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Collections including paper arxiv:2403.08763

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

Paper • 2402.17764 • Published Feb 27 • 566
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Paper • 2403.03507 • Published Mar 6 • 172
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29 • 49
ResLoRA: Identity Residual Mapping in Low-Rank Adaption

Paper • 2402.18039 • Published Feb 28 • 10

Simple and Scalable Strategies to Continually Pre-train Large Language Models

Paper • 2403.08763 • Published Mar 13 • 48

Simple and Scalable Strategies to Continually Pre-train Large Language Models

Paper • 2403.08763 • Published Mar 13 • 48

Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset

Paper • 2403.09029 • Published Mar 14 • 52
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression

Paper • 2403.12968 • Published Mar 19 • 20
RAFT: Adapting Language Model to Domain Specific RAG

Paper • 2403.10131 • Published Mar 15 • 62
Quiet-STaR: Language Models Can Teach Themselves to Think Before Speaking

Paper • 2403.09629 • Published Mar 14 • 54

Simple and Scalable Strategies to Continually Pre-train Large Language Models

Paper • 2403.08763 • Published Mar 13 • 48
Jamba: A Hybrid Transformer-Mamba Language Model

Paper • 2403.19887 • Published Mar 28 • 99
Transformer-Lite: High-efficiency Deployment of Large Language Models on Mobile Phone GPUs

Paper • 2403.20041 • Published Mar 29 • 34
Advancing LLM Reasoning Generalists with Preference Trees

Paper • 2404.02078 • Published Apr 2 • 41

Simple and Scalable Strategies to Continually Pre-train Large Language Models

Paper • 2403.08763 • Published Mar 13 • 48

Continual training

Simple and Scalable Strategies to Continually Pre-train Large Language Models

Paper • 2403.08763 • Published Mar 13 • 48

Simple and Scalable Strategies to Continually Pre-train Large Language Models

Paper • 2403.08763 • Published Mar 13 • 48

Simple and Scalable Strategies to Continually Pre-train Large Language Models

Paper • 2403.08763 • Published Mar 13 • 48

Simple and Scalable Strategies to Continually Pre-train Large Language Models

Paper • 2403.08763 • Published Mar 13 • 48
Language models scale reliably with over-training and on downstream tasks

Paper • 2403.08540 • Published Mar 13 • 13
PLLaVA : Parameter-free LLaVA Extension from Images to Videos for Video Dense Captioning

Paper • 2404.16994 • Published 25 days ago • 30

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