Collections
Discover the best community collections!
Collections including paper arxiv:2504.19720
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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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LLMs + Persona-Plug = Personalized LLMs
Paper • 2409.11901 • Published • 35 -
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning
Paper • 2409.12183 • Published • 39 -
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
Paper • 2402.12875 • Published • 13 -
TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices
Paper • 2410.00531 • Published • 34
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I-Con: A Unifying Framework for Representation Learning
Paper • 2504.16929 • Published • 29 -
LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Paper • 2504.16078 • Published • 21 -
WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents
Paper • 2504.15785 • Published • 21 -
OTC: Optimal Tool Calls via Reinforcement Learning
Paper • 2504.14870 • Published • 35
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MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 302 -
Scalable-Softmax Is Superior for Attention
Paper • 2501.19399 • Published • 22 -
FastKV: KV Cache Compression for Fast Long-Context Processing with Token-Selective Propagation
Paper • 2502.01068 • Published • 18 -
Scaling Embedding Layers in Language Models
Paper • 2502.01637 • Published • 24
-
I-Con: A Unifying Framework for Representation Learning
Paper • 2504.16929 • Published • 29 -
LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities
Paper • 2504.16078 • Published • 21 -
WALL-E 2.0: World Alignment by NeuroSymbolic Learning improves World Model-based LLM Agents
Paper • 2504.15785 • Published • 21 -
OTC: Optimal Tool Calls via Reinforcement Learning
Paper • 2504.14870 • Published • 35
-
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
-
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper • 2501.08313 • Published • 302 -
Scalable-Softmax Is Superior for Attention
Paper • 2501.19399 • Published • 22 -
FastKV: KV Cache Compression for Fast Long-Context Processing with Token-Selective Propagation
Paper • 2502.01068 • Published • 18 -
Scaling Embedding Layers in Language Models
Paper • 2502.01637 • Published • 24
-
LLMs + Persona-Plug = Personalized LLMs
Paper • 2409.11901 • Published • 35 -
To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning
Paper • 2409.12183 • Published • 39 -
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
Paper • 2402.12875 • Published • 13 -
TPI-LLM: Serving 70B-scale LLMs Efficiently on Low-resource Edge Devices
Paper • 2410.00531 • Published • 34