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20242026
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cs.CL2025

From Model to Breach: Towards Actionable LLM-Generated Vulnerabilities Reporting

Cyril Vallez, Alexander Sternfeld, Andrei Kucharavy +1

As the role of Large Language Models (LLM)-based coding assistants in software development becomes more critical, so does the role of the bugs they generate in the overall cybersec…

cs.CL2025

Are the LLMs Capable of Maintaining at Least the Language Genus?

Sandra Mitrović, David Kletz, Ljiljana Dolamic +1

Large Language Models (LLMs) display notable variation in multilingual behavior, yet the role of genealogical language structure in shaping this variation remains underexplored. In…

cs.CL2025

TypePilot: Leveraging the Scala Type System for Secure LLM-generated Code

Alexander Sternfeld, Andrei Kucharavy, Ljiljana Dolamic

Large language Models (LLMs) have shown remarkable proficiency in code generation tasks across various programming languages. However, their outputs often contain subtle but critic…

cs.CL2025

Tokenization and Representation Biases in Multilingual Models on Dialectal NLP Tasks

Vani Kanjirangat, Tanja Samardžić, Ljiljana Dolamic +1

Dialectal data are characterized by linguistic variation that appears small to humans but has a significant impact on the performance of models. This dialect gap has been related t…

cs.CL2025

Exploring Data and Parameter Efficient Strategies for Arabic Dialect Identifications

Vani Kanjirangat, Ljiljana Dolamic, Fabio Rinaldi

This paper discusses our exploration of different data-efficient and parameter-efficient approaches to Arabic Dialect Identification (ADI). In particular, we investigate various so…

cs.CL2024

NMT-Obfuscator Attack: Ignore a sentence in translation with only one word

Sahar Sadrizadeh, César Descalzo, Ljiljana Dolamic +1

Neural Machine Translation systems are used in diverse applications due to their impressive performance. However, recent studies have shown that these systems are vulnerable to car…