Hymba, A New Architecture That Pushes The Limits Of Small LLMs
Hymba, A New Architecture That Pushes The Limits Of Small LLMs
Machine Learning In Non-Euclidean Space Enabled By The Kuramoto Model
Machine Learning In Non-Euclidean Space Enabled By The Kuramoto Model
Computer Vision
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MGSER-SAM] A Method For Solving The Ruinous Forgetting Problem In Continuous Learning
MGSER-SAM] A Method For Solving The Ruinous Forgetting Problem In Continuous Learning
Continual Learning
For IoT Devices: A Coalitional Learning Method That Distributes The Inference Load
For IoT Devices: A Coalitional Learning Method That Distributes The Inference Load
Internet Of Things
ADAMG" Revolutionizes Deep Learning Optimization: A New Era Of Parameter-Free
ADAMG" Revolutionizes Deep Learning Optimization: A New Era Of Parameter-Free
Large Language Models
AI Will Solve The Electricity Supply-demand Conundrum In The Era Of Mass EV Proliferation!
AI Will Solve The Electricity Supply-demand Conundrum In The Era Of Mass EV Proliferation!
Neural Network
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[FlagVNE] A Flexible And Generalizable Reinforcement Learning Framework For Virtual Network Embedding
[FlagVNE] A Flexible And Generalizable Reinforcement Learning Framework For Virtual Network Embeddin ...
Networking And Internet Architecture
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[Double Descent] Why Are "large Models" And "large Data Sets" Important?
[Double Descent] Why Are "large Models" And "large Data Sets" Important?
Neural Network
The Key To Reducing Sales Losses: Optimizing Corporate Facility Networks With High-Speed Surrogate-Assisted MCTS
The Key To Reducing Sales Losses: Optimizing Corporate Facility Networks With High-Speed Surrogate-A ...
Meta Achieves Unexpected Improvements In Bayesian Optimization
Meta Achieves Unexpected Improvements In Bayesian Optimization
Bayesian Optimization
Teach Augment: Optimizing Data Augmentation By Utilizing Teacher Models
Teach Augment: Optimizing Data Augmentation By Utilizing Teacher Models
Data Augmentation