5 papers indexed
Shiyu Yuan, Sourav Sanjukta Bhabesh, Zhe Wang, Dmitriy Bespalov, Wesley Rose, Huzefa Rangwala
Vision Language Models (VLMs) demonstrate strong perceptual abilities but remain limited in tasks requiring analytical reasoning across multiple visual states, such as multi-image comparison, change detection, and multi-step visual inference. These capabilities are critical for r…
Kang Ding, Zhigui Lin, Hongsong Wang, Jie Gui, Qi Liu, Zhe Wang, et al.
This letter presents PrismAD, a decoupled end-to-end autonomous driving framework based on a Semantic Mixture-of-Planners. Existing planners usually aggregate heterogeneous scene tokens into a coupled representation space, forcing a single planning branch to jointly model agent i…
Yidong Ouyang, Zhe Wang, Sourav Bhabesh, Dmitriy Bespalov
Diffusion Language Models (DLMs) have recently achieved substantial progress in natural language generation tasks. Recent research demonstrates that adaptive token generation ordering can significantly improve performance in mathematical reasoning and code synthesis applications.…
Yizheng Wu, Hongwei Fan, Kewei Wang, Ruibo Li, Xingyi Li, Xiao Song, et al.
Motion understanding is critical for ensuring safety and robustness in autonomous driving systems, driving increasing interest in motion prediction. A key challenge in this domain is the high cost associated with acquiring real-world motion labels. It is therefore ideal if we cou…
Peng Zhang, Hanmei Yuan, Zhe Wang, Vitaly Petrov, Emil Björnson
At THz frequencies, the radiative near-field distance can be sufficiently large to matter in real deployments. Existing near-field formulas are often understood in a simple way: as the link distance decreases, the propagation regime is expected to change only once, i.e., from far…