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This document provides a summary of proposals for extending agreements on inter-vendor AI/ML model training collaboration, including dataset exchange and model parameter sharing for NR air interface.
Year:
2026
Region / City:
Gothenburg, Sweden
Topic:
Inter-vendor training collaboration in AI/ML models for NR air interface
Document Type:
Meeting Agenda
Organization / Institution:
3GPP TSG RAN WG1
Author:
Moderator (Apple), Huaning Niu
Target Audience:
3GPP participants, RAN1, RAN4 experts
Period of Validity:
February 9th – 13th, 2026
Approval Date:
February 9th, 2026
Date of Changes:
N/A
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Year:
2026
Meeting:
3GPP TSG RAN WG1 #124
Document Number:
R1-2601149
Agenda Item:
9.1.2
Location:
Gothenburg, Sweden
Date:
Feb 9–13, 2026
Source:
Moderator (Apple)
Title:
FL summary # 1 for inter-vendor training collaboration
Document For:
Discussion/Decision
Topic:
Inter-vendor training collaboration for two-sided AI/ML models
Related Work Item:
RP-253340 “Revised WID: Artificial Intelligence (AI)/Machine Learning (ML) for NR air interface phase 2”
Technical Scope:
Direction C reference model; Direction A options 3a-1 and 4-1; standardized dataset format/content; encoder model structure; parameter and dataset exchange; CSI compression
Contributing Companies:
Apple, OPPO, Lenovo, NTT DOCOMO, Huawei, HiSilicon, Ericsson, MediaTek, ZTE, CMCC, CATT, Panasonic, NEC, LG Electronics, Fujitsu, vivo, Samsung, Sony, InterDigital, ETRI, TCL, Xiaomi, IITM, Toyota
Contact Persons:
Huaning Niu; Wendong Liu; Vahid Pourahmadi; Xin Wang; Keyvan Zarifi; Yuan Li; Jingya Li; Xinlin Zhang; Pedram Kheirkhah Sangdeh; Reubengeorge Stephen; Hanchao Liu; Wenfeng Liu; Yi Zheng; Yongchang Liu; Qianrui Li; Tetsuya Yamamoto; Hidetoshi Suzuki; Xuan Tuong Tran; Shafivulla Sayyed; Peng Guan; Zhen He; Minseok Jo; Xin Wang; Liqiang Jin; Yuanyuan Wang; Ameha Tsegaye Abebe; Chen Sun; Yingshuang Bai; Afshin Haghighat; Anseok Lee; Pu Yuan; Tianqi Wu; Mu Qin; Liu Zhengxuan; Liu Min; Anil Kumar Y; Sai Praneeth K; Konstantinos Dimou; Takayuki Shimizu
Performance Metrics:
Average SGCS; Average NMSE; Optional NMSE and/or SGCS at X-percentiles
Open Issues:
Pairing ID uniqueness; impact of additional dataset samples; quantization codebook exchange method; rank association; per-layer CSI payload size consistency
Year:
2026
Location:
Gothenburg, Sweden
Event:
3GPP TSG RAN WG1 #124
Dates:
9–13 February 2026
Agenda Item:
9.1.2
Document ID:
R1-2601149
Title:
FL summary #1 for inter-vendor training collaboration
Source:
Moderator (Apple)
Moderator:
Huaning Niu
Organization:
3GPP TSG RAN Working Group 1
Topic:
Artificial Intelligence / Machine Learning for NR air interface
Subtopic:
Inter-vendor training collaboration for two-sided AI/ML models
Technical Scope:
AI/ML-based CSI compression, dataset exchange, model parameter exchange, encoder model structure specification
Related Work Item:
Revised WID “Artificial Intelligence (AI)/Machine Learning (ML) for NR air interface phase 2” (RP-253340)
Participants:
Apple, OPPO, Lenovo, NTT DOCOMO, Huawei, Ericsson, MediaTek, ZTE, CMCC, CATT, Panasonic, NEC, LG Electronics, Fujitsu, vivo, Samsung, Sony, InterDigital, ETRI, TCL, Xiaomi, IITM, Toyota
Document Type:
Technical meeting contribution / summary for discussion and decision
Purpose:
Summary of contributions and proposals discussed under agenda item 9.1.2 in RAN1 #124
Key Topics:
dataset format and exchange, encoder model structure standardization, pairing ID mechanism, CSI feedback and target CSI association
Performance Metrics Mentioned:
SGCS, NMSE
Year:
2026
Region / city:
Gothenburg, Sweden
Topic:
Artificial Intelligence (AI) / Machine Learning (ML) for NR air interface
Document Type:
Technical Report
Organization:
3GPP TSG RAN WG1
Author:
Moderator (Apple)
Target Audience:
Industry professionals and organizations in telecommunications
Effective Period:
2026-02-09 to 2026-02-13
Approval Date:
February 9th, 2026
Last Modified:
February 13th, 2026
Year:
2026
Location:
Gothenburg, Sweden
Organization:
3GPP TSG RAN WG1
Meeting:
RAN WG1 #124
Agenda Item:
9.1.2
Document ID:
R1-2601149
Title Reference:
FL summary #1 for inter-vendor training collaboration
Source:
Moderator (Apple)
Primary Contact:
Huaning Niu
Companies Involved:
Apple, OPPO, Lenovo, NTT DOCOMO, Huawei, HiSilicon, Ericsson, MediaTek, ZTE, China Mobile, CATT, Panasonic, NEC, LG Electronics, Fujitsu, vivo, Samsung, Sony, InterDigital, ETRI, TCL, Xiaomi, IITM, Toyota, Ofinno, Spreadtrum
Technical Domain:
AI/ML for NR air interface
Subject:
Inter-vendor training collaboration for AI/ML-based CSI compression
Related Work Item:
Artificial Intelligence (AI)/Machine Learning (ML) for NR air interface phase 2 (RP-253340)
Document Type:
Technical meeting contribution summary
Purpose:
Discussion and decision
Technical Scope:
Dataset exchange, encoder model structure, model parameter exchange, CSI feedback and target CSI association
Participants:
Multiple telecommunications vendors and research organizations
Contact Information Included:
Yes
Year:
2026
Region / City:
Gothenburg, Sweden
Topic:
Artificial Intelligence (AI) / Machine Learning (ML)
Document Type:
Meeting Document
Organization / Institution:
3GPP TSG RAN WG1
Author:
Moderator (Apple), Huaning Niu, et al.
Target Audience:
3GPP TSG RAN WG1 members, vendors
Period of Validity:
2026
Approval Date:
February 2026
Date of Changes:
N/A
Contact Information:
[email protected], [email protected], etc.
Summary:
The document summarizes proposals and contributions regarding inter-vendor AI/ML-based training collaboration within the context of the 3GPP RAN1 #124 meeting.
Year:
2015
Region / City:
London, UK
Topic:
Fetal and neonatal echocardiography
Document Type:
Research Article
Authors:
Dr. Olga Patey, Professor Julene S. Carvalho, Professor Basky Thilaganathan
Target Audience:
Medical professionals, researchers
Period of Study:
2012–2015
Approval Date:
2012
Modification Date:
Not specified
Keywords:
fetal heart, fetal echocardiography, myocardial deformation, neonatal echocardiography, speckle tracking, tissue Doppler imaging, repeatability, reproducibility
Context Description:
The document evaluates the inter-vendor reproducibility and observer repeatability of TDI and STE measurements in normal term fetuses and neonates, emphasizing the challenges in comparing echocardiographic findings across different ultrasound systems.
Year:
2026
Region / City:
Gothenburg, Sweden
Topic:
AI/ML Inter-vendor Collaboration
Document Type:
Report
Organization:
3GPP
Author:
Moderator (Apple), Huaning Niu
Target Audience:
Industry professionals in AI/ML and 3GPP members
Action Period:
February 9th - 13th, 2026
Approval Date:
Not specified
Date of Changes:
Not specified
Note:
Summary
Year:
2026
Region / City:
Gothenburg, Sweden
Theme:
AI/ML in NR air interface
Document Type:
Discussion/Decision
Organization / Institution:
3GPP TSG RAN WG1
Author:
Huaning Niu (Apple), Wendong Liu (OPPO), Vahid Pourahmadi (Lenovo), Xin Wang (NTT DOCOMO), Keyvan Zarifi (Huawei), et al.
Target Audience:
Industry professionals in wireless communications and AI/ML
Period of Application:
2026
Approval Date:
February 9th – 13th, 2026
Date of Changes:
Not specified
Year:
2026
Region / City:
Gothenburg, Sweden
Topic:
Inter-vendor AI/ML training collaboration
Document Type:
Meeting Summary
Organization:
3GPP TSG RAN WG1
Author:
Moderator (Apple)
Target Audience:
3GPP Members
Period of Validity:
February 9th – 13th, 2026
Approval Date:
N/A
Modification Date:
N/A
Year:
2026
Location:
Gothenburg, Sweden
Subject:
AI/ML-based inter-vendor training collaboration for NR air interface
Document Type:
Meeting summary / technical report
Organization:
3GPP TSG RAN WG1
Authors:
Moderator (Apple), Huaning Niu; contributions from OPPO, Lenovo, NTT DOCOMO, Huawei, Ericsson, MediaTek, ZTE, CMCC, CATT, Panasonic, NEC, LG Electronics, Fujitsu, vivo, Samsung, Sony, InterDigital, ETRI, TCL, Xiaomi, IITM, Toyota, Ofinno, Spreadtrum, China Telecom, Futurewei
Agenda Item:
9.1.2
Reference:
RP-253340, Revised WID: Artificial Intelligence (AI)/Machine Learning (ML) for NR air interface phase 2
Key Topics:
Direction C reference model, Direction A sub-options 3a-1 and 4-1, standardized dataset and parameter exchange, performance metrics (SGCS/NMSE), RAN1 scalability study outcomes
Meeting Dates:
Feb 9–13, 2026
Contact Emails:
[email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected]
Year:
2026
Location:
Gothenburg, Sweden
Subject:
AI/ML inter-vendor training collaboration for NR air interface
Document type:
Meeting report / Summary
Organization:
3GPP TSG RAN WG1
Authors:
Huaning Niu (Apple), Wendong Liu (OPPO), Vahid Pourahmadi (Lenovo), Xin Wang (NTT DOCOMO), Keyvan Zarifi & Yuan Li (Huawei, HiSilicon), Jingya Li & Xinlin Zhang (Ericsson), Pedram Kheirkhah Sangdeh & Reubengeorge Stephen (MediaTek), Hanchao Liu & Wenfeng Liu (ZTE), Yi Zheng & Yongchang Liu (CMCC), Qianrui Li (CATT), Tetsuya Yamamoto, Hidetoshi Suzuki & Xuan Tuong Tran (Panasonic), Shafivulla Sayyed, Peng Guan & Zhen He (NEC), Minseok Jo (LG Electronics), Xin Wang & Liqiang Jin (Fujitsu), Yuanyuan Wang (vivo), Ameha Tsegaye Abebe (Samsung), Chen Sun & Yingshuang Bai (Sony), Afshin Haghighat (InterDigital), Anseok Lee (ETRI), Pu Yuan & Tianqi Wu (TCL), Mu Qin, Liu Zhengxuan & Liu Min (Xiaomi), Anil Kumar Y & Sai Praneeth K (IITM), Konstantinos Dimou & Takayuki Shimizu (Toyota), Jaehoon Chung (Ofinno), Zhe Yu (Spreadtrum), Nanxi Li & Yueyan Chu (China Telecom), Baoling Sheen (Futurewei)
Agenda item:
9.1.2
Period:
Feb 9–13, 2026
Source:
Moderator (Apple)
Status:
Discussion/Decision
Focus:
Specification of standardized dataset format/content, parameter exchange, RAN1 scalability, AI/ML CSI compression models
Year:
2026
Location:
Gothenburg, Sweden
Subject:
AI/ML-based NR air interface inter-vendor training
Document type:
Meeting summary / Technical contribution
Organization:
3GPP TSG RAN WG1
Author:
Moderator (Apple), Huaning Niu
Participants:
Apple, OPPO, Lenovo, NTT DOCOMO, Huawei, Ericsson, MediaTek, ZTE, CMCC, CATT, Panasonic, NEC, LG Electronics, Fujitsu, vivo, Samsung, Sony, InterDigital, ETRI, TCL, Xiaomi, IITM, Toyota, Ofinno, Spreadtrum, China Telecom, Futurewei
Agenda item:
9.1.2
Period:
Feb 9–13, 2026
Topics covered:
Standardized dataset format, model parameter exchange, Direction A 3a-1 and 4-1, Direction C reference model, RAN1 scalability study outcomes, inter-vendor AI/ML collaboration agreements
Contact emails:
Provided for all participating companies
Year:
2021
Region / City:
Not specified
Topic:
Clinical practice guidelines, rehabilitation, stroke
Document Type:
Interview transcript
Organization / Institution:
Academy of Neurologic Physical Therapy, Jefferson College of Rehabilitation Sciences, Boston University
Authors:
Dr. Therese Johnston, Dr. Lisa Brown
Target Audience:
Clinicians, rehabilitation professionals, researchers
Period of Validity:
Not specified
Approval Date:
Not specified
Date of Changes:
Not specified
Year:
2018
Region / City:
N/A
Topic:
Evidence and gap maps
Document Type:
Report
Organization:
Campbell Collaboration
Authors:
Howard White, Vivian Welch, Terri Pigott, Zack Marshall, Birte Snilstveit, Christine Mathew, Julia Littell
Target Audience:
Authors and researchers involved in creating evidence and gap maps
Period of Validity:
N/A
Approval Date:
February 2018
Date of Changes:
February 2018
Year:
2018
Region / city:
Unknown
Theme:
Evidence mapping, Research methodology
Document type:
Checklist
Organization:
Campbell Collaboration
Author:
Howard White, Vivian Welch, Terri Pigott, Zack Marshall, Birte Snilstveit, Christine Mathew, Julia Littell
Target audience:
Authors of evidence and gap maps
Period of validity:
Not specified
Approval date:
11 April 2018
Date of revisions:
Not specified
Year:
N/A
Region / City:
N/A
Topic:
Research Collaboration, Authorship, Intellectual Property
Document Type:
Guideline
Author:
N/A
Target Audience:
Research Teams, Academics
Period of Validity:
N/A
Approval Date:
N/A
Modification Date:
N/A
Year:
2023
Region / city:
Australia, Aotearoa New Zealand
Topic:
Ultrasound Training, Clinical Assessment
Document type:
Training guidelines, Assessment form
Organization / institution:
ACEM, EMUGs Collaboration Working Group
Author:
ACEM and EMUGs Collaboration Working Group
Target audience:
Clinical Leads in Ultrasound, Healthcare professionals
Period of validity:
Not specified
Approval date:
Not specified
Date of changes:
Not specified
Year:
Not specified
Region / City:
Not specified
Topic:
Project management, collaboration
Document Type:
Process guide
Organization / Institution:
Swinerton
Author:
Not specified
Target Audience:
Subcontractors, General Contractors, Project Partners
Effective Period:
Not specified
Approval Date:
Not specified
Modification Date:
Not specified
Note:
Year
Year:
Not specified
Region / City:
Not specified
Subject:
Education, Curriculum and Instruction
Document Type:
Academic Program
Author:
Not specified
Target Audience:
Students of Ed.D. program
Period of validity:
Not specified
Approval Date:
Not specified
Date of Changes:
Not specified
Context:
An academic program outline detailing the courses, requirements, and residency activities for students pursuing a Doctorate in Education with a concentration in Curriculum and Instruction.