Papers Model Optimization
“Model Optimization” 태그가 달린 논문 380편 · 필터 해제
SLOT: Sample-specific Language Model Optimization at Test-time
We propose SLOT (Sample-specific Language Model Optimization at Test-time), a novel and parameter-efficient test-time inference approach that enhances a language model's ability to more accurately respond to individual p…
GSM8KLanguage ModelingLanguage ModellingModel OptimizationMUST: Multi-Scale Structural-Temporal Link Prediction Model for UAV Ad Hoc Networks
Link prediction in unmanned aerial vehicle (UAV) ad hoc networks (UANETs) aims to predict the potential formation of future links between UAVs. In adversarial environments where the route information of UAVs is unavailab…
Graph AttentionLink PredictionModel OptimizationPredictionFrom Rankings to Insights: Evaluation Should Shift Focus from Leaderboard to Feedback
Automatic evaluation benchmarks such as MT-Bench, Arena-Hard, and Auto-Arena are seeing growing adoption for the evaluation of Large Language Models (LLMs). Existing research has primarily focused on approximating human-…
Model OptimizationCombining Abstract Argumentation and Machine Learning for Efficiently Analyzing Low-Level Process Event Streams
Monitoring and analyzing process traces is a critical task for modern companies and organizations. In scenarios where there is a gap between trace events and reference business activities, this entails an interpretation …
Abstract ArgumentationModel OptimizationEdge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey
Edge-cloud collaborative computing (ECCC) has emerged as a pivotal paradigm for addressing the computational demands of modern intelligent applications, integrating cloud resources with edge devices to enable efficient, …
Autonomous DrivingBenchmarkingDistributed ComputingLow-latency processing+3D$^{2}$MoE: Dual Routing and Dynamic Scheduling for Efficient On-Device MoE-based LLM Serving
The mixture of experts (MoE) model is a sparse variant of large language models (LLMs), designed to hold a better balance between intelligent capability and computational overhead. Despite its benefits, MoE is still too …
Mixture-of-ExpertsModel CompressionModel OptimizationQuantization+1Unveiling Hidden Collaboration within Mixture-of-Experts in Large Language Models
Mixture-of-Experts based large language models (MoE LLMs) have shown significant promise in multitask adaptability by dynamically routing inputs to specialized experts. Despite their success, the collaborative mechanisms…
Dictionary LearningMixture-of-ExpertsModel OptimizationMicroNAS: An Automated Framework for Developing a Fall Detection System
This work presents MicroNAS, an automated neural architecture search tool specifically designed to create models optimized for microcontrollers with small memory resources. The ESP32 microcontroller, with 320 KB of memor…
Action DetectionActivity DetectionModel OptimizationNeural Architecture Search2D-Curri-DPO: Two-Dimensional Curriculum Learning for Direct Preference Optimization
Aligning large language models with human preferences is crucial for their safe deployment. While Direct Preference Optimization (DPO) offers an efficient alternative to reinforcement learning from human feedback, tradit…
Model OptimizationLLM-Guided Evolution: An Autonomous Model Optimization for Object Detection
In machine learning, Neural Architecture Search (NAS) requires domain knowledge of model design and a large amount of trial-and-error to achieve promising performance. Meanwhile, evolutionary algorithms have traditionall…
Evolutionary Algorithmsimage-classificationImage ClassificationLarge Language Model+4On-device Sora: Enabling Training-Free Diffusion-based Text-to-Video Generation for Mobile Devices
We present On-device Sora, the first model training-free solution for diffusion-based on-device text-to-video generation that operates efficiently on smartphone-grade devices. To address the challenges of diffusion-based…
DenoisingModel OptimizationText-to-Video GenerationVideo GenerationMap Feature Perception Metric for Map Generation Quality Assessment and Loss Optimization
In intelligent cartographic generation tasks empowered by generative models, the authenticity of synthesized maps constitutes a critical determinant. Concurrently, the selection of appropriate evaluation metrics to quant…
Model OptimizationSSIMUI-R1: Enhancing Efficient Action Prediction of GUI Agents by Reinforcement Learning
The recent DeepSeek-R1 has showcased the emergence of reasoning capabilities in LLMs through reinforcement learning (RL) with rule-based rewards. Despite its success in language models, its application in multi-modal dom…
Model OptimizationReinforcement Learning (RL)OpenHuEval: Evaluating Large Language Model on Hungarian Specifics
We introduce OpenHuEval, the first benchmark for LLMs focusing on the Hungarian language and specifics. OpenHuEval is constructed from a vast collection of Hungarian-specific materials sourced from multiple origins. In t…
Language ModelingLanguage ModellingLarge Language ModelModel OptimizationKnowledge-guided machine learning for county-level corn yield prediction under drought
Remote sensing (RS) technique, enabling the non-contact acquisition of extensive ground observations, is a valuable tool for crop yield predictions. Traditional process-based models struggle to incorporate large volumes …
Model OptimizationHySurvPred: Multimodal Hyperbolic Embedding with Angle-Aware Hierarchical Contrastive Learning and Uncertainty Constraints for Survival Prediction
Multimodal learning that integrates histopathology images and genomic data holds great promise for cancer survival prediction. However, existing methods face key limitations: 1) They rely on multimodal mapping and metric…
Contrastive LearningModel OptimizationSurvival PredictionA Comprehensive Survey on Cross-Domain Recommendation: Taxonomy, Progress, and Prospects
Recommender systems (RS) have become crucial tools for information filtering in various real world scenarios. And cross domain recommendation (CDR) has been widely explored in recent years in order to provide better reco…
ArticlesModel OptimizationRecommendation SystemsSurveyACT360: An Efficient 360-Degree Action Detection and Summarization Framework for Mission-Critical Training and Debriefing
Effective training and debriefing are critical in high-stakes, mission-critical environments such as disaster response, military simulations, and industrial safety, where precision and minimizing errors are paramount. Th…
Action DetectionDisaster ResponseModel OptimizationQuantizationDifferentiable Folding for Nearest Neighbor Model Optimization
The Nearest Neighbor model is the $\textit{de facto}$ thermodynamic model of RNA secondary structure formation and is a cornerstone of RNA structure prediction and sequence design. The current functional form (Turner 200…
modelModel OptimizationOn Digital Optimization of Analog Self-Interference Cancellation for Full-Duplex Wireless Systems
Wireless systems with inband full-duplex transceiver typically require multiple lines of defense against the effect of harsh self-interference, specifically, to avoid saturation of the analog-to-digital converter (ADC) i…
Model Optimization