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20222026
most citedUnimodal Training-Multimodal Prediction: Cross-modal Federated Learning with Hierarchical Aggregation

5 citations · 17 across the 41 of their papers we have counts for

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Showing 2023Show all

3 papers · 1 filter

cs.CV2023

MChat: Empowering VLM for Multimodal LLM Interleaved Text-Image Generation

Xiaowei Chi, Junbo Qi, Rongyu Zhang +3

While current LLM chatbots like GPT-4V bridge the gap between human instructions and visual representations to enable text-image generations, they still lack efficient alignment me…

cs.CV2023

Weakly-Supervised Emotion Transition Learning for Diverse 3D Co-speech Gesture Generation

Xingqun Qi, Jiahao Pan, Peng Li +8

Generating vivid and emotional 3D co-speech gestures is crucial for virtual avatar animation in human-machine interaction applications. While the existing methods enable generating…

cs.LG2023★ 5 cited

Unimodal Training-Multimodal Prediction: Cross-modal Federated Learning with Hierarchical Aggregation

Rongyu Zhang, Xiaowei Chi, Guiliang Liu +3

Multimodal learning has seen great success mining data features from multiple modalities with remarkable model performance improvement. Meanwhile, federated learning (FL) addresses…