3 papers indexed
Zinan Tang, Yukun Zhang, Shaomian Zheng, Zhuoshi Pan, Qizhi Pei, Dingnan Jin, et al.
In Large Language Model (LLM) training, data mixing plays a pivotal role in determining model performance. Recent methods optimize mixture weights via proxy models, but they rely on the assumption of static data distributions. As a result, when the underlying data pool shifts, th…
Ziqi Zhou, Weize Quan, Mining Tan, Zhihan Chen, Dandan Zheng, Jingdong Chen, et al.
Composition is a high-level visual intent that governs where subjects are placed and how a scene is organized, yet current unified multimodal models remain unreliable at fine-grained composition recognition and struggle to turn such intent into controllable generation. We present…
Tabinda Naz Syed, Jun Zhou, Imran Ali Lakhiar, Francesco Marinello, Tamiru Tesfaye Gemechu, Luke Toroitich Rottok, et al.
Autonomous navigation in agricultural environments requires precise obstacle classification to ensure collision-free movement. This study proposes a convolutional neural network (CNN)-based model designed to enhance obstacle classification for agricultural robots, particularly in…