Collections
Discover the best community collections!
Collections including paper arxiv:2504.05897
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Low-Rank Adapters Meet Neural Architecture Search for LLM Compression
Paper • 2501.16372 • Published • 12 -
TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models
Paper • 2501.16937 • Published • 7 -
Matryoshka Quantization
Paper • 2502.06786 • Published • 32 -
Identifying Sensitive Weights via Post-quantization Integral
Paper • 2503.01901 • Published • 8
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The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 625 -
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 105 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 107 -
TransformerFAM: Feedback attention is working memory
Paper • 2404.09173 • Published • 43
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LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 34 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 27 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 126 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 22
-
Low-Rank Adapters Meet Neural Architecture Search for LLM Compression
Paper • 2501.16372 • Published • 12 -
TAID: Temporally Adaptive Interpolated Distillation for Efficient Knowledge Transfer in Language Models
Paper • 2501.16937 • Published • 7 -
Matryoshka Quantization
Paper • 2502.06786 • Published • 32 -
Identifying Sensitive Weights via Post-quantization Integral
Paper • 2503.01901 • Published • 8
-
LinFusion: 1 GPU, 1 Minute, 16K Image
Paper • 2409.02097 • Published • 34 -
Phidias: A Generative Model for Creating 3D Content from Text, Image, and 3D Conditions with Reference-Augmented Diffusion
Paper • 2409.11406 • Published • 27 -
Diffusion Models Are Real-Time Game Engines
Paper • 2408.14837 • Published • 126 -
Segment Anything with Multiple Modalities
Paper • 2408.09085 • Published • 22
-
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 625 -
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 105 -
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models
Paper • 2404.02258 • Published • 107 -
TransformerFAM: Feedback attention is working memory
Paper • 2404.09173 • Published • 43