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Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence
Paper • 2404.05892 • Published • 36 -
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 143 -
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models
Paper • 2404.07839 • Published • 46 -
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention
Paper • 2404.07143 • Published • 107
Collections
Discover the best community collections!
Collections including paper arxiv:2312.00752
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Attention Is All You Need
Paper • 1706.03762 • Published • 55 -
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Paper • 1810.04805 • Published • 17 -
RoBERTa: A Robustly Optimized BERT Pretraining Approach
Paper • 1907.11692 • Published • 7 -
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter
Paper • 1910.01108 • Published • 14
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Vision Mamba: Efficient Visual Representation Learning with Bidirectional State Space Model
Paper • 2401.09417 • Published • 61 -
VMamba: Visual State Space Model
Paper • 2401.10166 • Published • 40 -
DiM: Diffusion Mamba for Efficient High-Resolution Image Synthesis
Paper • 2405.14224 • Published • 16 -
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 143
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Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 143 -
Elucidating the Design Space of Diffusion-Based Generative Models
Paper • 2206.00364 • Published • 15 -
GLU Variants Improve Transformer
Paper • 2002.05202 • Published • 3 -
StarCoder 2 and The Stack v2: The Next Generation
Paper • 2402.19173 • Published • 138
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Attention Is All You Need
Paper • 1706.03762 • Published • 55 -
LLaMA: Open and Efficient Foundation Language Models
Paper • 2302.13971 • Published • 14 -
Efficient Tool Use with Chain-of-Abstraction Reasoning
Paper • 2401.17464 • Published • 20 -
MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts
Paper • 2407.21770 • Published • 22
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Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
Paper • 2404.08801 • Published • 67 -
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models
Paper • 2404.07839 • Published • 46 -
Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence
Paper • 2404.05892 • Published • 36 -
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 143
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Rho-1: Not All Tokens Are What You Need
Paper • 2404.07965 • Published • 90 -
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time
Paper • 2404.10667 • Published • 18 -
Instruction-tuned Language Models are Better Knowledge Learners
Paper • 2402.12847 • Published • 26 -
DoRA: Weight-Decomposed Low-Rank Adaptation
Paper • 2402.09353 • Published • 27
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Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 63 -
A Survey on Data Selection for Language Models
Paper • 2402.16827 • Published • 4 -
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
Paper • 2402.00159 • Published • 62 -
The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only
Paper • 2306.01116 • Published • 34