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Collections including paper arxiv:2404.14047

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 143
Orion-14B: Open-source Multilingual Large Language Models

Paper • 2401.12246 • Published Jan 20 • 11
MambaByte: Token-free Selective State Space Model

Paper • 2401.13660 • Published Jan 24 • 49
MM-LLMs: Recent Advances in MultiModal Large Language Models

Paper • 2401.13601 • Published Jan 24 • 44

XC-Cache: Cross-Attending to Cached Context for Efficient LLM Inference

Paper • 2404.15420 • Published Apr 23 • 7
OpenELM: An Efficient Language Model Family with Open-source Training and Inference Framework

Paper • 2404.14619 • Published Apr 22 • 124
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Paper • 2404.14219 • Published Apr 22 • 251
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22 • 44

Specific Models

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Paper • 2404.14219 • Published Apr 22 • 251
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22 • 44
Octopus v4: Graph of language models

Paper • 2404.19296 • Published Apr 30 • 117

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22 • 44

Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Paper • 2404.14219 • Published Apr 22 • 251
How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22 • 44
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 602

Papers - Llama 3 - GPTQ AWQ PB-LLM BiLLM - 1.1-8 bits LoRA

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22 • 44

Papers - Llama 3 - Fine-tuning

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22 • 44
LiteSearch: Efficacious Tree Search for LLM

Paper • 2407.00320 • Published Jun 29 • 37

Papers - Llama 3 - Fine-tuning - Quantization

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22 • 44

Papers - Llama 3

How Good Are Low-bit Quantized LLaMA3 Models? An Empirical Study

Paper • 2404.14047 • Published Apr 22 • 44
Reasoning in Large Language Models: A Geometric Perspective

Paper • 2407.02678 • Published Jul 2 • 1

The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27 • 602
BitNet: Scaling 1-bit Transformers for Large Language Models

Paper • 2310.11453 • Published Oct 17, 2023 • 96
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2 • 104
TransformerFAM: Feedback attention is working memory

Paper • 2404.09173 • Published Apr 14 • 43

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