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Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision
Paper • 2312.09390 • Published • 32 -
OneLLM: One Framework to Align All Modalities with Language
Paper • 2312.03700 • Published • 20 -
Generative Multimodal Models are In-Context Learners
Paper • 2312.13286 • Published • 31 -
The LLM Surgeon
Paper • 2312.17244 • Published • 9
Collections
Discover the best community collections!
Collections including paper arxiv:2404.02258
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OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
Paper • 2402.10176 • Published • 33 -
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 50 -
Beyond Language Models: Byte Models are Digital World Simulators
Paper • 2402.19155 • Published • 45 -
Matryoshka Representation Learning
Paper • 2205.13147 • Published • 7
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Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 70 -
An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models
Paper • 2309.09958 • Published • 18 -
Noise-Aware Training of Layout-Aware Language Models
Paper • 2404.00488 • Published • 6 -
Streaming Dense Video Captioning
Paper • 2404.01297 • Published • 10
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Large Language Models as Optimizers
Paper • 2309.03409 • Published • 72 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 102 -
OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework
Paper • 2404.14619 • Published • 122 -
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Paper • 2404.14219 • Published • 238