Fifth Workshop on Bias and Fairness in AI at ECML PKDD 2025 (BIAS 2025 @ ECML PKDD)

Call for Papers: BIAS 2025 – Fifth Workshop on Bias and Fairness in AI @ ECML PKDD
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We are inviting submissions (full papers and extended abstracts) for BIAS 2025 (https://sites.google.com/view/bias-2025-ecmlpkdd/), co-located at ECML PKDD 2025 (https://ecmlpkdd.org/2025/) in Porto, Portugal. The workshop will take place on either September 15 or September 19 (TBD).
== Important dates ==
* Submission deadline: June 14, 2025 (AoE)
* Acceptance notification: July 14, 2025
* Workshop date (TBD): September 15, 2025 or September 19, 2025
== Full Call for Papers ==
At this workshop, we wish to stimulate the exchange of novel ideas and interdisciplinary perspectives. To do this, we will accept two types of submissions:
* Full papers that present novel and original work. 
* Abstracts that present already published work, including papers in other conferences, journals, demo's, datasets, or projects that are publicly available.
Exact submission details, including page limits and submission format, will be announced later.

Competition Final Call – MapText’25 (Deadline: April 20)

ICDAR 2025 Competition on Historical Map Text Detection, Recognition, and Linking

📌 Website: https://rrc.cvc.uab.es/?ch=32
📩 Contact: icdar25-maptext-contact (at) googlegroups.com
📢 Updates: https://groups.google.com/g/icdar25-maptext-news
Final Submission Deadline: April 20, 2025


Final Call – Just Under Two Weeks Left to Submit to MapText’25

Dear colleagues,

This is a final reminder that the MapText’25 competition, part of ICDAR 2025 (International Conference on Document Analysis and Recognition), is still open for participation—but only for a few more days. The final deadline is April 20, 2025.

If you're working on text detection, recognition, or linking, this competition offers a valuable opportunity to benchmark your methods on challenging historical map data and contribute to ongoing research in document analysis.

Key Information:

📅 Final Submission Deadline: April 20, 2025
📂 What to Submit: Test set predictions + short method description (no code nor binaries)
🏆 Top teams will be invited to co-author the official competition report (published at ICDAR) and will receive an on-stage award at the main conference

Dataset Highlights:

  • French land registers
  • English Ordnance Survey maps
  • Taiwanese maps with Chinese characters
  • Synthetic training data to support development

You can evaluate your methods on our public platform or use the open evaluation tools offline.

🔗 Competition platform & test set access: https://rrc.cvc.uab.es/?ch=32
 📢 Stay informed: https://groups.google.com/g/icdar25-maptext-news

Whether you’ve been preparing for months or are just discovering the competition, we encourage you to take part and submit your results before the deadline.

We look forward to your contributions,
 — ICDAR 2025 MapText Organizers

Pedestrian Attribute Recognition (PAR) Contest 2025 – CAIP 2025

Pedestrian Attribute Recognition (PAR) Contest 2025
International Conference on Computer Analysis of Images and Patterns CAIP 2025
Conference Website: https://caip2025.com/
Contest Website: https://mivia.unisa.it/par2025/
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=== Important dates ===
Method Submission Deadline: May 31, 2025
Contest Paper Deadline: June 15, 2025
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=== Contest ===
Following the success of the previous edition presented during CAIP 2023, the Pedestrian Attribute Recognition (PAR) 2025 Contest is an international competition aimed at assessing methods for recognizing pedestrian attributes from images. We provide the participants with the Mivia PAR KD Dataset 2025, featuring newly annotated images with labels such as clothing color, gender and the presence or absence of a bag or hat. After the contest, the dataset—expanded with additional samples and annotations contributed by participants—will be made publicly available to the scientific community, with the goal to build one of the largest datasets for PAR with the considered set of annotations. Competing methods will be evaluated based on accuracy using a distinct private test set, separate from the training data. Recently, a wide variety of methods have been proposed to tackle the challenge of PAR in both effective and efficient ways. In the 2023 edition, the winning method, which leveraged Visual Question Answering (VQA), achieved remarkable success by integrating Large Language Models. This approach reached an impressive 92% accuracy on the contest’s private test set, highlighting the immense potential of Vision-Language Models (VLMs) in addressing complex PAR challenges. Considering the rapid advancements in VLMs over the past two years, we expect many of the proposed methods to take advantage of these cutting-edge technologies. However, the competition is not limited to a specific approach and every innovative solution is not only welcomed but highly valued, contributing to the ongoing progression of this field.
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=== Rules ===
The deadline for method submission is May 31, 2025. Submissions must be made via email, in which participants must share (either directly or via external links) the trained model, the code and a technical report of the method. The participants can obtain the training set, validation set and their annotations by sending an email, specifying their team name. They are allowed to use these provided training and validation samples and annotations but they may incorporate additional samples. However, the additional samples and annotations used must be made publicly available. Each participant must train a neural network to predict all the required pedestrian attributes for each sample. Teams are free to design novel neural network architectures, define new training procedures or propose innovative loss functions. Participants are highly encouraged to submit their contest papers via email by the deadline of June 15, 2025. The top three papers will be featured in the proceedings of the CAIP 2025 main conference. When submitting a paper, participants are requested to cite the official contest paper, which can be downloaded from the bibtex file or as follows:

Greco A., Vento B., “PAR Contest 2025: Pedestrian Attributes Recognition with Advanced Neural Networks”, 21st International Conference Computer Analysis of Images and Patterns, CAIP 2025

The detailed instructions can be downloaded here: https://mivia.unisa.it/par2025/
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The organizers,
Antonio Greco, University of Salerno, Italy
Bruno Vento, University of Naples – Federico II, Italy

Purdue Quantum AI Symposium CFP Deadline May 3 Abstract May 10 Paper

Quantum computing has emerged as a groundbreaking paradigm, offering the promise of unparalleled speed and efficiency in solving complex problems. This transformative technology has spurred rapid advancements in the fields of quantum artificial intelligence (Quantum AI) and beyond. By harnessing the principles of quantum mechanics, Quantum AI holds the potential to revolutionize disciplines such as machine learning, cryptography, optimization, and communication systems, paving the way for innovations that were once considered out of reach. 

This symposium aims to delve into the forefront of Quantum AI research, addressing key questions and exploring emerging possibilities. For more information, visit https://engineering.purdue.edu/IE/PurdueQuantumAIWorkshop2025 . This symposium will cover a wide range of topics at the intersection of quantum computing and artificial intelligence, including but not limited to:
  • Quantum Speedup for AI Algorithms: Harnessing quadratic and exponential speedups for optimization, search, and learning tasks.

  • Quantum Annealing and Combinatorial Optimization: Exploring applications of quantum annealers in solving NP-hard problems and industry-specific use cases.

  • Quantum Generative AI: Developing and analyzing quantum-enhanced generative models for data synthesis, creativity, and simulation.

  • Hybrid Quantum-Classical Architectures: Designing systems that leverage the strengths of both classical and quantum computation for scalable AI solutions.

  • Quantum Neural Networks (QNNs): Advancing the design and application of neural networks operating in the quantum regime.

  • Quantum Computing in Natural Language Processing (NLP): Leveraging quantum algorithms to enhance language understanding and semantic analysis.

  • Quantum Cryptography and Secure AI Models: Addressing the challenges of integrating quantum-based security measures in AI systems.

  • Error Mitigation and Fault Tolerance in Quantum AI: Developing methods to ensure reliability and scalability of quantum computations.

  • Quantum Hardware for AI: Investigating advancements in qubit technologies and their implications for AI workloads.

  • Ethics and Societal Impact of Quantum AI: Analyzing the broader implications of quantum technologies on society, ethics, and policy.

  • Business and Industry Applications of Quantum AI: Exploring viable models for deploying quantum-enhanced AI in sectors like finance, healthcare, logistics, and telecommunications.

  • Role of Quantum AI in Augmenting Human Work: Improving productivity, creativity, and workplace ergonomics with Quantum AI.

  • Quantum Transformation in Industrial Engineering: Transitioning industrial practices to leverage quantum paradigms.

  • Future of Education: Reshaping curricula and research directions to integrate Quantum AI advancements.


    We welcome submissions of regular papers, review papers, tutorials, position papers. Submission deadline is May 10, 2025. Please see https://engineering.purdue.edu/IE/PurdueQuantumAIWorkshop2025 for details. 

    Best,

    Vaneet Aggarwal

    Professor, Purdue University

ICCNS 2025 CFP: The International Conference on Intelligent Computing, Communication, Networking and Services, Varna, Bulgaria, 1 to 4 Sept. 2025

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