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RLHF Workflow: From Reward Modeling to Online RLHF
Paper • 2405.07863 • Published • 67 -
Chameleon: Mixed-Modal Early-Fusion Foundation Models
Paper • 2405.09818 • Published • 126 -
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models
Paper • 2405.15574 • Published • 53 -
An Introduction to Vision-Language Modeling
Paper • 2405.17247 • Published • 85
Collections
Discover the best community collections!
Collections including paper arxiv:2408.12570
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Blending Is All You Need: Cheaper, Better Alternative to Trillion-Parameters LLM
Paper • 2401.02994 • Published • 47 -
MambaByte: Token-free Selective State Space Model
Paper • 2401.13660 • Published • 50 -
Repeat After Me: Transformers are Better than State Space Models at Copying
Paper • 2402.01032 • Published • 22 -
BlackMamba: Mixture of Experts for State-Space Models
Paper • 2402.01771 • Published • 23
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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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Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Paper • 2405.21060 • Published • 63 -
Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models
Paper • 2406.04320 • Published • 7 -
MambaMixer: Efficient Selective State Space Models with Dual Token and Channel Selection
Paper • 2403.19888 • Published • 10 -
Graph Mamba: Towards Learning on Graphs with State Space Models
Paper • 2402.08678 • Published • 13
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Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
Paper • 2404.08801 • Published • 63 -
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models
Paper • 2404.07839 • Published • 41 -
Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence
Paper • 2404.05892 • Published • 31 -
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
Paper • 2312.00752 • Published • 138
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Rho-1: Not All Tokens Are What You Need
Paper • 2404.07965 • Published • 84 -
VASA-1: Lifelike Audio-Driven Talking Faces Generated in Real Time
Paper • 2404.10667 • Published • 17 -
Instruction-tuned Language Models are Better Knowledge Learners
Paper • 2402.12847 • Published • 24 -
DoRA: Weight-Decomposed Low-Rank Adaptation
Paper • 2402.09353 • Published • 26
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OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 80 -
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Paper • 2403.05530 • Published • 60 -
StarCoder: may the source be with you!
Paper • 2305.06161 • Published • 29 -
SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling
Paper • 2312.15166 • Published • 56
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Non-asymptotic oracle inequalities for the Lasso in high-dimensional mixture of experts
Paper • 2009.10622 • Published • 1 -
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models
Paper • 2401.15947 • Published • 48 -
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts
Paper • 2401.04081 • Published • 70 -
MoE-Infinity: Activation-Aware Expert Offloading for Efficient MoE Serving
Paper • 2401.14361 • Published • 2
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Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
Paper • 2402.04248 • Published • 30 -
Scavenging Hyena: Distilling Transformers into Long Convolution Models
Paper • 2401.17574 • Published • 15 -
Scalable Autoregressive Image Generation with Mamba
Paper • 2408.12245 • Published • 23 -
Jamba-1.5: Hybrid Transformer-Mamba Models at Scale
Paper • 2408.12570 • Published • 29