From Plausible to Actionable: A Position on LLM Self-Explanations — Paper

Abstract

Large Language Models (LLMs) can generate natural language explanations that rationalize their own decisions, a phenomenon commonly referred to as self-explanations. Such explanations have emerged as a promising direction for explainable artificial intelligence (XAI), particularly for interpreting LLM behavior. However, while self-explanations often appear plausible, whether they faithfully reflect a model's underlying reasoning process remains an open question. In this opinion paper, we argue that self-explanations can be highly plausible, questionably faithful, and yet highly actionable. From a traditional XAI perspective, we identify the limitations of standard evaluation protocols for LLM-generated self-explanations and propose practical guidelines for assessing their plausibility and faithfulness.Moreover, we argue that evaluation should extend beyond these criteria to actionability, highlighting applications of LLM rationalization capabilities that support informed decision-making and appropriate action across diverse stakeholders.

Authors 4

Elize Herrewijnen, Benedetta Muscato, Gizem Gezici, Fosca Giannotti

Specification

Official page: arxiv.org/abs/2607.15957
Source:arXiv (Atom API + RSS)T1observed 6 h agohigh
Arxiv announce type: cross
Source:arXiv (Atom API + RSS)T1observed 6 h agohigh
arXiv id: 2607.15957
Source:arXiv (Atom API + RSS)T1observed 6 h agohigh
Categories: cs.CL, cs.AI
Source:arXiv (Atom API + RSS)T1observed 6 h agohigh
PDF: arxiv.org/pdf/2607.15957
Source:arXiv (Atom API + RSS)T1observed 6 h agohigh
Primary category: cs.CL
Source:arXiv (Atom API + RSS)T1observed 6 h agohigh
Published: 11 Sept 2026
Source:arXiv (Atom API + RSS)T1observed 6 h agohigh

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Attributed facts

9

Source tiers

T19

Freshest observation

6 h ago

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None

No models linked to this paper yet.

Authors: Elize Herrewijnen, Benedetta Muscato, Gizem Gezici

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Claim history · Categories

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Claim history for Categories
Value	Valid from → to	Status	Source	Confidence	Extractor
cs.CL, cs.AI	11 Sept 2026 21:03 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 paperPaperFrom Plausible to Actionable: A Position on LLM Self-Explanations
New paper: From Plausible to Actionable: A Position on LLM Self-Explanations
arxiv
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Source documents
Source	Document	Type	Tier	Last observed	Snapshots
arXiv (Atom API + RSS)	rss.arxiv.org/rss/cs.AI	feed	T1· Official	4 h ago	1

Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.