1 citations · 1 across the 6 of their papers we have counts for
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Quantifying Retriever-Generator Alignment in RAG with Local Explanations
Korbinian Randl, Guido Rocchietti, Aron Henriksson +3
Retrieval-Augmented Generation (RAG) systems combine dense retrievers and language models to ground their outputs in external documents. However, the interaction between these comp…
Building Multilingual Datasets for Predicting Mental Health Severity through LLMs: Prospects and Challenges
Konstantinos Skianis, John Pavlopoulos, A. Seza DoÄruöz
Large Language Models (LLMs) are increasingly being integrated into various medical fields, including mental health support systems. However, there is a gap in research regarding t…
Leveraging LLMs for Translating and Classifying Mental Health Data
Konstantinos Skianis, A. Seza DoÄruöz, John Pavlopoulos
Large language models (LLMs) are increasingly used in medical fields. In mental health support, the early identification of linguistic markers associated with mental health conditi…
Proverbs or Pythian Oracles? Sentiments and Emotions in Greek Sayings
Katerina Korre, John Pavlopoulos
Proverbs are among the most fascinating language phenomena that transcend cultural and linguistic boundaries. Yet, much of the global landscape of proverbs remains underexplored, a…
TopClustRAG at SIGIR 2025 LiveRAG Challenge
Juli Bakagianni, John Pavlopoulos, Aristidis Likas
We present TopClustRAG, a retrieval-augmented generation (RAG) system developed for the LiveRAG Challenge, which evaluates end-to-end question answering over large-scale web corpor…
A Systematic Survey of Natural Language Processing for the Greek Language
Juli Bakagianni, Kanella Pouli, Maria Gavriilidou +1
Comprehensive monolingual Natural Language Processing (NLP) surveys are essential for assessing language-specific challenges, resource availability, and research gaps. However, exi…