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Scaling Autoregressive Models for Content-Rich Text-to-Image Generation
Paper • 2206.10789 • Published • 4 -
Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws
Paper • 2401.00448 • Published • 28 -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 10 -
Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 6
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Collections including paper arxiv:2203.15556
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Scaling Laws for Neural Language Models
Paper • 2001.08361 • Published • 6 -
Scaling Laws for Autoregressive Generative Modeling
Paper • 2010.14701 • Published -
Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 10 -
A Survey on Data Selection for Language Models
Paper • 2402.16827 • Published • 4
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Qwen2.5-Coder Technical Report
Paper • 2409.12186 • Published • 125 -
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
Paper • 2409.12122 • Published • 1 -
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Paper • 2405.04434 • Published • 13 -
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Paper • 2402.03300 • Published • 69
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SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding
Paper • 2408.15545 • Published • 34 -
Controllable Text Generation for Large Language Models: A Survey
Paper • 2408.12599 • Published • 62 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 40 -
Automated Design of Agentic Systems
Paper • 2408.08435 • Published • 38
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Self-Play Preference Optimization for Language Model Alignment
Paper • 2405.00675 • Published • 24 -
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
Paper • 2205.14135 • Published • 11 -
Attention Is All You Need
Paper • 1706.03762 • Published • 44 -
FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning
Paper • 2307.08691 • Published • 8
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SELF: Language-Driven Self-Evolution for Large Language Model
Paper • 2310.00533 • Published • 2 -
GrowLength: Accelerating LLMs Pretraining by Progressively Growing Training Length
Paper • 2310.00576 • Published • 2 -
A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity
Paper • 2305.13169 • Published • 3 -
Transformers Can Achieve Length Generalization But Not Robustly
Paper • 2402.09371 • Published • 12
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TinyLLaVA: A Framework of Small-scale Large Multimodal Models
Paper • 2402.14289 • Published • 19 -
ImageBind: One Embedding Space To Bind Them All
Paper • 2305.05665 • Published • 3 -
DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 181 -
Multimodal Contrastive Learning with LIMoE: the Language-Image Mixture of Experts
Paper • 2206.02770 • Published • 3
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Measuring the Effects of Data Parallelism on Neural Network Training
Paper • 1811.03600 • Published • 2 -
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost
Paper • 1804.04235 • Published • 2 -
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Paper • 1905.11946 • Published • 3 -
Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 62
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Training Compute-Optimal Large Language Models
Paper • 2203.15556 • Published • 10 -
Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism
Paper • 1909.08053 • Published • 2 -
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Paper • 1910.10683 • Published • 8 -
Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling
Paper • 2304.01373 • Published • 8