Lightweight Deployment
6 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Lightweight Deployment
Most implemented papers
Fast-BEV: A Fast and Strong Bird's-Eye View Perception Baseline
Our Fast-BEV consists of five parts, We novelly propose (1) a lightweight deployment-friendly view transformation which fast transfers 2D image feature to 3D voxel space, (2) an multi-scale image encoder which leverages multi-scale information for better performance, (3) an efficient BEV encoder which is particularly designed to speed up on-vehicle inference.
ModuleFormer: Modularity Emerges from Mixture-of-Experts
ibm/moduleformer
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In our experiment, we found that the modular architecture enables three important abilities for large pre-trained language models: 1) Efficiency, since ModuleFormer only activates a subset of its modules for each input token, thus it could achieve the same performance as dense LLMs with more than two times throughput; 2) Extendability, ModuleFormer is more immune to catastrophic forgetting than dense LLMs and can be easily extended with new modules to learn new knowledge that is not included in the training data; 3) Specialisation, finetuning ModuleFormer could specialize a subset of modules to the finetuning task and the task-unrelated modules could be easily pruned for a lightweight deployment.
Reprogramming Distillation for Medical Foundation Models
However, due to the gap between pre-training tasks (or modalities) and downstream tasks (or modalities), the real-world computation and speed constraints, it might not be straightforward to apply medical foundation models in the downstream scenarios.
Continuous reasoning for adaptive container image distribution in the cloud-edge continuum
Cloud-edge computing requires applications to operate across diverse infrastructures, often triggered by cyber-physical events.
Digestion Algorithm in Hierarchical Symbolic Forests: A Fast Text Normalization Algorithm and Semantic Parsing Framework for Specific Scenarios and Lightweight Deployment
Text Normalization and Semantic Parsing have numerous applications in natural language processing, such as natural language programming, paraphrasing, data augmentation, constructing expert systems, text matching, and more.
PsyLite Technical Report
With the rapid development of digital technology, AI-driven psychological counseling has gradually become an important research direction in the field of mental health.
