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cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…