Parent-Guided Adaptive Reliability (PGAR): A Behavioural Meta-Learning Framework for Stable and Trustworthy AI
Fuente:
arXiv
Enregistré dans:
| Auteur principal: | Rankawat, Anshum |
|---|---|
| Format: | Preprint |
| Publié: |
2026
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
A Meta-learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning
par: Zhang, Xiaojin, et autres
Publié: (2023)
par: Zhang, Xiaojin, et autres
Publié: (2023)
Trustworthy AI Must Account for Interactions
par: Cresswell, Jesse C.
Publié: (2025)
par: Cresswell, Jesse C.
Publié: (2025)
Faithful and Stable Neuron Explanations for Trustworthy Mechanistic Interpretability
par: Yan, Ge, et autres
Publié: (2025)
par: Yan, Ge, et autres
Publié: (2025)
Adaptive Meta-Domain Transfer Learning (AMDTL): A Novel Approach for Knowledge Transfer in AI
par: Laurelli, Michele
Publié: (2024)
par: Laurelli, Michele
Publié: (2024)
Uncertainty-Driven Reliability: Selective Prediction and Trustworthy Deployment in Modern Machine Learning
par: Rabanser, Stephan
Publié: (2025)
par: Rabanser, Stephan
Publié: (2025)
GuardFed: A Trustworthy Federated Learning Framework Against Dual-Facet Attacks
par: Li, Yanli, et autres
Publié: (2025)
par: Li, Yanli, et autres
Publié: (2025)
Meta-Learning Adaptive Loss Functions
par: Raymond, Christian, et autres
Publié: (2023)
par: Raymond, Christian, et autres
Publié: (2023)
Aligning Findings with Diagnosis: A Self-Consistent Reinforcement Learning Framework for Trustworthy Radiology Reporting
par: Zhao, Kun, et autres
Publié: (2026)
par: Zhao, Kun, et autres
Publié: (2026)
A Guide to Failure in Machine Learning: Reliability and Robustness from Foundations to Practice
par: Heim, Eric, et autres
Publié: (2025)
par: Heim, Eric, et autres
Publié: (2025)
FedMM-X: A Trustworthy and Interpretable Framework for Federated Multi-Modal Learning in Dynamic Environments
par: Balija, Sree Bhargavi
Publié: (2025)
par: Balija, Sree Bhargavi
Publié: (2025)
Meta-Learning and Meta-Reinforcement Learning -- Tracing the Path towards DeepMind's Adaptive Agent
par: Hoppmann, Björn, et autres
Publié: (2026)
par: Hoppmann, Björn, et autres
Publié: (2026)
From Answers to Arguments: Toward Trustworthy Clinical Diagnostic Reasoning with Toulmin-Guided Curriculum Goal-Conditioned Learning
par: Zhan, Chen, et autres
Publié: (2026)
par: Zhan, Chen, et autres
Publié: (2026)
Dynamic Meta-Learning for Adaptive XGBoost-Neural Ensembles
par: Sedek, Arthur
Publié: (2025)
par: Sedek, Arthur
Publié: (2025)
Co-Investigator AI: The Rise of Agentic AI for Smarter, Trustworthy AML Compliance Narratives
par: Naik, Prathamesh Vasudeo, et autres
Publié: (2025)
par: Naik, Prathamesh Vasudeo, et autres
Publié: (2025)
Data Heterogeneity Modeling for Trustworthy Machine Learning
par: Liu, Jiashuo, et autres
Publié: (2025)
par: Liu, Jiashuo, et autres
Publié: (2025)
From Imperfect Signals to Trustworthy Structure: Confidence-Aware Inference from Heterogeneous and Reliability-Varying Utility Data
par: Li, Haoran, et autres
Publié: (2025)
par: Li, Haoran, et autres
Publié: (2025)
PSO-XAI: A PSO-Enhanced Explainable AI Framework for Reliable Breast Cancer Detection
par: Raquib, Mirza, et autres
Publié: (2025)
par: Raquib, Mirza, et autres
Publié: (2025)
Stable Attention Response for Reliable Precipitation Nowcasting
par: Wen, Penghui, et autres
Publié: (2026)
par: Wen, Penghui, et autres
Publié: (2026)
Grounding Generative Planners in Verifiable Logic: A Hybrid Architecture for Trustworthy Embodied AI
par: Wu, Feiyu, et autres
Publié: (2026)
par: Wu, Feiyu, et autres
Publié: (2026)
MASteer: Multi-Agent Adaptive Steer Strategy for End-to-End LLM Trustworthiness Repair
par: Li, Changqing, et autres
Publié: (2025)
par: Li, Changqing, et autres
Publié: (2025)
CALM: A CKA-Guided Adaptive Layer-Wise Modularization Framework for LLM Quantization
par: Zhang, Jinhao, et autres
Publié: (2025)
par: Zhang, Jinhao, et autres
Publié: (2025)
Assessing Trustworthiness of AI Training Dataset using Subjective Logic -- A Use Case on Bias
par: Ouattara, Koffi Ismael, et autres
Publié: (2025)
par: Ouattara, Koffi Ismael, et autres
Publié: (2025)
Guiding Diffusion Models with Reinforcement Learning for Stable Molecule Generation
par: Zhou, Zhijian, et autres
Publié: (2025)
par: Zhou, Zhijian, et autres
Publié: (2025)
MANGO: Meta-Adaptive Network Gradient Optimization for Online Continual Learning
par: Awasthi, Ankita, et autres
Publié: (2026)
par: Awasthi, Ankita, et autres
Publié: (2026)
RL-Struct: A Lightweight Reinforcement Learning Framework for Reliable Structured Output in LLMs
par: Hu, Ruike, et autres
Publié: (2025)
par: Hu, Ruike, et autres
Publié: (2025)
GHPO: Adaptive Guidance for Stable and Efficient LLM Reinforcement Learning
par: Liu, Ziru, et autres
Publié: (2025)
par: Liu, Ziru, et autres
Publié: (2025)
A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learning
par: Zhang, Xiaojin, et autres
Publié: (2024)
par: Zhang, Xiaojin, et autres
Publié: (2024)
Meta-Task: A Method-Agnostic Framework for Learning to Regularize in Few-Shot Learning
par: Rostami, Mohammad, et autres
Publié: (2024)
par: Rostami, Mohammad, et autres
Publié: (2024)
Toward Maturity-Based Certification of Embodied AI: Quantifying Trustworthiness Through Measurement Mechanisms
par: Darling, Michael C., et autres
Publié: (2026)
par: Darling, Michael C., et autres
Publié: (2026)
Internalizing Meta-Experience into Memory for Guided Reinforcement Learning in Large Language Models
par: Huang, Shiting, et autres
Publié: (2026)
par: Huang, Shiting, et autres
Publié: (2026)
Margin-Adaptive Confidence Ranking for Reliable LLM Judgement
par: Jin, Gaojie, et autres
Publié: (2026)
par: Jin, Gaojie, et autres
Publié: (2026)
User-Adaptive Meta-Learning for Cold-Start Medication Recommendation with Uncertainty Filtering
par: Moghaddam, Arya Hadizadeh, et autres
Publié: (2026)
par: Moghaddam, Arya Hadizadeh, et autres
Publié: (2026)
FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging
par: Lekadir, Karim, et autres
Publié: (2021)
par: Lekadir, Karim, et autres
Publié: (2021)
EDGE: A Theoretical Framework for Misconception-Aware Adaptive Learning
par: Verma, Ananda Prakash
Publié: (2025)
par: Verma, Ananda Prakash
Publié: (2025)
Standardization Trends on Safety and Trustworthiness Technology for Advanced AI
par: Jeon, Jonghong
Publié: (2024)
par: Jeon, Jonghong
Publié: (2024)
An Offline Meta Black-box Optimization Framework for Adaptive Design of Urban Traffic Light Management Systems
par: Yun, Taeyoung, et autres
Publié: (2024)
par: Yun, Taeyoung, et autres
Publié: (2024)
Towards Trustworthy Keylogger detection: A Comprehensive Analysis of Ensemble Techniques and Feature Selections through Explainable AI
par: Mahmud, Monirul Islam
Publié: (2025)
par: Mahmud, Monirul Islam
Publié: (2025)
FedDRL: A Trustworthy Federated Learning Model Fusion Method Based on Staged Reinforcement Learning
par: Chen, Leiming, et autres
Publié: (2023)
par: Chen, Leiming, et autres
Publié: (2023)
Towards Trustworthy Machine Learning in Production: An Overview of the Robustness in MLOps Approach
par: Bayram, Firas, et autres
Publié: (2024)
par: Bayram, Firas, et autres
Publié: (2024)
Multi-LLM Adaptive Conformal Inference for Reliable LLM Responses
par: Noh, Kangjun, et autres
Publié: (2026)
par: Noh, Kangjun, et autres
Publié: (2026)
Documents similaires
-
A Meta-learning Framework for Tuning Parameters of Protection Mechanisms in Trustworthy Federated Learning
par: Zhang, Xiaojin, et autres
Publié: (2023) -
Trustworthy AI Must Account for Interactions
par: Cresswell, Jesse C.
Publié: (2025) -
Faithful and Stable Neuron Explanations for Trustworthy Mechanistic Interpretability
par: Yan, Ge, et autres
Publié: (2025) -
Adaptive Meta-Domain Transfer Learning (AMDTL): A Novel Approach for Knowledge Transfer in AI
par: Laurelli, Michele
Publié: (2024) -
Uncertainty-Driven Reliability: Selective Prediction and Trustworthy Deployment in Modern Machine Learning
par: Rabanser, Stephan
Publié: (2025)