works on

From the 1 of 6 linked papers with an AI index.

activity
20242026
collaborators

6 papers

cs.DB2026

AgenticER: the next frontier in Entity Resolution

George Papadakis, Panos Korovesis, Manolis Koubarakis +1

The paper proposes Agentic Entity Resolution, a new paradigm where autonomous agents actively plan and execute sequential decision-making steps to resolve entities, gathering evide…

cs.DB2026

DistillER: Knowledge Distillation in Entity Resolution with Large Language Models

Alexandros Zeakis, George Papadakis, Dimitrios Skoutas +1

Recent advances in Entity Resolution (ER) have leveraged Large Language Models (LLMs), achieving strong performance but at the cost of substantial computational resources or high f…

cs.CL2025

Harnessing Collective Intelligence of LLMs for Robust Biomedical QA: A Multi-Model Approach

Dimitra Panou, Alexandros C. Dimopoulos, Manolis Koubarakis +1

Biomedical text mining and question-answering are essential yet highly demanding tasks, particularly in the face of the exponential growth of biomedical literature. In this work, w…

cs.CV2025

TerraQ: Spatiotemporal Question-Answering on Satellite Image Archives

Sergios-Anestis Kefalidis, Konstantinos Plas, Manolis Koubarakis

TerraQ is a spatiotemporal question-answering engine for satellite image archives. It is a natural language processing system that is built to process requests for satellite images…

cs.CL2024

Transformer-based Language Models for Reasoning in the Description Logic ALCQ

Angelos Poulis, Eleni Tsalapati, Manolis Koubarakis

Recent advancements in transformer-based language models have sparked research into their logical reasoning capabilities. Most of the benchmarks used to evaluate these models are s…

cs.CL2024

The Large Language Model GreekLegalRoBERTa

Vasileios Saketos, Despina-Athanasia Pantazi, Manolis Koubarakis

We develop four versions of GreekLegalRoBERTa, which are four large language models trained on Greek legal and nonlegal text. We show that our models surpass the performance of Gre…