:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Lee, Woojin, Mekkoth, Pranav, Tian, Ye, Gungor, Onat, Rosing, Tajana
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Artificial Intelligence
Accesso online:	https://arxiv.org/abs/2605.05499
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

LifeAgentBench: A Multi-dimensional Benchmark and Agent for Personal Health Assistants in Digital Health
di: Tian, Ye, et al.
Pubblicazione: (2026)

DailyLLM: Context-Aware Activity Log Generation Using Multi-Modal Sensors and LLMs
di: Tian, Ye, et al.
Pubblicazione: (2025)

KLDrive: Fine-Grained 3D Scene Reasoning for Autonomous Driving based on Knowledge Graph
di: Tian, Ye, et al.
Pubblicazione: (2026)

E-QUARTIC: Energy Efficient Edge Ensemble of Convolutional Neural Networks for Resource-Optimized Learning
di: Zhang, Le, et al.
Pubblicazione: (2024)

ACORN-IDS: Adaptive Continual Novelty Detection for Intrusion Detection Systems
di: Fuhrman, Sean, et al.
Pubblicazione: (2026)

CND-IDS: Continual Novelty Detection for Intrusion Detection Systems
di: Fuhrman, Sean, et al.
Pubblicazione: (2025)

EAGER: Edge-Aligned LLM Defense for Robust, Efficient, and Accurate Cybersecurity Question Answering
di: Gungor, Onat, et al.
Pubblicazione: (2025)

AQUA-LLM: Evaluating Accuracy, Quantization, and Adversarial Robustness Trade-offs in LLMs for Cybersecurity Question Answering
di: Gungor, Onat, et al.
Pubblicazione: (2025)

Offload Rethinking by Cloud Assistance for Efficient Environmental Sound Recognition on LPWANs
di: Zhang, Le, et al.
Pubblicazione: (2025)

CyberMaskQA: A Privacy-Aware Benchmark for Evaluating Large Language Models in Cybersecurity Question Answering
di: Gaddi, Matilda, et al.
Pubblicazione: (2026)

CAN-QA: A Question-Answering Benchmark for Reasoning over In-Vehicle CAN Traffic
di: Chen, Jing, et al.
Pubblicazione: (2026)

CITADEL: Continual Anomaly Detection for Enhanced Learning in IoT Intrusion Detection
di: Li, Elvin, et al.
Pubblicazione: (2025)

SAGE: Sample-Aware Guarding Engine for Robust Intrusion Detection Against Adversarial Attacks
di: Chen, Jing, et al.
Pubblicazione: (2025)

SAFE: Self-Supervised Anomaly Detection Framework for Intrusion Detection
di: Li, Elvin, et al.
Pubblicazione: (2025)

LIGHT-HIDS: A Lightweight and Effective Machine Learning-Based Framework for Robust Host Intrusion Detection
di: Gungor, Onat, et al.
Pubblicazione: (2025)

TrimLLM: Progressive Layer Dropping for Domain-Specific LLMs
di: Hu, Lanxiang, et al.
Pubblicazione: (2024)

INTARG: Informed Real-Time Adversarial Attack Generation for Time-Series Regression
di: Tokgoz, Gamze Kirman, et al.
Pubblicazione: (2026)

TS-OOD: Evaluating Time-Series Out-of-Distribution Detection and Prospective Directions for Progress
di: Gungor, Onat, et al.
Pubblicazione: (2025)

ReLATE+: Unified Framework for Adversarial Attack Detection, Classification, and Resilient Model Selection in Time-Series Classification
di: Kocal, Cagla Ipek, et al.
Pubblicazione: (2025)

MicroHD: An Accuracy-Driven Optimization of Hyperdimensional Computing Algorithms for TinyML systems
di: Ponzina, Flavio, et al.
Pubblicazione: (2024)

DYNAMITE: Dynamic Defense Selection for Enhancing Machine Learning-based Intrusion Detection Against Adversarial Attacks
di: Chen, Jing, et al.
Pubblicazione: (2025)

QMC: Efficient SLM Edge Inference via Outlier-Aware Quantization and Emergent Memories Co-Design
di: Pandey, Nilesh Prasad, et al.
Pubblicazione: (2026)

ReLATE: Resilient Learner Selection for Multivariate Time-Series Classification Against Adversarial Attacks
di: Kocal, Cagla Ipek, et al.
Pubblicazione: (2025)

A KL Lens on Quantization: Fast, Forward-Only Sensitivity for Mixed-Precision SSM-Transformer Models
di: Kong, Jason, et al.
Pubblicazione: (2026)

Divide and Learn: Multi-Objective Combinatorial Optimization at Scale
di: Singh, Esha, et al.
Pubblicazione: (2026)

DPQ-HD: Post-Training Compression for Ultra-Low Power Hyperdimensional Computing
di: Pandey, Nilesh Prasad, et al.
Pubblicazione: (2025)

Towards Interpretable and Inference-Optimal COT Reasoning with Sparse Autoencoder-Guided Generation
di: Zhao, Daniel, et al.
Pubblicazione: (2025)

TAMO: Fine-Grained Root Cause Analysis via Tool-Assisted LLM Agent with Multi-Modality Observation Data in Cloud-Native Systems
di: Zhang, Xiao, et al.
Pubblicazione: (2025)

Feature-Enhanced TResNet for Fine-Grained Food Image Classification
di: Liu, Lulu, et al.
Pubblicazione: (2025)

MMPB: It's Time for Multi-Modal Personalization
di: Kim, Jaeik, et al.
Pubblicazione: (2025)

Mem-Rec: Memory Efficient Recommendation System using Alternative Representation
di: Jha, Gopi Krishna, et al.
Pubblicazione: (2023)

SeMoBridge: Semantic Modality Bridge for Efficient Few-Shot Adaptation of CLIP
di: Timmermann, Christoph, et al.
Pubblicazione: (2025)

SolidCoder: Bridging the Mental-Reality Gap in LLM Code Generation through Concrete Execution
di: Lee, Woojin, et al.
Pubblicazione: (2026)

FEAST: Retrieval-Augmented Multi-Hierarchical Food Classification for the FoodEx2 System
di: Molfetta, Lorenzo, et al.
Pubblicazione: (2026)

Large Language Model Guided Incentive Aware Reward Design for Cooperative Multi-Agent Reinforcement Learning
di: Urgun, Dogan, et al.
Pubblicazione: (2026)

SensorChat: Answering Qualitative and Quantitative Questions during Long-Term Multimodal Sensor Interactions
di: Yu, Xiaofan, et al.
Pubblicazione: (2025)

SensorQA: A Question Answering Benchmark for Daily-Life Monitoring
di: Reichman, Benjamin, et al.
Pubblicazione: (2025)

FoodPuzzle: Developing Large Language Model Agents as Flavor Scientists
di: Huang, Tenghao, et al.
Pubblicazione: (2024)

lmgame-Bench: How Good are LLMs at Playing Games?
di: Hu, Lanxiang, et al.
Pubblicazione: (2025)

Multi-Modal Zero-Shot Prediction of Color Trajectories in Food Drying
di: Li, Shichen, et al.
Pubblicazione: (2025)