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Can Large Language Models Understand Context?
Paper • 2402.00858 • Published • 22 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 82 -
Self-Rewarding Language Models
Paper • 2401.10020 • Published • 145 -
SemScore: Automated Evaluation of Instruction-Tuned LLMs based on Semantic Textual Similarity
Paper • 2401.17072 • Published • 25
Collections
Discover the best community collections!
Collections including paper arxiv:2403.03853
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ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
Paper • 2403.03853 • Published • 61 -
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Paper • 2401.15024 • Published • 69 -
Your Transformer is Secretly Linear
Paper • 2405.12250 • Published • 149 -
Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 62
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MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training
Paper • 2403.09611 • Published • 125 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 31 -
ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
Paper • 2403.03853 • Published • 61 -
LLM-ABR: Designing Adaptive Bitrate Algorithms via Large Language Models
Paper • 2404.01617 • Published • 6
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Scaling Instruction-Finetuned Language Models
Paper • 2210.11416 • Published • 7 -
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 138 -
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Paper • 2403.05530 • Published • 61 -
Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 62
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ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
Paper • 2403.03853 • Published • 61 -
Revisiting In-Context Learning with Long Context Language Models
Paper • 2412.16926 • Published • 27 -
Rethinking Addressing in Language Models via Contexualized Equivariant Positional Encoding
Paper • 2501.00712 • Published • 4
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ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
Paper • 2403.03853 • Published • 61 -
SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks
Paper • 2402.09025 • Published • 6 -
Shortened LLaMA: A Simple Depth Pruning for Large Language Models
Paper • 2402.02834 • Published • 14 -
Algorithmic progress in language models
Paper • 2403.05812 • Published • 18
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ShortGPT: Layers in Large Language Models are More Redundant Than You Expect
Paper • 2403.03853 • Published • 61 -
SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shot
Paper • 2301.00774 • Published • 3 -
The LLM Surgeon
Paper • 2312.17244 • Published • 9 -
SliceGPT: Compress Large Language Models by Deleting Rows and Columns
Paper • 2401.15024 • Published • 69