AIxNET 2026, International Conference on Interconnected AI and NETworks 2026

Call for Papers

International Conference on Interconnected AI and NETworks 2026

AIxNET 2026

Nov. 23-25, 2026 – Paris, France

On-site event

https://aixnet.dnac.org/


Paper submission deadline: June 20, 2026

Networks are entering an era where both classical ML and emerging generative and agentic AI are transforming end‑to‑end networking—from intent capture to closed‑loop control across RAN, Core, transport, and edge/cloud. AIxNET welcomes contributions that advance algorithms, architectures, protocols, evaluations, and safeguards for trustworthy, explainable, and safe‑to‑operate AI‑driven networking. We particularly encourage rigorous comparative studies across control layers (SMO/intent vs near‑RT vs lower‑layer control), and the release of open datasets and artifacts to help the community build together. AIxNET is intending to build a stimulating, open, dynamic, and friendly forum to co‑create the future and spark collaborations across teams. The conference will be a unique opportunity to gather academic and industry research on this crucial topic for 2030 networks. Expect interactive sessions, demos, and time for discussion.

Main Topics of Interest include (but are not limited to)

  1. Agentic AI: from Human Intent to Action Autonomy 

· Networked “xLM” challenges: Intent capture/parsing/policy synthesis at SMO and service layers, use of Large, Small or Machine Language Models (LLM, SLM, MLM) · Hierarchical/heterogeneous agents spanning non‑RT and near‑RT control (e.g., O‑RAN RIC), Core CNFs, and edge resources · Agentic 6G functions · Interconnection and collaboration between AI agents · Tool and protocols for network‑facing agents (e.g., MCP‑enabled clients/servers), conflict resolution, safe rollbacks

  1. New paradigms for networking: from Classical ML to xLM-based Control at Scale 

· Supervised/unsupervised/self‑supervised learning for prediction, anomaly detection, resource allocation, QoE optimization · ML and LLM techniques for scheduling, slicing, mobility, energy saving; cross‑domain orchestration across RAN/Core/transport for B5G and 6G · Programmable data planes (P4/eBPF) and SDN control plane with ML‑in‑the‑loop; NWDAF‑enabled analytics · Challenges for access networks and edge networking, use of alternative models, SLM, TRM · Architecture and framework for agentic AI networking · Data collection and labeling

  1. Comparative Designs Across Layers: SMO/Intent vs Near‑RT vs Lower‑Layer Control 

· Side‑by‑side evaluations of top‑down (intent‑driven) vs bottom‑up (local) autonomy · Responsibility split across SMO policies, RIC xApps/rApps, Core functions, device/edge controllers · Stability, latency and safety; arbitration under competing objectives (QoE, energy, cost, SLAs) · Cross‑layer observability, auditability, and explainability methodologies

  1. Explainability and trustworthiness: Bias and Functional Safety 

· Human in the loop supervision and autonomy levels for safe operations · Explainability for operator oversight (pre/post methods, rationales, provenance, accountability logs) · Security and governance for AI‑operated changes (access control, authorization, verification, compliance‑by‑design) · Possible Bias sources and mitigation (data, prompts, tools, policies); fairness in resource allocation and service admission · Trust, safety and ethical considerations in generative and agentic AI networking

  1. Evaluation, Benchmarks, Open Datasets, and experimentations 

· Public datasets/benchmarks for RAN/Core/transport/edge; simulated vs real testbeds · Evaluation methodology and built of meaningful KPIs (e.g., relying on MTTR, SLO, energy–QoE trade‑offs…) · Network performance metric in generative and agentic AI communication systems · Digital twins, experimentation platforms, and testbeds for generative and agentic AI networking · Reproducible pipelines, artifact sharing, and insightful negative results, robustness to drift · Sustainability and cost modeling (e.g., compute budgets, edge vs cloud placement)


Submission types and guidelines

Authors are invited to submit original contributions that have not been published or submitted for publication elsewhere. Papers should be prepared using the IEEE 2-column conference style and are limited to 8 pages including references for regular papers, 5 pages including references for short papers and 2-4 pages for Demos/Positions. Papers must be submitted electronically in PDF format through EDAS at: https://edas.info/N35032

Open artifacts are encouraged: release code/data/measurement scripts when possible; otherwise provide high‑fidelity synthetic surrogates or detailed reproduction recipes. Comparative studies must clearly state the targeted control layer(s) and report stability/latency/safety metrics alongside performance.

For accepted papers to be included on AIxNEt 2026 proceedings, at least one author must register at the Author rate and papers must be presented in-person at the conference by a registered co-author.


Important dates

· Paper submission deadline: June 20, 2026 Paper Acceptance Notification: September 15, 2026 Camera‑ready: October 5, 2026 Conference Date: November 23-25, 2026


TPC Co-Chairs

Chiara Contoli (University of Urbino, Italy) Sahar Hoteit (Paris-Saclay University, France)

General Co-Chairs

Emmanuel Bertin(Orange Innovation, France) Stefano Secci (CNAM, France)


ChaLearn UDIVA-HHOI Challenge @ ECCV 2026 – Still Time to Participate!

 

Dear colleagues,

 

There is still plenty of time to participate in the ChaLearn UDIVA-HHOI Challenge @ ECCV 2026, organized within the CONTEXTUS Workshop at ECCV 2026.

 

Submission deadline: July 12th, 2026

 

The challenge focuses on advancing research in context-aware human behavior understanding and socially grounded multimodal intelligence, encouraging methods that go beyond isolated action recognition toward understanding how people collaborate, coordinate, anticipate, and influence one another in real-world environments.

 

Participants will work with the newly released UDIVA-HHOI dataset, a rich multimodal corpus featuring:

  • non-scripted dyadic collaborative interactions,
  • synchronized audio, video, and transcripts,
  • one exocentric and two egocentric views,
  • contextual metadata and social interaction cues,
  • procedural task information,
  • annotations of verbal and non-verbal human-human-object interaction events,
  • goals, intentions, and causal relationships.

 

The challenge includes 5 tracks:

  • Track 1: Multimodal Exocentric Event Recognition
  • Track 2: Multimodal Egocentric Event Recognition
  • Track 3: Multimodal Exocentric Event Anticipation
  • Track 4: Multimodal Egocentric Event Anticipation
  • Track 5: Multimodal Exocentric Causal Event Grounding

 

The top-ranked team in each track will receive a $1,000 USD award, along with certificates and the opportunity to present and publish their work at the ECCV 2026 CONTEXTUS Workshop.

 

Data, starting kit, track descriptions, and metrics are already available, and baseline models will be released soon.

 

We strongly encourage participation from researchers and students working on:

  • multimodal learning,
  • video understanding,
  • egocentric vision,
  • embodied AI,
  • social signal processing,
  • event anticipation,
  • causal reasoning,
  • human behavior understanding.

 

We look forward to seeing new advances toward AI systems capable of understanding human interactions, intentions, and collaborative behavior in complex real-world scenarios.

 

Challenge website: https://lap.chalearn.eu/public/udiva-hhoi-challenge-eccv26

 

Workshop website: https://lap.chalearn.eu/public/ECCV26-CONTEXTUS

 

Supported by ChaLearn, SurfingTech, and Google.

 

Organizers:
Cristina Palmero (King’s College London)
Sergio Escalera (Universitat de Barcelona & Computer Vision Center)
Albert Clapés (Universitat de Barcelona)
Xavier Baró (Universitat de Barcelona)
Daniele Berardini (Istituto Italiano di Tecnologia)
Hugo Jair Escalante (The University of Texas at El Paso & INAOE)
Vittorio Murino (Istituto Italiano di Tecnologia & University of Verona)

 

Challenge chairs:
Jeanfed Ramírez Lima, Luis J. Arellano

 

Advisory board:
Isabelle Guyon, Jeffrey Cohn

iLRN2027 Call for Special Track Proposals

I would like to draw your attention to the iLRN2027 Call for Special Track Proposals for the 13th Immersive Learning Research Network Conference, which will take place online and in person in Daegu, Republic of Korea. Please find details below. 

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Call for Special Track Proposals: 13th Immersive Learning Research Network (iLRN2027) Conference

Theme: “XR + AI Collaboration: Co-Creating Knowledge through Globally Situated Communities of Practice”

Online Conference Dates: June 11-13, 2027
Hosted by iLRN geographic chapters in their respective time-zones

In-person Conference Dates: June 26-29, 2027
Daegu, Republic of Korea – Humanities Korea Hall, Kyungpook National University

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Conference website: https://immersivelrn.org/ilrn2027/

The Immersive Learning Research Network (iLRN) invites proposals for Special Tracks to be featured at the 13th annual iLRN Conference. The conference will be held online (June 11–13, 2027) and in person at Kyungpook National University, Daegu, Republic of Korea (June 26–29, 2027).

The theme of iLRN2027, “XR + AI Collaboration: Co-Creating Knowledge through Globally Situated Communities of Practice”, explores the growing convergence of immersive technologies and artificial intelligence in learning, training, and knowledge creation. The conference seeks to advance our understanding of how XR and AI can support meaningful collaboration, innovation, and knowledge co-construction across diverse educational, professional, and cultural contexts.

Special Tracks provide an opportunity for researchers, educators, practitioners, artists, and developers to build focused scholarly communities around emerging or specialized topics in immersive learning that extend beyond the scope of the conference's main tracks.

SPECIAL TRACKS

Special Tracks should address innovative topics related to immersive learning and must be clearly distinct from the main conference tracks.

Potential areas of interest include, but are not limited to:

  • XR and Artificial Intelligence in Education
  • Human-AI Collaboration in Immersive Environments
  • Immersive Learning Analytics
  • AI-Enhanced Virtual Worlds
  • Extended Reality for Professional Development
  • Digital Twins and Immersive Simulation
  • Immersive Learning and Creativity
  • Immersive Technologies for Sustainability
  • Emerging Methodologies in XR Research
  • Ethical, Responsible, and Inclusive AI in Immersive Learning
  • Immersive Learning Communities of Practice
  • Future Directions in XR and AI Integration
MAIN CONFERENCE TRACKS

Special Track topics must be clearly differentiated from the following main conference tracks:

Track 1. Foundations of Immersive Learning Research and Theory

Track 2. Assessment and Evaluation (A&E)

Track 3. Galleries, Libraries, Archives & Museums (GLAM)

Track 4. Inclusion, Diversity, Equity, Access & Social Justice (IDEAS)

Track 5. STEM Education

Track 6. Language, Culture & Heritage (LCH)

Track 7. Medical & Healthcare Education (MHE)

Track 8. Nature & Environmental Sciences (NES)

Track 9. Workforce Development & Industry Training (WDIT)

Track 10. Self and Co-Regulated Learning with Immersive Learning Environments (SCILE)

SPECIAL TRACK REQUIREMENTS

Proposals should include:

  • A concise Special Track title and abbreviation.
  • Names and affiliations of the organizers (typically up to three co-chairs).
  • A description of the topic, themes, and relevance of the Special Track.
  • An explanation of how the proposed Special Track differs from the main conference tracks.
  • Information on previous editions of the Special Track (if applicable).
  • A public-facing description suitable for publication on the conference website.
  • Types of submissions accepted by the track.
  • A tentative Program Committee and reviewer list.
  • A description of the planned review process.
  • Short biographies of the organizers and their relevant experience.
ACCEPTED SUBMISSION TYPES

Special Tracks may accept the same submission categories as the main conference, including:

Academic Stream

  • Full Papers (12–15+ pages)
  • Short Papers (8–11 pages)
  • Extended Abstracts (4–7 pages)
  • Doctoral Colloquium submissions

iLEAD Stream

  • Oral Presentations
  • Poster Presentations
  • Workshops
  • Panel Sessions
  • Special Sessions
  • Guided Virtual Adventures
  • Product Demonstrations
RESPONSIBILITIES OF SPECIAL TRACK CHAIRS

Accepted Special Track organizers will be responsible for:

  • Promoting the Special Track.
  • Building and coordinating a Program Committee.
  • Managing the peer-review process using the conference EasyChair system.
  • Communicating with authors and reviewers.
  • Providing recommendations regarding acceptance and rejection decisions.
  • Preparing a summary abstract of the Special Track for publication in the conference proceedings.

The review process and submission deadlines must align with those of the main conference.

IMPORTANT DATES
  • Special Track Proposal Submission Deadline: June 15, 2026
  • Notification of Acceptance: June 23, 2026
  • Official Announcement of Accepted Special Tracks: June 30, 2026 (Athens, Greece)
  • Academic Paper Submission Deadline: October 4, 2026
HOW TO SUBMIT

Special Track proposals must be submitted through the official proposal form:

https://tally.so/r/0Qo55B

Examples of previous iLRN Special Tracks can be found in the iLRN2026 Call for Papers:

https://www.immersivelrn.org/ilrn2026/call-for-papers/

CONTACT

For questions regarding Special Track proposals, please contact:

ilrn2027@immersivelrn.org

For additional information, please visit:

https://immersivelrn.org/ilrn2027/

We look forward to receiving your proposals and to building vibrant new communities of practice around immersive learning, XR, and artificial intelligence at iLRN2027.

VISMAC Computer Vision Summer School in Siena, Italy

VISMAC 2026,  Siena, Italy,  September 21st to 25th, 2026
EARLY BIRD REGISTRATION DEADLINE: June 15th

Located just steps away from the University of Siena’s Engineering Department and the iconic Piazza del Campo, the school offers an intensive program designed for doctoral students, researchers, and industry professionals. VISMAC continues to serve as a premier venue for networking and professional growth within the computer vision community.

**Confirmed Keynote Speakers:**
The program features a distinguished lineup of international experts, including:
Dima Damen, University of Bristol
Iacopo Masi, University of Rome, La Sapienza
Lamberto Ballan, University of Padova
Vittorio Murino, University of Verona
Matteo Poggi, University of Bologna
Simone Calderara, University of Modena and Reggio Emilia
Luisa Verdoliva, University of Naples Federico II
Marina Paolanti, University of Macerata
Tomaso Fontanini, University of Parma

Massimiliano Mancini, University of Trento
(Additional speakers to be announced shortly)

**Registration and Information**
For full program details, accommodation information, and registration, please visit the official website: https://vismac2026.github.io/
Due to venue capacity, we anticipate a limited number of places. We encourage interested participants to register early to secure their attendance.
We kindly ask you to share this invitation with your students and colleagues who may benefit from this experience.

EARLY BIRD REGISTRATION ENDS SOON: June 15th

**Innovation and Industry Engagement**
This year, VISMAC is introducing a dedicated session for Startups and University Spinoffs. This initiative aims to bridge the gap between academic research and industrial application. It provides an excellent platform for companies to connect with emerging talent, while offering students and PhD candidates insights into entrepreneurial career paths and research-driven business opportunities.
Further details regarding sponsorship and industry participation can be found here: https://vismac2026.github.io/sponsor.html


July Seminars: Hands-on AI and Machine Learning for Researchers

Hello everyone,

Statistical Horizons and AI Horizons will host the following livestream seminars:

  • Using LLMs for Social Science Research*, taught by Ethan C. Busby, July 7-10. Explore the fundamentals of large language models (LLMs) and their applications in social and behavioral research, including open-ended response coding, synthetic sample generation, experimental treatments, and effective prompt engineering. Preview the first hour on YouTube!
  • Using AI to Build Better Experiments*, taught by Charles Crabtree, July 14-17. Use LLMs to improve experimental design, implementation, and analysis by generating and validating materials, building AI-powered chatbot studies, and applying automated text analysis. 
  • Claude-Powered Academic Research: From Ideation to Publication*, taught by Jeffrey DotsonJuly 21-24. Learn how to use Claude tools and GitHub to support the full academic research workflow, from refining research questions and organizing replication-ready codebases to wrangling data, running analyses, and preparing polished writing.
  • Machine Learning, taught by Bruce Desmarais, July 21-24. Gain a comprehensive understanding of machine learning concepts and practical applications, and use these powerful techniques to enhance your research and analysis. This training counts toward the 4-course Machine Learning Certification.

All seminars are livestreamed via Zoom, with full recordings available for asynchronous viewing.


Email natalie@statisticalhorizons.com with any questions.

Thanks,
Natalie
*This course is part of AI Horizons, a division of Statistical Horizons, that features livestream seminars on applied AI and LLM methods.

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