2 citations · 4 across the 4 of their papers we have counts for
4 papers
ISAM-MTL: Cross-subject multi-task learning model with identifiable spikes and associative memory networks
Junyan Li, Bin Hu, Zhi-Hong Guan
Cross-subject variability in EEG degrades performance of current deep learning models, limiting the development of brain-computer interface (BCI). This paper proposes ISAM-MTL, whi…
LSceneLLM: Enhancing Large 3D Scene Understanding Using Adaptive Visual Preferences
Hongyan Zhi, Peihao Chen, Junyan Li +6
Research on 3D Vision-Language Models (3D-VLMs) is gaining increasing attention, which is crucial for developing embodied AI within 3D scenes, such as visual navigation and embodie…
MultiPLY: A Multisensory Object-Centric Embodied Large Language Model in 3D World
Yining Hong, Zishuo Zheng, Peihao Chen +3
Human beings possess the capability to multiply a melange of multisensory cues while actively exploring and interacting with the 3D world. Current multi-modal large language models…
CoVLM: Composing Visual Entities and Relationships in Large Language Models Via Communicative Decoding
Junyan Li, Delin Chen, Yining Hong +4
A remarkable ability of human beings resides in compositional reasoning, i.e., the capacity to make "infinite use of finite means". However, current large vision-language foundatio…