Beyond Language Models: Byte Models are Digital World Simulators
Paper
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2402.19155
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Published
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45
Papers
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Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models
Paper • 2402.19427 • Published • 50 -
VisionLLaMA: A Unified LLaMA Interface for Vision Tasks
Paper • 2403.00522 • Published • 40 -
Resonance RoPE: Improving Context Length Generalization of Large Language Models
Paper • 2403.00071 • Published • 19 -
Learning and Leveraging World Models in Visual Representation Learning
Paper • 2403.00504 • Published • 25 -
AtP*: An efficient and scalable method for localizing LLM behaviour to components
Paper • 2403.00745 • Published • 8 -
Learning to Decode Collaboratively with Multiple Language Models
Paper • 2403.03870 • Published • 17 -
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
Paper • 2403.03853 • Published • 61 -
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection
Paper • 2403.03507 • Published • 176 -
ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment
Paper • 2403.05135 • Published • 39 -
DeepSeek-VL: Towards Real-World Vision-Language Understanding
Paper • 2403.05525 • Published • 38 -
Stealing Part of a Production Language Model
Paper • 2403.06634 • Published • 85 -
MoAI: Mixture of All Intelligence for Large Language and Vision Models
Paper • 2403.07508 • Published • 71 -
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM
Paper • 2403.07816 • Published • 37 -
Synth^2: Boosting Visual-Language Models with Synthetic Captions and Image Embeddings
Paper • 2403.07750 • Published • 19 -
Chronos: Learning the Language of Time Series
Paper • 2403.07815 • Published • 43 -
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 122 -
Veagle: Advancements in Multimodal Representation Learning
Paper • 2403.08773 • Published • 7 -
Qwen Technical Report
Paper • 2309.16609 • Published • 30 -
Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities
Paper • 2308.12966 • Published • 6 -
Uni-SMART: Universal Science Multimodal Analysis and Research Transformer
Paper • 2403.10301 • Published • 50 -
LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models
Paper • 2403.13372 • Published • 57 -
The Unreasonable Ineffectiveness of the Deeper Layers
Paper • 2403.17887 • Published • 75 -
InternLM2 Technical Report
Paper • 2403.17297 • Published • 25 -
Jamba: A Hybrid Transformer-Mamba Language Model
Paper • 2403.19887 • Published • 99 -
Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs
Paper • 2403.20041 • Published • 34 -
Localizing Paragraph Memorization in Language Models
Paper • 2403.19851 • Published • 13 -
DiJiang: Efficient Large Language Models through Compact Kernelization
Paper • 2403.19928 • Published • 9 -
Long-form factuality in large language models
Paper • 2403.18802 • Published • 23 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 102 -
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention
Paper • 2404.07143 • Published • 93 -
Pre-training Small Base LMs with Fewer Tokens
Paper • 2404.08634 • Published • 32 -
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
Paper • 2404.08801 • Published • 62 -
SnapKV: LLM Knows What You are Looking for Before Generation
Paper • 2404.14469 • Published • 23 -
FlowMind: Automatic Workflow Generation with LLMs
Paper • 2404.13050 • Published • 32