CLEF 2026 FinMMEval Lab - Call for Participation Register Now
CLEF 2026 - Call for Participation

FinMMEval Lab 2026

Multilingual and Multimodal Evaluation of Financial AI Systems

About the Lab

FinMMEval Lab integrates financial reasoning, multilingual understanding, and decision-making into a unified evaluation suite designed to promote robust, transparent, and globally competent financial AI. The 2026 edition introduces three interconnected tasks spanning five languages.

Multi-modal inputs: news, filings, macro indicators, tests.

Multiple languages with low-resource representations: English, Chinese, Arabic, Hindi, Greek, Japanese, Spanish.

Tasks spanning Q&A, and decision making.

Metrics centered on Accuracy, ROUGE-1, BLEURT and performance quantitative metrics (e.g. CR, SR, MD).

Financial AI Framework

"How can I tailor my setup to make an LLM exceptionally good at finance?"

Tasks

Choose one or more tasks. Each submission must provide calibrated confidence scores and an evidence trace.

Task 1 - Financial Exam Q&A

Given a stand-alone multiple-choice question Q with four candidate options { A1, A2, A3, A4 }, the system must select the correct answer A. Questions cover valuation, accounting, ethics, corporate finance, and regulatory knowledge.

Motivation

Professional financial qualification exams (e.g., CFA, EFPA) require the integration of theoretical and regulatory knowledge with applied reasoning. Existing LLMs often rely on factual recall without demonstrating the analytical rigor expected from human candidates.

Data

  • EFPA (Spanish): 50 exam-style financial questions on investment and regulation.
  • GRFinQA (Greek): 225 multiple-choice finance questions from university-level exams.
  • CFA (English): 600 exam-style multiple-choice questions covering nine core domains.
  • CPA (Chinese): 300 exam-style financial questions focusing on major modules.
  • BBF (Hindi): 500-1000 exam-style financial multiple-choice questions covering over 30 domains.

Evaluation

Models are required to output the correct answer label. Performance is measured by accuracy, defined as the proportion of correctly identified options in the test set.

Important Dates

Specific dates will be announced once they are fixed.

Lab registration opens
17 November 2025
Release of the training materials
December 2025
Lab registration closes
23 April 2026
Beginning of the evaluation cycle (test sets release)
May 2026
End of the evaluation cycle (run submission)
07 May 2026
Deadline for the submission of working notes [CEUR-WS]
28 May 2026
Review process of participant papers
28 May – 30 June 2026
Submission of Condensed Lab Overviews [LNCS]
08 June 2026
Notification of Acceptance for Condensed Lab Overviews [LNCS]
15 June 2026
Camera Ready Copy of Condensed Lab Overviews [LNCS] due
22 June 2026
Notification of Acceptance for Participant Papers [CEUR-WS]
30 June 2026
Camera Ready Copy of Participant Papers and Extended Lab Overviews [CEUR-WS] due
06 July 2026
CLEF 2026 Conference
21–24 September 2026 • Jena, Germany

Latest News

Announcement December 7, 2025

Unique registered participants grow every day

We are experiencing consistent growth in unique participants through registrations, demonstrating interest prior to the start of our marketing campaign.

Registration Growth Read more →

How to Participate

Engage with the challenges in a way that suits you - from a quick, one-time experiment to a detailed research project. While we invite you to share your findings in our workshop notes, you are also free to develop promising results into a full paper for an archival journal.

The workshop itself is a perfect opportunity to refine your ideas through discussion with peers.

Ready to join?

Sign Up

Sign up via the CLEF registration form (FinMMEval section)

Packaging Checklist


  • Results JSONL (per task)
  • System Card (architecture, data usage, risks)
  • Reproducibility (seed, versions, hardware)
  • License compliance acknowledgements (if applicable)

Organizers

Organizing committee and partner institutions.

Zhuohan Xie
Zhuohan Xie
MBZUAI (UAE)
Rania Elbadry
Rania Elbadry
MBZUAI (UAE)
FZ
Fan Zhang
University of Tokyo (Japan)
Georgi Georgiev
Georgi Georgiev
Sofia University "St. Kliment Ohridski" (Bulgaria)
Xueqing Peng
Xueqing Peng
The Fin AI (USA)
Lingfei Qian
Lingfei Qian
The Fin AI (USA)
Jimin Huang
Jimin Huang
The Fin AI (USA)
Dimitar Dimitrov
Dimitar Dimitrov
Sofia University "St. Kliment Ohridski" (Bulgaria)
VJ
Vanshikaa Jani
University of Arizona (USA)
YD
Yuyang Dai
INSAIT (Bulgaria)
Jiahui Geng
Jiahui Geng
MBZUAI (UAE)
Yuxia Wang
Yuxia Wang
INSAIT (Bulgaria)
Ivan Koychev
Ivan Koychev
Sofia University "St. Kliment Ohridski" (Bulgaria)
Veselin Stoyanov
Veselin Stoyanov
MBZUAI (UAE)
Preslav Nakov
Preslav Nakov
MBZUAI (UAE)

Frequently Asked Questions

Who can participate?

Researchers and practitioners from academia and industry. Student teams are particularly welcome.

How is data licensed?

Research-only license; redistribution of raw sources may be restricted.

Can we submit to multiple tasks?

Yes. Submit independent result bundles per task.

Are ensembles allowed?

Yes, but disclose all components in the system card.