AutoTuneX: Interactive Automated Fine-Tuning for Large Language Models

Underline Science Inc. 2026 Open access

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Authors: Association for Artificial Intelligence 2026, Frederico Araujo, Radu Marinescu, Priyanshu Rai, Teryl Taylor, Daniel Karl I. Weidele
DOI: 10.48448/mt9d-5754
Cited by: 0

Abstract

We present AutoTuneX, a system architecture design and implementation for users to interactively fine-tune large language models (LLMs) based on automated hyperparameter optimization particularly built around Bandit Limited Discrepancy Search (Kishimoto et al. 2022). Next to a classical Graphical User Interface (GUI) our system features an agentic runtime to facilitate automated fine-tuning via chat.

Fields of Study & Subjects

Topic Modeling Machine Learning and Data Classification Natural Language Processing Techniques

Publication details

Journal / source
Underline Science Inc.
Publication date
7 January 2026
Language
EN