5 papers
Who Judges the Frame? Auditing Multimodal LLM Judges for News Framing Across Event-Level Perspectives
Antonela Tommasel, Markus Schedl
News coverage of major world events is shaped not only by what is reported, but also by how events are framed through text, images and their combination. At the same time, Large La…
Measuring Human-Like Bias in LLMs? A Critique of Human-Derived Bias Constructs in LLM Evaluation
Antonela Tommasel, Markus Schedl
Researchers increasingly use human-derived bias constructs to study Large Language Models (LLMs), including social-cognitive constructs such as implicit bias and stereotype activat…
What Price Fairness? Evaluating Energy - Fairness - Accuracy Trade-off in Recommender Systems
Abhirup Mitra, Oleg Lesota, Antonela Tommasel
Fairness-aware recommender systems aim to mitigate systematic imbalances in recommendation outcomes, including how visibility, relevance, and opportunities are distributed among us…
Team DArgk at the 2026 ELOQUENT lab for evaluating generative language model quality: Residuals of Humanity: AI Detection Evasion via GRPO Fine-Tuning
Antonela Tommasel, Juan Manuel Rodriguez
Large language models (LLMs) can generate fluent and coherent text that is increasingly difficult to distinguish from human writing, motivating the development of automatic AI-gene…
Training seeds and model-selection stability in recommender-system evaluation
Juan Manuel Rodriguez, Oleg Lesota, Antonela Tommasel
Recommender-system experiments often rely on a single random training seed, assuming that run-to-run stochasticity has limited impact on evaluation conclusions. This assumption is…