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Marvin Muñoz Barón

3 papers hereh-index 3131 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2

Across the 2 of 3 papers where every author was matched, so the position is known.

fields
  • cs.SE3

identity via Semantic Scholar / OpenAlex

most citedGuidelines for Empirical Studies in Software Engineering involving Large Language Models

3 citations · 3 across the 2 of their papers we have counts for

collaborators

3 papers

cs.SE2026

Evaluating the Impact of Explainable AI on Trust in AI-Assisted Code Review

Zhenhan Gao, Marvin Muñoz Barón, Umm-e Habiba +2

Background: Large language models (LLMs) are increasingly used to automate code review, but the reasoning behind their decisions remains hard to understand. Developers struggle to…

cs.SE2026★ 3 cited

Guidelines for Empirical Studies in Software Engineering involving Large Language Models

Sebastian Baltes, Florian Angermeir, Chetan Arora +19

Large Language Models (LLMs) are widely used in software engineering (SE) research and practice, yet their non-determinism, opaque training data, and rapidly evolving models threat…

cs.SE2025

Towards Evaluation Guidelines for Empirical Studies involving LLMs

Stefan Wagner, Marvin Muñoz Barón, Davide Falessi +1

In the short period since the release of ChatGPT, large language models (LLMs) have changed the software engineering research landscape. While there are numerous opportunities to u…

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