Folding changes the linearized aeroelastic spectrum and can switch which mode becomes unstable first, with consequences for local postflutter interactions. This study formulates a three-component Z-fold wing by assigning every aerodynamic station to a structural component and a material coordinate. The same attachment...
Ge-Lin Chen, Haolin Yang, Chen Song et al.· 0 citations
Solving high-dimensional structural model updating problems requires an algorithm capable of navigating complex, non-convex landscapes with correlated parameters. Existing hybrid evolutionary algorithms typically rely on static architectures or fixed switching rules, resulting in disjointed search phases. To address th...
L. Li, Rong-Ye Shi, Wanhuan Zhou State Key Laboratory of Internet of Things fo City et al.· 0 citations
To the best of this audit, this is the first automated system to synthesize this trace-tree model family, generate well-founded inversion proofs, and emit self-contained Lean 4 certificates.
Jia-Ming Zhao, Bing Wu, Tong-Bin Yang et al.· 0 citations
Multi-step tool-calling LLM agents rely on host runtimes to preserve state across turns. When a runtime carries an external tool return into later model inputs, providers meter it again. An admitted malicious or compromised tool can thereby convert untrusted data into recurring victim-billed processing without victim c...
Jin-Qian Zhang, Hao-Jun Xia, Shu-Jiang Wu et al.· 0 citations
This paper argues that the gap in machine intelligence's push into the physical world is structural, and locates where it can be legitimately closed, and gives the Promulgation Criterion, which fixes the runtime division of labor with LLMs.
PALATE (Person-Aligned LLM-Simulated-User Assessment with Tailored Evaluation with Tailored Evaluation), a scalable RPA benchmark built on user simulators, produces interpretable evaluations of specific user-RPA pairs rather than compressing systems into a single user-independent ranking.
Yuhan Zhu, Ming-Xuan Du, Benfeng Xu et al.· arXiv.org· 0 citations
Action-conditioned JEPA world models enable planning toward visually specified goals without reconstructing future pixels, yet latent prediction alone does not explicitly encourage the learned representations to retain information relevant to robotic control. We introduce an end-to-end JEPA world model that augments la...
Mu-Yuan Liu, Yue-Ning Huang, Zhe Liang et al.· 3 citations
High-throughput experimentation and self-driving laboratories are drastically accelerating materials discovery, yet automated interpretation of X-ray powder diffraction (XRPD) data remains a critical rate-limiting step. Conventional search-match workflows rely heavily on expert manual intervention, while pure data-driv...
Hongqing V. Wang, Ming-Wei Chen, Hong Luo et al.· 0 citations
Machine intelligence has conquered the symbolic world but stalled at the physical one. The stall is structural: physical AI faces a cold-start deadlock -- no intelligence without data, no data without deployed intelligence. Our thesis: the deadlock is real but unevenly distributed, and the exception has a name: the art...
Context quality is identified as a central bottleneck in on-policy self-distillation and the value of separating rollout-conditioned guidance from canonical supervision is demonstrated, demonstrating the value of separating rollout-conditioned guidance from canonical supervision.
Meilin Yang, Zixuan Ding, Jianhao Nie et al.· 0 citations
This paper presents a tutorial-style, collective-centric taxonomy for collective communication, which organizes recent advances into three layers: communication planning, which generates topology-aware collective schedules; communication execution and adaptation, which maps these schedules onto GPU runtimes and hardwar...
Xue-Bin Song, Menghao Zhang, Yue Liu et al.· IEEE Network· 0 citations
The Physics-Informed Stochastic Configuration Machine is proposed, a novel backpropagation-free framework for both forward and inverse problems in differential equations that achieves high-fidelity predictive accuracy and robust parameter identification while accelerating the training process by orders of magnitude com...
Yueze Song, Zhong-Zhe Chen, Li-Hui Cen et al.· 0 citations
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