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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 144 -
Orion-14B: Open-source Multilingual Large Language Models
Paper • 2401.12246 • Published • 12 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 51 -
MM-LLMs: Recent Advances in MultiModal Large Language Models
Paper • 2401.13601 • Published • 45
Collections
Discover the best community collections!
Collections including paper arxiv:2407.07304
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The Impact of Hyperparameters on Large Language Model Inference Performance: An Evaluation of vLLM and HuggingFace Pipelines
Paper • 2408.01050 • Published • 8 -
Efficient Inference of Vision Instruction-Following Models with Elastic Cache
Paper • 2407.18121 • Published • 15 -
LazyLLM: Dynamic Token Pruning for Efficient Long Context LLM Inference
Paper • 2407.14057 • Published • 44 -
Q-Sparse: All Large Language Models can be Fully Sparsely-Activated
Paper • 2407.10969 • Published • 20
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How Do Large Language Models Acquire Factual Knowledge During Pretraining?
Paper • 2406.11813 • Published • 30 -
From RAGs to rich parameters: Probing how language models utilize external knowledge over parametric information for factual queries
Paper • 2406.12824 • Published • 20 -
Tokenization Falling Short: The Curse of Tokenization
Paper • 2406.11687 • Published • 15 -
Iterative Length-Regularized Direct Preference Optimization: A Case Study on Improving 7B Language Models to GPT-4 Level
Paper • 2406.11817 • Published • 13
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XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference
Paper • 2404.15420 • Published • 7 -
OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework
Paper • 2404.14619 • Published • 124 -
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Paper • 2404.14219 • Published • 253 -
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study
Paper • 2404.14047 • Published • 44