Conferences: CV4Edu@CVPR CfP

February 5th, 2026 Daniela Lopez de Luise
Hi all,

We are excited to invite submissions to CV4Edu, an interdisciplinary workshop at CVPR 2026 in Denver, bringing together researchers in AI in education, computer vision, and human-centered AI.

The workshop focuses on multimodal perception in classrooms and the challenges of building interpretable, reliable, and privacy-aware AI systems for modeling engagement, self-regulation, and collaboration in real learning environments. 

We welcome work on multimodal modeling, behavioral forecasting, cognitive state inference, privacy-aware benchmarks, real-world deployments, multimodal learning, CV “in the wild”, etc. — as long as the paper makes a clear link to education or learning environments (even if that’s primarily in the discussion), e.g., by indicating applicability beyond benchmark datasets/tasks and explaining potential relevance in noisy educational settings.


Formats: Full, short, or position papers (archival/non-archival in CVPR Style) 

Submission deadline: March 12, 2026

Website: https://cv4edu.github.io/

We hope you’ll join us.

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Webinar by: Henning Wachsmuth (Leibniz University Hannover)

February 5th, 2026 Daniela Lopez de Luise
Dear colleague,

We are happy to announce the next webinar in the Language Technology webinar series organized by The HiTZ Chair of Artificial Intelligence and Language Technology (https://hitz.eus/katedra). We are organizing one seminar every month.

Next webinar:

Speaker: Henning Wachsmuth (Leibniz University Hannover)
Title: Toward Argumentative Large Language Models
Date: Thursday, February 5, 2026 – 15:00

Summary: Today's large language models (LLMs) are optimized toward giving helpful answers in response to prompts. In many situations, however, it may be preferable for an LLM to foster critical thinking rather than just following an instruction. While recent LLMs are said to 'reason', they barely build on established reasoning concepts known from argumentation theory. In this talk, I will give insights into recent efforts of my group in making LLMs more argumentative. Starting from basics of LLM training processes, I will present how to specialize LLMs for argumentation tasks via instruction fine-tuning as well as how to align the arguments they generate using reinforcement learning. From there, I will give an outlook on how to improve the actual reasoning capabilities of LLMs.

Bio: Henning Wachsmuth leads the Natural Language Processing Group at the Institute of Artificial Intelligence of Leibniz University Hannover. After receiving his PhD from Paderborn University in 2015, he worked as a PostDoc at Bauhaus-Universität Weimar and as a junior professor in Paderborn, before he became a full professor in Hannover in 2022. His group does basic research on large language models for computational argumentation, social bias detection and mitigation, as well as explainable and educational NLP. Henning's main research interests include the generation of audience-aware text, the assessment of pragmatic text quality, and the modeling of bias and framing.

Registration: https://www.hitz.eus/webinar_izenematea

Upcoming webinars:

  • José Andrés González-López (March 5)
  • Ranjay Krishna (April 16)
  • Barbara Plank (May 7)

You can view the videos of previous webinars and the schedule for upcoming webinars here: http://www.hitz.eus/webinars

If you cannot attend this seminar, but you want to be informed of the following HiTZ webinars, please complete this registration form instead: http://www.hitz.eus/webinar_info

Best wishes,

The HiTZ Chair of Artificial Intelligence and Language Technology

P.S: HiTZ will not grant any type of certificate for attendance at these webinars.

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1rst call for contributions to the PhD Forum of the 24th International Symposium on Intelligent Data Analysis (IDA)

February 5th, 2026 Daniela Lopez de Luise
IDA 2026 PhD Forum

Call for papers
Leiden (Netherlands) April 22-24, 2026 (Wednesday – Friday)

https://ida2026.liacs.nl/

IDA is organizing the 2026 edition of the PhD Forum, aimed at PhD students.

This mentoring program aims to connect PhD students with senior scientists who share their experience to help advance the students’ research and academic careers. Meetings will be arranged during the conference to allow discussion between the students and mentors.

Objectives

The objectives of the PhD Forum are:

  • to provide doctoral researchers with the opportunity to present their ongoing work and receive constructive feedback from experienced researchers (e.g., IDA Senior Program Committee members),

  • to facilitate the establishment of contacts with research teams working in related areas,

  • to provide insights into current research trends related to the students' research topics, thereby expanding the scope of their knowledge.

Submission

The PhD Forum welcomes original research in the field of Intelligent Data Analysis conducted by early-career researchers. Papers will be evaluated based on their relevance to the conference themes and the ability of the student to present:

  • the research problem and why it is important to address it,

  • the research objectives and questions,

  • the planned approach and methods to tackle the problem,

  • an outline of the current state of knowledge on the research problem,

  • the expected outcomes of the research, such as overviews, algorithms, improved understanding of a concept, a pilot study, a model, or a system.

Short papers (2 pages, including references) must follow the general template provided by the IDA conference (https://www.springer.com/gp/computer-science/lncs/conference-proceedings-guidelines).

Submissions will be handled through CMT:  https://cmt3.research.microsoft.com/IDA2026/

(Authors are requested to ensure that they select the IDA2026-PhDTrack).

The authors of accepted presentations will be required to prepare a poster and a presentation. The poster will serve as a basis for discussions during the conference, while the presentation will be used in the mentorship program. Authors of accepted presentations must register in order to participate in the mentorship program. All presentations and interactions will take place in person.

Reduced registration fees are available for students:

Early registration (Deadline: March 16): 249.00 € / Late registration: 399.00 €

The registration fees include:

  • All sessions

  • Coffee breaks

  • Lunches

  • Social events: opening reception, traditional social event.

Important dates

  • Two-page paper submission deadline: February 23, 2026 AOE (Monday)

  • Notification to authors: March 2, 2026 (Monday)

  • Registration (for accepted submissions): March 16, 2026 (Monday)

  • Conference dates:  April 22-24 2026

Contact

Christine Sinoquet – IDA 2026 PhD Forum Chair

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IEEE International Joint Conference on Biometrics (IJCB 2026)

February 3rd, 2026 Daniela Lopez de Luise
IEEE International Joint Conference on Biometrics (IJCB 2026)
Rome, Italy – September 1-4, 2026
Website: https://ijcb2026.ieee-biometrics.org

The IEEE International Joint Conference on Biometrics (IJCB 2026) is the
premier international forum for cutting-edge research in biometrics and
related areas. IJCB brings together two major conferences — the IEEE
Biometrics Theory, Applications, and Systems (BTAS) and the IAPR
International Conference on Biometrics (ICB) — and is sponsored by the
IEEE Biometrics Council and the IAPR Technical Committee on Biometrics
(TC-4).

We invite submissions of original and unpublished research papers
addressing theoretical advances, applications, and interdisciplinary
developments in biometrics. Submissions under review elsewhere will not
be considered.

Topics of Interest
Topics include, but are not limited to, the following areas:
– Biometric modalities: face, fingerprint, iris, palmprint, vein,
periocular, ear, voice, gait, signature, touch dynamics, behavioral
biometrics
– Deepfake detection and AI-generated content verification
– Multimodal and multispectral biometric systems
– Presentation Attack Detection (PAD) and anti-spoofing techniques
– Template security and privacy protection: encryption, secure storage,
anonymization, differential privacy
– Bias, fairness, explainability, and transparency in biometric systems
– Machine learning for biometrics: deep learning, transfer learning,
continual learning, efficient/compact models, transformers
– Evaluation protocols and benchmarking, performance modeling, new
datasets and large-scale studies
– Biometrics in forensics and law enforcement, large-scale
identification, border control
– Emerging applications: IoT, wearable devices, mobile biometrics,
healthcare, human-computer interaction
– Ethical, legal, and societal implications: compliance with regulations
(GDPR, AI Act), human rights, societal acceptance

Submission Guidelines
– Manuscripts must be in English and formatted according to the IEEE
conference template.
– Maximum length: 8 pages (excluding references).
– The review process will be double-blind. Authors must remove all
personally identifying information, including names and affiliations.
– Submissions must be made electronically via the conference submission
portal, which will be available on the official IJCB 2026 website.
Accepted papers will be published in IEEE Xplore, provided they meet
IEEE’s publication and quality standards.

Important Dates
Full paper submission               April 10, 2026
Notification of paper acceptance    June  10, 2026
Camera-ready paper submission       July  10, 2026

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A New Dataset for Geospatial Visual Localisation: egenioussBench

February 3rd, 2026 Daniela Lopez de Luise
Determining a camera’s pose from images – known as visual localisation- is fundamental to applications from autonomous driving and robotics to augmented reality, yet existing datasets face two key issues. They either lack the scale needed for large-scale scenes, limiting progress towards truly scalable methods. Second, when they do cover large scenes, they often provide imprecise ground truth poses for the query image data. egenioussBench overcomes these limitations by pairing a high-resolution aerial 3D mesh and a CityGML LoD2 model as geospatial referee data and a map-independent ground-level smartphone imagery with centimetre-accurate poses obtained via PPK and GCP/CP-aided adjustment as query data.

The benchmark offers:

-A high-resolution aerial 3D Mesh and a CityGML LoD2 model as geospatial reference data
-A test split of 42 non-co-visible query images with withheld ground truth
-A validation split of 412 sequential query images with released poses
-A public leaderboard, evaluated with multi-threshold binning metrics and comprehensive global statistics

More information, including a link to a paper, can be found at https://www.isprs.org/resources/datasets/benchmarks/egenioussBench/Default.aspx

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