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From the 3 of 19 linked papers with an AI index.

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cs.CL2026

Automated Textbook Auditing with Multi-Agent LLM Systems

Ciprian Cristescu, Adrian-Marius Dumitran, Angela-Liliana Dumitran +1

The paper introduces AI Textbook Auditor, a modular multi‑agent pipeline that uses large language models to automatically detect factual, technical, and grammatical errors in textb…

cs.CL2026

Not All Tokens Are Equal: Inflation-Aware Routing for Agentic LLM Systems

Heming Fu, Shan Lin, Qianqian Xie +1

When a language model fails to answer a query on the first attempt, an agentic system retries, consuming additional tokens each time. This retry overhead creates a gap between what…

cs.CL2026

MuTSE: A Human-in-the-Loop Multi-use Text Simplification Evaluator

Rares-Alexandru Roscan, Gabriel Petre1, Adrian-Marius Dumitran +1

As Large Language Models (LLMs) become increasingly prevalent in text simplification, systematically evaluating their outputs across diverse prompting strategies and architectures…

cs.CL2025

RoBiologyDataChoiceQA: A Romanian Dataset for improving Biology understanding of Large Language Models

Dragos-Dumitru Ghinea, Adela-Nicoleta Corbeanu, Adrian-Marius Dumitran

In recent years, large language models (LLMs) have demonstrated significant potential across various natural language processing (NLP) tasks. However, their performance in domain-s…

cs.CL2025

A Cross-Lingual Analysis of Bias in Large Language Models Using Romanian History

Matei-Iulian Cocu, Răzvan-Cosmin Cristia, Adrian Marius Dumitran

In this case study, we select a set of controversial Romanian historical questions and ask multiple Large Language Models to answer them across languages and contexts, in order to…

cs.CL2025

Do LLMs Understand Romanian Driving Laws? A Study on Multimodal and Fine-Tuned Question Answering

Eduard Barbu, Adrian Marius Dumitran

Ensuring that both new and experienced drivers master current traffic rules is critical to road safety. This paper evaluates Large Language Models (LLMs) on Romanian driving-law QA…