Benchmark to Unveil Cognitive Depth in LLMs
Paper • 2312.17080 • Published • 1 -
We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?
Paper • 2407.01284 • Published • 75
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MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?
Paper • 2403.14624 • Published • 50 -
We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?
Paper • 2407.01284 • Published • 75 -
MAVIS: Mathematical Visual Instruction Tuning
Paper • 2407.08739 • Published • 30