Qiang Su

2 accepted papers

2024

Multi-Source Dynamic Interactive Network Collaborative Reasoning Image Captioning

ICASSP 2024accepted

Rich image and text features can largely improve the training of image captioning tasks. However, rich image and text features mean the incorporation of a large amount of unnecessary information. In our work, in order to fully explore and utilize the key information in images and text, we view the c…

Cited by 0 Source ↗Scholar ↗

2023

Adaptive Gating in Mixture-of-Experts based Language Models

Jiamin Li, Qiang Su, Yitao Yang, Yimin Jiang, Cong Wang, Hong Xu

EMNLP 2023long main

Large language models have demonstrated exceptional language understanding capabilities in many NLP tasks. Sparsely activated mixture-of-experts (MoE) has emerged as a promising solution for scaling models while maintaining a constant number of computational operations. Existing MoE models adopt a f…

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