6 papers
A Systematic Evaluation of Large Language Models for PTSD Severity Estimation: The Role of Contextual Knowledge and Modeling Strategies
Panagiotis Kaliosis, Adithya V Ganesan, Oscar N. E. Kjell +8
Large language models (LLMs) are increasingly being used in a zero-shot (generative) fashion to assess mental health conditions, yet we have limited knowledge on what factors affec…
LVLMs and Humans Ground Differently in Referential Communication
Peter Zeng, Weiling Li, Amie J. Paige +6
For generative AI agents to partner effectively with human users, the ability to accurately predict human intent is critical. But this ability to collaborate remains limited by a c…
LVLMs are Bad at Overhearing Human Referential Communication
Zhengxiang Wang, Weiling Li, Panagiotis Kaliosis +2
During spontaneous conversations, speakers collaborate on novel referring expressions, which they can then re-use in subsequent conversations. Understanding such referring expressi…
Learning to Align: Addressing Character Frequency Distribution Shifts in Handwritten Text Recognition
Panagiotis Kaliosis, John Pavlopoulos
Handwritten text recognition aims to convert visual input into machine-readable text, and it remains challenging due to the evolving and context-dependent nature of handwriting. Ch…
What is the Right Embedding Space for Contrastive Learning in Referring Expression Counting?
Kostas Triaridis, Panagiotis Kaliosis, E-Ro Nguyen +3
Referring Expression Counting (REC) requires distinguishing visually similar objects described by fine-grained text cues. Existing methods tackle this via image-text contrastive le…
A Data-Driven Guided Decoding Mechanism for Diagnostic Captioning
Panagiotis Kaliosis, John Pavlopoulos, Foivos Charalampakos +2
Diagnostic Captioning (DC) automatically generates a diagnostic text from one or more medical images (e.g., X-rays, MRIs) of a patient. Treated as a draft, the generated text may a…