3 citations · 3 across the 1 of their papers we have counts for
2 papers
cs.CV2024
RoDE: Linear Rectified Mixture of Diverse Experts for Food Large Multi-Modal Models
Pengkun Jiao, Xinlan Wu, Bin Zhu +3
Large Multi-modal Models (LMMs) have significantly advanced a variety of vision-language tasks. The scalability and availability of high-quality training data play a pivotal role i…
cs.CL2024★ 3 cited
AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling
Jun Zhan, Junqi Dai, Jiasheng Ye +13
We introduce AnyGPT, an any-to-any multimodal language model that utilizes discrete representations for the unified processing of various modalities, including speech, text, images…