On the Benefits of Early Fusion in Multimodal Representation Learning

14 November 2020

Papers citing "On the Benefits of Early Fusion in Multimodal Representation Learning"

7 / 7 papers shown

Title
I2MoE: Interpretable Multimodal Interaction-aware Mixture-of-Experts Jiayi Xin Sukwon Yun Jie Peng Inyoung Choi Jenna L. Ballard Tianlong Chen Qi Long MoE 28 0 0 25 May 2025
TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis Sabera Talukder Yisong Yue Georgia Gkioxari AI4TS 145 14 0 03 Jan 2025
Learnable Expansion of Graph Operators for Multi-Modal Feature Fusion Dexuan Ding Lei Wang Liyun Zhu Tom Gedeon Piotr Koniusz 134 9 0 02 Oct 2024
GraFT: Gradual Fusion Transformer for Multimodal Re-Identification Haoli Yin Jiayao Li Eva Schiller Luke McDermott Daniel Cummings 89 7 0 25 Oct 2023
AutoFraudNet: A Multimodal Network to Detect Fraud in the Auto Insurance Industry Azin Asgarian Rohit Saha Daniel Jakubovitz Julia Peyre 62 2 0 15 Jan 2023
Learning Multimodal Data Augmentation in Feature Space Zichang Liu Zhiqiang Tang Xingjian Shi Aston Zhang Mu Li Anshumali Shrivastava A. Wilson 98 23 0 29 Dec 2022
Beyond Just Vision: A Review on Self-Supervised Representation Learning on Multimodal and Temporal Data Shohreh Deldari Hao Xue Aaqib Saeed Jiayuan He Daniel V. Smith Flora D. Salim AI4TS 75 37 0 06 Jun 2022