37 citations · 84 across the 12 of their papers we have counts for
13 papers
Contextualized Counterspeech Can Be More Persuasive Than Generic Counterspeech
Lorenzo Cima, Alessio Miaschi, Amaury Trujillo +3
AI-generated counterspeech offers a scalable and effective strategy to mitigate online toxicity by promoting more constructive dialogue. Yet, existing approaches adopt a generic, o…
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…
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…
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…
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…
Fine-tuning with HED-IT: The impact of human post-editing for dialogical language models
Daniela Occhipinti, Michele Marchi, Irene Mondella +4
Automatic methods for generating and gathering linguistic data have proven effective for fine-tuning Language Models (LMs) in languages less resourced than English. Still, while th…
AI "News" Content Farms Are Easy to Make and Hard to Detect: A Case Study in Italian
Giovanni Puccetti, Anna Rogers, Chiara Alzetta +2
Large Language Models (LLMs) are increasingly used as "content farm" models (CFMs), to generate synthetic text that could pass for real news articles. This is already happening eve…
Linguistic Knowledge Can Enhance Encoder-Decoder Models (If You Let It)
Alessio Miaschi, Felice Dell'Orletta, Giulia Venturi
In this paper, we explore the impact of augmenting pre-trained Encoder-Decoder models, specifically T5, with linguistic knowledge for the prediction of a target task. In particular…
T-FREX: A Transformer-based Feature Extraction Method from Mobile App Reviews
Quim Motger, Alessio Miaschi, Felice Dell'Orletta +2
Mobile app reviews are a large-scale data source for software-related knowledge generation activities, including software maintenance, evolution and feedback analysis. Effective ex…
Outliers Dimensions that Disrupt Transformers Are Driven by Frequency
Giovanni Puccetti, Anna Rogers, Aleksandr Drozd +1
While Transformer-based language models are generally very robust to pruning, there is the recently discovered outlier phenomenon: disabling only 48 out of 110M parameters in BERT-…
On the interaction of automatic evaluation and task framing in headline style transfer
Lorenzo De Mattei, Michele Cafagna, Huiyuan Lai +3
An ongoing debate in the NLG community concerns the best way to evaluate systems, with human evaluation often being considered the most reliable method, compared to corpus-based me…
Linguistic Profiling of a Neural Language Model
Alessio Miaschi, Dominique Brunato, Felice Dell'Orletta +1
In this paper we investigate the linguistic knowledge learned by a Neural Language Model (NLM) before and after a fine-tuning process and how this knowledge affects its predictions…
GePpeTto Carves Italian into a Language Model
Lorenzo De Mattei, Michele Cafagna, Felice Dell'Orletta +2
In the last few years, pre-trained neural architectures have provided impressive improvements across several NLP tasks. Still, generative language models are available mainly for E…