7 papers indexed
Nanbeige Lab, :, Chen Yang, Chengrui Huang, Fufeng Lan, Hanhui Chen, et al.
We present Nanbeige4.2-3B, a compact general agentic model with 3B non-embedding parameters. It delivers strong performance across code-agent, office-agent, and complex tool-use tasks while maintaining highly competitive reasoning capabilities in mathematics, coding, and science.…
Y Wang, Chen Yang, Yucheng Zhang
Abstract Drive by the rapid envolution of deep-learning techniques, a large body of biological experiments bas has uncovered extensive associations between microRNAs (miRNAs) and complex human diseases, hig- hlighting the pivotal roles of miRNAs in pathogenesis. Elucidating these…
Bo Huang, Fengxiang Li, Hao Xu, Haoyang Huang, Hongyi Fu, Jinhua Hao, et al.
We present KAT-Coder-V2.5, a coding-focused agentic model trained to act autonomously inside real, executable repositories rather than as a single-turn code generator. Its capability is bottlenecked less by model scale than by the scarcity of reproducible environments, verifiable…
Zanwei Zhou, Jiazhong Cen, Jiemin Fang, Yumeng He, Chen Yang, Sikuang Li, et al.
Precise control over complex dynamics remains challenging for modern video generative models, as text prompts alone often cannot specify physically plausible, fine-grained motion and interactions. We introduce $\textit{proxy-conditioned video generation}$, where a coarse proxy vi…
Lev Sorokin, Chen Yang, Ken E. Friedl, Andrea Stocco
In the automotive domain, in-car scene understanding (ISU) enables the detection of safety-critical events, such as driver distraction, and supports drivers or passengers by analyzing the in-car scene and adapting the environment (e.g., ambient lighting). The industry is increasi…
Zheng Fang, Chen Yang, Yusen Tan, Yunpeng Zhao, Fanjie Xu, Hongxin Xiang, et al.
Nuclear Magnetic Resonance (NMR) spectroscopy is the gold standard for molecular structure elucidation, yet interpreting complex spectra for unknown molecules remains a bottleneck reliant on human expertise. While artificial intelligence has advanced this field, current methods f…
Chen Yang, Yuhao Wei, Ze Xu, Ziheng Zou, Shuang Liang, Delin Ouyang, et al.
Vision-Language Models (VLMs) provide powerful semantic understanding and commonsense reasoning for End-to-End Autonomous Driving (E2E-AD) planning. However, trajectories directly generated by VLMs often encode only coarse driving intentions and remain insufficient for geometrica…