Papers with multimodal learning tasks

2 papers
Multimodal Phased Transformer for Sentiment Analysis (2021.emnlp-main)

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Challenge: Existing methods to model multimodal sentiment analysis are limited due to their complexity and memory footprint.
Approach: They propose a multimodal Sparse Phased Transformer to reduce self-attention complexity and memory footprint.
Outcome: The proposed method achieves comparable or superior performance with a 90% reduction in the number of parameters.
VisualRWKV: Exploring Recurrent Neural Networks for Visual Language Models (2025.coling-main)

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Challenge: Visual Language Models (VLMs) have been gaining popularity with large language models, but few attempts have been made to incorporate efficient linear Recurrent Neural Networks (RNNs) into VLMs.
Approach: They propose a linear RNN model with a data-dependent recurrence and sandwich prompts to enhance modeling capabilities and a 2D image scanning mechanism to enrich the processing of visual sequences.
Outcome: The proposed model achieves competitive performance compared to Transformer-based models on various benchmarks.

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