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O. Cocarascu

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#artificial intelligence Preprint Sep 2026

IndicSafeEval: Safety Robustness of Large Language Models under Multilingual Persuasive Jailbreak Attacks

IndicSafeEval, a persuasion-based jailbreak evaluation framework for Indian languages, is introduced and it is observed that different risk categories exhibit different levels of vulnerability, with some types of harmful content being significantly more susceptible to persuasion-based jailbreaks than others.

Saikat Mondal, Mamta Mamta, Deeksha Varshney et al. · 0 citations
Open access 2026

NarSiL at SemEval-2026 Task 4: A Multi-Expert, Multi-Pathway System for Narrative Story Similarity

This work presents NarSiL 1, a system for SemEval-2026 Task 4 Track A on Narrative Story Similarity that employs a Mixture-of-Experts initial classifier that also leverages supermajority voting across three large language models, followed by a structured three-pathway fallback for ambiguous cases.

B. Grecu, Costin-Gabriel Chiru, O. Cocarascu · 1 citation
Conference Open access 2026

TinyAttack: Exploring Stylistic Vulnerabilities in Large Language Models

This work proposes TinyAttack, a novel adversarial attack framework designed to exploit vulnerabilities in LLMs through Unicode-based stylistic transformations, which utilises five Unicode variants to modify the visual rendering of text without altering its underlying semantic or syntactic structure.

M. Mamta, B. Grecu, O. Cocarascu · 0 citations

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