13 papers
Prompting Complexity: Shortest Prompts for Texts and Behaviors in LLMs
Adrian Cosma
In this paper, we define the quantity of prompting complexity: for a fixed instruction-tuned language model, what is the shortest plausible prompt that makes deterministic decoding…
Counterfactual Methods for Detecting Unfairness in Anti-Money Laundering Algorithms
Lea Multerer, Michele Inchingolo, David Kletz +3
The application of machine learning-based predictive algorithms to Anti-Money Laundering (AML) has grown rapidly, driven by the vast volume of financial transaction data available…
Improving Medical Communication using Rubric-Guided Counterfactual Recommendations
Adrian Cosma, Nicoleta-Nina Basoc, Andrei Niculae +2
Text-based telemedicine increasingly relies on lightweight patient feedback, however, such feedback primarily reflects perceived communication quality rather than medical accuracy.…
An In-Vitro Study on Cross-Lingual Generalization in Language Models
Adrian Cosma
Cross-lingual transfer in language models is difficult to study in natural corpora because lexical overlap, morphology, data imbalance, and tokenization are entangled. We introduce…
What Makes a Good Doctor Response? A Study on Text-Based Telemedicine
Adrian Cosma, Cosmin Dumitrache, Emilian Radoi
Text-based telemedicine has become an increasingly used mode of care, requiring clinicians to deliver medical advice clearly and effectively in writing. As platforms increasingly r…
Spatial Colour Mixing Illusions as a Perception Stress Test for Vision-Language Models
Nicoleta-Nina Basoc, Adrian Cosma, Emilian Radoi
Vision-language models (VLMs) achieve strong benchmark results, yet can exhibit systematic perceptual weaknesses: structured, large changes to pixel values can cause confident yet…