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From the 1 of 6 linked papers with an AI index.

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6 papers

cs.HC2026

Contextualized Counterspeech Can Be More Persuasive Than Generic Counterspeech

Lorenzo Cima, Alessio Miaschi, Amaury Trujillo +3

The paper investigates AI‑generated counterspeech that is adapted to the conversation and the target user, showing that lightweight contextual and personalization strategies can im…

cs.AI2026

Integrating knowledge graphs and multilingual scholarly corpora for domain-adaptive LLMs in SSH

Adam Faci, Alessio Miaschi, Anne Combe +4

The integration of Large Language Models (LLMs) into scientific research workflows, particularly for bibliographic discovery and literature synthesis, raises significant methodolog…

cs.CL2025

Stress-testing Machine Generated Text Detection: Shifting Language Models Writing Style to Fool Detectors

Andrea Pedrotti, Michele Papucci, Cristiano Ciaccio +4

Recent advancements in Generative AI and Large Language Models (LLMs) have enabled the creation of highly realistic synthetic content, raising concerns about the potential for mali…

cs.CL2025

Optimizing LLMs for Italian: Reducing Token Fertility and Enhancing Efficiency Through Vocabulary Adaptation

Luca Moroni, Giovanni Puccetti, Pere-Lluis Huguet Cabot +6

The number of pretrained Large Language Models (LLMs) is increasing steadily, though the majority are designed predominantly for the English language. While state-of-the-art LLMs c…

cs.HC2025

Contextualized Counterspeech: Strategies for Adaptation, Personalization, and Evaluation

Lorenzo Cima, Alessio Miaschi, Amaury Trujillo +3

AI-generated counterspeech offers a promising and scalable strategy to curb online toxicity through direct replies that promote civil discourse. However, current counterspeech is o…

cs.CL2025

Leveraging Encoder-only Large Language Models for Mobile App Review Feature Extraction

Quim Motger, Alessio Miaschi, Felice Dell'Orletta +2

Mobile app review analysis presents unique challenges due to the low quality, subjective bias, and noisy content of user-generated documents. Extracting features from these reviews…