Intent-Aware Example-Based Explainability

In this PhD research, I aim to investigate the limitations inherent in current example-based explainability methods, develop solutions to address these deficiencies, and propose a novel direction for research that aligns example-based explainability with user needs and intent. The objectives of this research include: (a) Formalize existing evaluation metrics for local example-based explainability and propose new metrics to assess these methods from user perspectives; (b) Develop a framework for intent-aware local example-based explainability; and (c) Extend the framework for global example-based explainability and generate model-aware, faithful explanations.

Authors

Institutions

Publication Details

Journal
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Published
2025-01-22
DOI
https://doi.org/10.1609/aies.v7i2.31906
Primary Topic
Business Process Modeling and Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Intent-Aware Example-Based Explainability

Ikhtiyor Nematov
Proceedings of the AAAI/ACM Conference on AI Ethics and Society
Business Process Modeling and Analysis
article

Intent-Aware Example-Based Explainability

Ikhtiyor Nematov
article en

Abstract

In this PhD research, I aim to investigate the limitations inherent in current example-based explainability methods, develop solutions to address these deficiencies, and propose a novel direction for research that aligns example-based explainability with user needs and intent. The objectives of this research include: (a) Formalize existing evaluation metrics for local example-based explainability and propose new metrics to assess these methods from user perspectives; (b) Develop a framework for intent-aware local example-based explainability; and (c) Extend the framework for global example-based explainability and generate model-aware, faithful explanations.

Proceedings of the AAAI/ACM Conference on AI Ethics and SocietyVol. 7(2)
Université Libre de Bruxelles (BE)
Openalex Percentile: Top 98%
Business Process Modeling and Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.