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Reading list for research topics in multimodal machine learning

Collection of advice for prospective and current PhD students

[NeurIPS 2021] Multiscale Benchmarks for Multimodal Representation Learning

[NeurIPS 2019 FL workshop] Federated Learning with Local and Global Representations

[TMLR 2022] High-Modality Multimodal Transformer

[AAAI 2018] Memory Fusion Network for Multi-view Sequential Learning

[ICLR 2023] MultiViz: Towards Visualizing and Understanding Multimodal Models

[NeurIPS 2023, ICMI 2023] Quantifying & Modeling Multimodal Interactions

[NeurIPS 2023] Factorized Contrastive Learning: Going Beyond Multi-view Redundancy

[ICLR 2019] Learning Factorized Multimodal Representations

[ACL 2020] Towards Debiasing Sentence Representations

[ICML 2021] Towards Understanding and Mitigating Social Biases in Language Models