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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 146 -
Orion-14B: Open-source Multilingual Large Language Models
Paper • 2401.12246 • Published • 13 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 54 -
MM-LLMs: Recent Advances in MultiModal Large Language Models
Paper • 2401.13601 • Published • 47
Collections
Discover the best community collections!
Collections including paper arxiv:2408.06663
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Jamba: A Hybrid Transformer-Mamba Language Model
Paper • 2403.19887 • Published • 107 -
Aurora-M: The First Open Source Multilingual Language Model Red-teamed according to the U.S. Executive Order
Paper • 2404.00399 • Published • 42 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 104 -
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
Paper • 2404.08801 • Published • 66
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Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset
Paper • 2403.09029 • Published • 55 -
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
Paper • 2403.12968 • Published • 25 -
RAFT: Adapting Language Model to Domain Specific RAG
Paper • 2403.10131 • Published • 69 -
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking
Paper • 2403.09629 • Published • 76
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 26 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 13 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 41 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 22
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Partially Rewriting a Transformer in Natural Language
Paper • 2501.18838 • Published • 1 -
AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders
Paper • 2501.17148 • Published • 1 -
Sparse Autoencoders Trained on the Same Data Learn Different Features
Paper • 2501.16615 • Published • 1 -
Open Problems in Mechanistic Interpretability
Paper • 2501.16496 • Published • 16