Document Intelligence Centre of Excellence

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National Center for Scientific Research Demokritos
Patr. Gregoriou E & Neapoleos Str 27
15341 Agia Paraskevi
Athens, Greece

DICE is a Document Intelligence Centre of Excellence. Its mission is to develop novel AI methods and become a world class reference centre in AI for business documents.

Its vision is to connect researchers, scientists and AI professionals with business experts from a wide range of industrial sectors, aiming at using emerging technologies to accelerate innovation.

Research synopsis: Our principal research interests lie in the development of machine learning and statistical methodologies for solving problems involving un-/semi-/fully-structured financial data.

We are part of the Institute of Informatics and Telecommunications (IIT) at the National Center for Scientific Research - NCSR “Demokritos”.

Check out our publications and our projects outreach to learn more abour our work and feel free to reach out, if you are interested!

News

Sep 29, 2025 🚀 DICE at ICAIF-2025! We’re excited to share that two new papers from the team have been accepted: Positive-Unlabeled Learning for Financial Misstatement Detection under Realistic Constraints and A Multimodal Alignment-Based Anomaly Detection Method for Bankruptcy Prediction. Looking forward to the discussions in Singapore!
Sep 01, 2025 DICE has a new member🎉! Nick Reskos nice to have you onboard!
Aug 04, 2025 🎉 DICE at ECML-PKDD! Dimitris Kelesis will be presenting two of his works on GNNs and oversmoothing: Partially trained graph convolutional networks resist oversmoothing and Analyzing the effect of residual connections on oversmoothing in graph neural networks. Catch him in Porto in September!
Jun 20, 2025 DICE will be presenting in the 38th IEEE International Symposium on Computer-Based Medical Systems (CBMS), its latest work on Predicting Multi-Class Drug-Drug Interactions Using a Disease-Specific Knowledge Graph💊 as a full oral! Stay tuned for the full paper!

Selected Publications

  1. ACM
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    Machine Learning for Identifying Risk in Financial Statements: A Survey
    Elias ZavitsanosEirini Spyropoulou, George Giannakopoulos, and Georgios Paliouras
    ACM Comput. Surv., Mar 2025
  2. ICAIF
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    Bankruptcy Prediction: Data Augmentation, LLMs and the Need for Auditor’s Opinion
    In Proceedings of the 5th ACM International Conference on AI in Finance, Nov 2024
  3. Nature
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    Entrant: A large financial dataset for table understanding
    Scientific Data, Aug 2024