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RLHF Workflow: From Reward Modeling to Online RLHF
Paper • 2405.07863 • Published • 67 -
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 • 53 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 85
Collections
Discover the best community collections!
Collections including paper arxiv:2407.16674
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KAN or MLP: A Fairer Comparison
Paper • 2407.16674 • Published • 41 -
MathScale: Scaling Instruction Tuning for Mathematical Reasoning
Paper • 2403.02884 • Published • 15 -
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
Paper • 2402.13064 • Published • 46 -
DPTDR: Deep Prompt Tuning for Dense Passage Retrieval
Paper • 2208.11503 • Published
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Just How Flexible are Neural Networks in Practice?
Paper • 2406.11463 • Published • 7 -
Not All Language Model Features Are Linear
Paper • 2405.14860 • Published • 39 -
KAN: Kolmogorov-Arnold Networks
Paper • 2404.19756 • Published • 108 -
An Interactive Agent Foundation Model
Paper • 2402.05929 • Published • 27
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MobileCLIP: Fast Image-Text Models through Multi-Modal Reinforced Training
Paper • 2311.17049 • Published -
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Paper • 2405.04434 • Published • 13 -
A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision
Paper • 2303.17376 • Published -
Sigmoid Loss for Language Image Pre-Training
Paper • 2303.15343 • Published • 4
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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