Papers Lightweight Deployment
“Lightweight Deployment” 태그가 달린 논문 15편 · 필터 해제
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. However, existing models still have deficiencies in…
Large Language ModelLightweight DeploymentQuantizationRAGTrialMatchAI: An End-to-End AI-powered Clinical Trial Recommendation System to Streamline Patient-to-Trial Matching
Patient recruitment remains a major bottleneck in clinical trials, calling for scalable and automated solutions. We present TrialMatchAI, an AI-powered recommendation system that automates patient-to-trial matching by pr…
Lightweight DeploymentRetrieval-augmented GenerationSemantic SimilaritySemantic Textual SimilarityMerging and Disentangling Views in Visual Reinforcement Learning for Robotic Manipulation
Vision is well-known for its use in manipulation, especially using visual servoing. To make it robust, multiple cameras are needed to expand the field of view. That is computationally challenging. Merging multiple views …
DisentanglementLightweight DeploymentQ-LearningRetrieval Augmented Anomaly Detection (RAAD): Nimble Model Adjustment Without Retraining
We propose a novel mechanism for real-time (human-in-the-loop) feedback focused on false positive reduction to enhance anomaly detection models. It was designed for the lightweight deployment of a behavioral network anom…
Anomaly DetectionLightweight DeploymentRetrievalRetrieval-augmented GenerationA Comprehensive Social Bias Audit of Contrastive Vision Language Models
In the domain of text-to-image generative models, biases inherent in training datasets often propagate into generated content, posing significant ethical challenges, particularly in socially sensitive contexts. We introd…
DiversityFairnessLightweight DeploymentDigestion 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 mo…
Lightweight DeploymentSemantic ParsingText NormalizationCompensate Quantization Errors+: Quantized Models Are Inquisitive Learners
The quantization of large language models (LLMs) has been a prominent research area aimed at enabling their lightweight deployment in practice. Existing research about LLM's quantization has mainly explored the interplay…
Lightweight DeploymentQuantizationContinuous 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. Containers offer a lightweight deployment option but pulling images from central repositorie…
Decision MakingEdge-computingLightweight DeploymentReprogramming Distillation for Medical Foundation Models
Medical foundation models pre-trained on large-scale datasets have demonstrated powerful versatile capabilities for various tasks. However, due to the gap between pre-training tasks (or modalities) and downstream tasks (…
Knowledge DistillationLightweight Deploymentparameter-efficient fine-tuningTransfer LearningEdge-Enabled Anomaly Detection and Information Completion for Social Network Knowledge Graphs
In the rapidly advancing information era, various human behaviors are being precisely recorded in the form of data, including identity information, criminal records, and communication data. Law enforcement agencies can e…
Anomaly DetectionEdge-computingGraph EmbeddingKnowledge Graph Completion+3ModuleFormer: Modularity Emerges from Mixture-of-Experts
Large Language Models (LLMs) have achieved remarkable results. However, existing models are expensive to train and deploy, and it is also difficult to expand their knowledge beyond pre-training data without forgetting pr…
Language ModellingLightweight DeploymentMixture-of-ExpertsMixed-Type Wafer Classification For Low Memory Devices Using Knowledge Distillation
Manufacturing wafers is an intricate task involving thousands of steps. Defect Pattern Recognition (DPR) of wafer maps is crucial for determining the root cause of production defects, which may further provide insight fo…
Knowledge DistillationLightweight DeploymentVocal Bursts Type PredictionFast-BEV: A Fast and Strong Bird's-Eye View Perception Baseline
Recently, perception task based on Bird's-Eye View (BEV) representation has drawn more and more attention, and BEV representation is promising as the foundation for next-generation Autonomous Vehicle (AV) perception. How…
Data AugmentationLightweight DeploymentDevice-Cloud Collaborative Recommendation via Meta Controller
On-device machine learning enables the lightweight deployment of recommendation models in local clients, which reduces the burden of the cloud-based recommenders and simultaneously incorporates more real-time user featur…
counterfactualDevice-Cloud CollaborationLightweight DeploymentRobBERTje: a Distilled Dutch BERT Model
Pre-trained large-scale language models such as BERT have gained a lot of attention thanks to their outstanding performance on a wide range of natural language tasks. However, due to their large number of parameters, the…
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