1 citations · 2 across the 16 of their papers we have counts for
18 papers
Last Translation Benchmark
Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…
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…
Automatic Prompt Optimization for Dataset-Level Feature Discovery
Adrian Cosma, Oleg Szehr, David Kletz +2
Feature extraction from unstructured text is a critical step in many downstream classification pipelines, yet current approaches largely rely on hand-crafted prompts or fixed featu…
Training Language Models with homotokens Leads to Delayed Overfitting
Adrian Cosma, Stefan Ruseti, Emilian Radoi +1
Subword tokenization introduces a computational layer in language models where many distinct token sequences decode to the same surface form and preserve meaning, yet induce differ…
MoME: Estimating Psychological Traits from Gait with Multi-Stage Mixture of Movement Experts
Andy Cǎtrunǎ, Adrian Cosma, Emilian Rǎdoi
Gait encodes rich biometric and behavioural information, yet leveraging the manner of walking to infer psychological traits remains a challenging and underexplored problem. We intr…
Dr.Copilot: A Multi-Agent Prompt Optimized Assistant for Improving Patient-Doctor Communication in Romanian
Andrei Niculae, Adrian Cosma, Cosmin Dumitrache +1
Text-based telemedicine has become increasingly common, yet the quality of medical advice in doctor-patient interactions is often judged more on how advice is communicated rather t…
Database-Agnostic Gait Enrollment using SetTransformers
Nicoleta Basoc, Adrian Cosma, Andy Cǎtrunǎ +1
Gait recognition has emerged as a powerful tool for unobtrusive and long-range identity analysis, with growing relevance in surveillance and monitoring applications. Although recen…
The Strawberry Problem: Emergence of Character-level Understanding in Tokenized Language Models
Adrian Cosma, Stefan Ruseti, Emilian Radoi +1
Despite their remarkable progress across diverse domains, Large Language Models (LLMs) consistently fail at simple character-level tasks, such as counting letters in words, due to…
A Retrieval-Based Approach to Medical Procedure Matching in Romanian
Andrei Niculae, Adrian Cosma, Emilian Radoi
Accurately mapping medical procedure names from healthcare providers to standardized terminology used by insurance companies is a crucial yet complex task. Inconsistencies in namin…
Aligning Actions and Walking to LLM-Generated Textual Descriptions
Radu Chivereanu, Adrian Cosma, Andy Catruna +2
Large Language Models (LLMs) have demonstrated remarkable capabilities in various domains, including data augmentation and synthetic data generation. This work explores the use of…
Gait Recognition from Highly Compressed Videos
Andrei Niculae, Andy Catruna, Adrian Cosma +2
Surveillance footage represents a valuable resource and opportunities for conducting gait analysis. However, the typical low quality and high noise levels in such footage can sever…
The Paradox of Motion: Evidence for Spurious Correlations in Skeleton-based Gait Recognition Models
Andy Cătrună, Adrian Cosma, Emilian Rădoi
Gait, an unobtrusive biometric, is valued for its capability to identify individuals at a distance, across external outfits and environmental conditions. This study challenges the…
CrossGaze: A Strong Method for 3D Gaze Estimation in the Wild
Andy Cătrună, Adrian Cosma, Emilian Rădoi
Gaze estimation, the task of predicting where an individual is looking, is a critical task with direct applications in areas such as human-computer interaction and virtual reality.…