Explainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models — Paper

Abstract

Energy consumption forecasting relies on increasingly complex machine learning (ML) models, such as Genetic Programming-based symbolic regressors, whose predictions can be difficult for facility managers and building operators to interpret. Explainable Artificial Intelligence (XAI) techniques address this opacity, but traditional XAI dashboards require substantial technical expertise and provide limited flexibility for dynamic, context-aware inquiry. Conversational XAI systems offer a promising alternative; however, previous approaches, such as TalkToModel, were constrained by rigid custom grammars and achieved only 76.8% intent-parsing accuracy. This paper introduces the Explainability Assistant, an open-source conversational XAI system that leverages the function-calling capabilities of modern Large Language Models (LLMs) to overcome these limitations. The system achieves 94% intent-parsing accuracy, supports flexible natural language interaction, and adapts to different ML problem types without task-specific fine-tuning. We present the system's architecture and report results from a comparative evaluation conducted with energy domain specialists, contrasting the Explainability Assistant with a traditional XAI dashboard. The evaluation suggests improved usability and consistent task accuracy, with all experts unanimously preferring the conversational interface for practical use.

Authors 4

Rodion Krjut\v{s}kov, Eduard Barbu, Nikos Sakkas, Sofia Yfanti

Specification

Official page: arxiv.org/abs/2609.11860
Source:arXiv (Atom API + RSS)T1observed 7 h agohigh
Arxiv announce type: cross
Source:arXiv (Atom API + RSS)T1observed 7 h agohigh
arXiv id: 2609.11860
Source:arXiv (Atom API + RSS)T1observed 7 h agohigh
Categories: cs.AI, cs.LG
Source:arXiv (Atom API + RSS)T1observed 7 h agohigh
DOI: 10.1109/ICECET65726.2026.11632877
Source:arXiv (Atom API + RSS)T1observed 7 h agohigh
PDF: arxiv.org/pdf/2609.11860
Source:arXiv (Atom API + RSS)T1observed 7 h agohigh
Primary category: cs.AI
Source:arXiv (Atom API + RSS)T1observed 7 h agohigh
Published: 11 Sept 2026
Source:arXiv (Atom API + RSS)T1observed 7 h agohigh

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10

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T110

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7 h ago

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Authors: Rodion Krjut\v{s}kov, Eduard Barbu, Nikos Sakkas

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Claim history for Authors
Value	Valid from → to	Status	Source	Confidence	Extractor
Rodion Krjut\v{s}kov, Eduard Barbu, Nikos Sakkas, Sofia Yfanti	11 Sept 2026 21:02 UTC → current	current	arXiv (Atom API + RSS)T1	high	deterministic

Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

11 Sept 2026
New paperPaperExplainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models
New paper: Explainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models
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Source documents
Source	Document	Type	Tier	Last observed	Snapshots
arXiv (Atom API + RSS)	rss.arxiv.org/rss/cs.LG	feed	T1· Official	5 h ago	1

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