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Rethinking Optimization and Architecture for Tiny Language Models
Paper • 2402.02791 • Published • 13 -
More Agents Is All You Need
Paper • 2402.05120 • Published • 53 -
Scaling Laws for Forgetting When Fine-Tuning Large Language Models
Paper • 2401.05605 • Published -
Aligning Large Language Models with Counterfactual DPO
Paper • 2401.09566 • Published • 2
Collections
Discover the best community collections!
Collections including paper arxiv:2403.03507
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Transformer^2: Self-adaptive LLMs
Paper • 2501.06252 • Published • 53 -
s1: Simple test-time scaling
Paper • 2501.19393 • Published • 100 -
Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling
Paper • 2502.06703 • Published • 114 -
Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models
Paper • 2501.12370 • Published • 10
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Paper • 1910.10683 • Published • 11 -
AutoTrain: No-code training for state-of-the-art models
Paper • 2410.15735 • Published • 59 -
LoRA Land: 310 Fine-tuned LLMs that Rival GPT-4, A Technical Report
Paper • 2405.00732 • Published • 120 -
LoRA: Low-Rank Adaptation of Large Language Models
Paper • 2106.09685 • Published • 32
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SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding
Paper • 2408.15545 • Published • 35 -
Controllable Text Generation for Large Language Models: A Survey
Paper • 2408.12599 • Published • 64 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 42 -
Automated Design of Agentic Systems
Paper • 2408.08435 • Published • 39
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Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 140 -
Elucidating the Design Space of Diffusion-Based Generative Models
Paper • 2206.00364 • Published • 15 -
GLU Variants Improve Transformer
Paper • 2002.05202 • Published • 2 -
StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 137