7 papers indexed
Jinting Yan, Chen Kuang, Xiao Liang, Xinquan Sun, F N Chen
Introduction Prosodic focus marking plays a central role in conveying information structure, yet little is known about how Mandarin-speaking children with autism spectrum disorder (ASD) use acoustic cues to signal contrastive focus in a tonal language. Methods Prosodic focus mark…
Eric Hanchen Jiang, Zhi Zhang, Yuchen Wu, Levina Li, Dong Liu, Xiao Liang, et al.
Large Language Model (LLM) agents increasingly rely on external memory systems to accumulate experience across tasks. Yet nearly all existing approaches, from graph-structured memories to reflective insight stores, access memory through fixed, hand-designed heuristics. We argue t…
Ziyang Zhang, Boyang Zhou, Zesong Yang, Haocheng Peng, Zeming Gai, Xiao Liang, et al.
Real-time navigation in cluttered and dynamic environments requires collision-free and dynamically feasible motion under limited perception. However, feasible navigation behaviors are inherently multimodal because multiple paths may exist around obstacles. In this paper, we formu…
Eric Jiang, Xiao Liang, Yikai Zhang, Yingjia Wan, Mengting Li, Haikang Deng, et al.
Recent developments in AI for Mathematics (AI4Math), especially Large Language Model (LLM)-driven theorem provers, has achieved remarkable success in formal proof generation for well-defined mathematical problems through Interactive Theorem Proving (ITP) languages. However, curre…
Runwei Guan, Shaofeng Liang, Jiacheng Weng, Xiaoyi Gu, Jia Weng, Daizong Liu, et al.
Male infertility contributes substantially to the global infertility burden, and sperm analysis remains central to diagnosis, treatment planning, and assisted reproductive technology. Conventional semen evaluation, however, is labor-intensive, operator-dependent, and limited by i…
Efficient and intelligent post-earthquake structural damage assessment is critical for rapid disaster response. Although data-driven approaches have shown promise in this domain, traditional supervised learning relies on large labeled datasets that are impractical to obtain for e…
Rapid and reliable post-earthquake damage assessment is critical for public safety, re-occupancy decisions, and effective emergency response. This paper presents a physics-informed, unsupervised learning framework that enables structural damage diagnosis in sparsely instrumented…