Enhancing Interpretability in Generative AI Through Search-Based Data Influence Analysis

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Aivalis, Theodoros, Klampanos, Iraklis A., Troumpoukis, Antonis, Jose, Joemon M.
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Training Data Attribution for Image Generation using Ontology-Aligned Knowledge Graphs
di: Aivalis, Theodoros, et al.
Pubblicazione: (2025)

Bridging Ethical Principles and Algorithmic Methods: An Alternative Approach for Assessing Trustworthiness in AI Systems
di: Papademas, Michael, et al.
Pubblicazione: (2025)

Automated and Interpretable Survival Analysis from Multimodal Data
di: Malafaia, Mafalda, et al.
Pubblicazione: (2025)

Generating Survival Interpretable Trajectories and Data
di: Konstantinov, Andrei V., et al.
Pubblicazione: (2024)

Enhancing Interpretability Through Loss-Defined Classification Objective in Structured Latent Spaces
di: Geissler, Daniel, et al.
Pubblicazione: (2024)

Concept Influence: Leveraging Interpretability to Improve Performance and Efficiency in Training Data Attribution
di: Kowal, Matthew, et al.
Pubblicazione: (2026)

Towards Unified Attribution in Explainable AI, Data-Centric AI, and Mechanistic Interpretability
di: Zhang, Shichang, et al.
Pubblicazione: (2025)

Survey on Generalization Theory for Graph Neural Networks
di: Vasileiou, Antonis, et al.
Pubblicazione: (2025)

DSAI: Unbiased and Interpretable Latent Feature Extraction for Data-Centric AI
di: Cho, Hyowon, et al.
Pubblicazione: (2024)

The Quest for the Right Mediator: Surveying Mechanistic Interpretability Through the Lens of Causal Mediation Analysis
di: Mueller, Aaron, et al.
Pubblicazione: (2024)

Enhancing Feature Selection and Interpretability in AI Regression Tasks Through Feature Attribution
di: Hinterleitner, Alexander, et al.
Pubblicazione: (2024)

Age Predictors Through the Lens of Generalization, Bias Mitigation, and Interpretability: Reflections on Causal Implications
di: Paul, Debdas, et al.
Pubblicazione: (2026)

Unsafe LLM-Based Search: Quantitative Analysis and Mitigation of Safety Risks in AI Web Search
di: Luo, Zeren, et al.
Pubblicazione: (2025)

Interpretable Embeddings with Sparse Autoencoders: A Data Analysis Toolkit
di: Jiang, Nick, et al.
Pubblicazione: (2025)

Leveraging Generative AI to Enhance Synthea Module Development
di: Kramer, Mark A., et al.
Pubblicazione: (2025)

A Comparative Analysis of Influence Signals for Data Debugging
di: Myrtakis, Nikolaos, et al.
Pubblicazione: (2025)

Toward Maturity-Based Certification of Embodied AI: Quantifying Trustworthiness Through Measurement Mechanisms
di: Darling, Michael C., et al.
Pubblicazione: (2026)

Empirical Analysis of Asynchronous Federated Learning on Heterogeneous Devices: Efficiency, Fairness, and Privacy Trade-offs
di: Mohammadi, Samaneh, et al.
Pubblicazione: (2025)

Application of AI-based Models for Online Fraud Detection and Analysis
di: Papasavva, Antonis, et al.
Pubblicazione: (2024)

Latent Space Disentanglement via Activation Steering for Interpretable Attribute Control in Symbolic Music Generation
di: Prokopiou, Ioannis, et al.
Pubblicazione: (2026)

Distinguishing AI-Generated and Human-Written Text Through Psycholinguistic Analysis
di: Opara, Chidimma
Pubblicazione: (2025)

Weak-to-Strong Generalization Through the Data-Centric Lens
di: Shin, Changho, et al.
Pubblicazione: (2024)

Towards Better Generalization and Interpretability in Unsupervised Concept-Based Models
di: De Santis, Francesco, et al.
Pubblicazione: (2025)

Interpretable Perturbation Modeling Through Biomedical Knowledge Graphs
di: Passigan, Pascal, et al.
Pubblicazione: (2025)

Enhancing Generative Auto-bidding with Offline Reward Evaluation and Policy Search
di: Mou, Zhiyu, et al.
Pubblicazione: (2025)

In Search of Grandmother Cells: Tracing Interpretable Neurons in Tabular Representations
di: Knauer, Ricardo, et al.
Pubblicazione: (2026)

AI Research Agents for Machine Learning: Search, Exploration, and Generalization in MLE-bench
di: Toledo, Edan, et al.
Pubblicazione: (2025)

Unleashing Uncertainty: Efficient Machine Unlearning for Generative AI
di: Spartalis, Christoforos N., et al.
Pubblicazione: (2025)

Data Interpreter: An LLM Agent For Data Science
di: Hong, Sirui, et al.
Pubblicazione: (2024)

Cyborg Data: Merging Human with AI Generated Training Data
di: North, Kai, et al.
Pubblicazione: (2025)

Is Data Valuation Learnable and Interpretable?
di: Wu, Ou, et al.
Pubblicazione: (2024)

AICRN: Attention-Integrated Convolutional Residual Network for Interpretable Electrocardiogram Analysis
di: Jayakody, J. M. I. H., et al.
Pubblicazione: (2025)

PISA: An AI Pipeline for Interpretable-by-design Survival Analysis Providing Multiple Complexity-Accuracy Trade-off Models
di: Schlender, Thalea, et al.
Pubblicazione: (2025)

When Privacy Isn't Synthetic: Hidden Data Leakage in Generative AI Models
di: Mustaqim, S. M., et al.
Pubblicazione: (2025)

Search-Time Data Contamination
di: Han, Ziwen, et al.
Pubblicazione: (2025)

Generative Models for Synthetic Data: Transforming Data Mining in the GenAI Era
di: Li, Dawei, et al.
Pubblicazione: (2025)

Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data
di: Wang, Xinyi, et al.
Pubblicazione: (2024)

Data Augmentation for Sparse Multidimensional Learning Performance Data Using Generative AI
di: Zhang, Liang, et al.
Pubblicazione: (2024)

Interpretable Representations in Explainable AI: From Theory to Practice
di: Sokol, Kacper, et al.
Pubblicazione: (2020)

Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series
di: Song, Xianhao, et al.
Pubblicazione: (2026)