GC-P8: Multimodal Learning for 6G Wireless Communications (CONVERGE)
Poster
Thu, 7 May, 14:00 - 16:00
Location: Poster Area 43
Session Type: Poster
Track: SP Grand Challenges
Click the to view the manuscript on IEEE Xplore Open Preview

GC-P8.9: CONVERGE CHALLENGE: MULTIMODAL LEARNING FOR 6G WIRELESS COMMUNICATIONS
Jichao Chen, EURECOM, France; Filipe Borges Teixeira, Francisco Manuel Ribeiro, INESC TEC, Portugal; Ahmed Alkhateeb, Arizona State University, United States of America; Manuel Ricardo, Luis Manuel Pessoa, INESC TEC, Portugal; Dirk Slock, EURECOM, France

GC-P8.10: ICASSP 2026 CONVERGE Challenge: Multimodal Fingerprinting for UE Localization
Norshahida Saba, Hanan Al-Tous, Aalto University, Finland

GC-P8.11: WEIGHTED VISION-RADIO FUSION FOR SHORT-TERM BLOCKAGE PREDICTION IN MMWAVE SYSTEMS
Aadhya Agrawal, Puppala Jyothi Srinidhi, R.V.S.R Rupesh, Tubati Vangmayi, Rimalapudi Sarvendranath, Indian Institute of Technology Tirupati, India, India

GC-P8.12: A Vision-and-Radio Transformer for the ICASSP 2026 Multimodal Learning for 6G Wireless Communications Challenge
Botao Wu, Pengxuan Gao, Tianchi Lou, Kai Ying, Shanghai Jiao Tong University, China

GC-P8.13: VISION-FIRST MULTIMODAL FRAMEWORK FOR SHORT-TERM MMWAVE BLOCKAGE PREDICTION
Pratik Raj, Madhav Gopal Rayate, Praval Gupta, Kaushik Bharatiya, Rimalapudi Sarvendranath, IIT Tirupati, India