The geometric structure of atomic nuclei plays an important role in shaping the initial conditions of high-energy nuclear collisions and the subsequent evolution of the quark--gluon plasma. In this work, we develop a multimodal deep-learning framework to infer the Woods--Saxon radius ($R_0$) and diffuseness parameter (...
Class-wise analyses, together with attention and masking analyses, show improved discrimination of ambiguous states and indicate that physical variables meaningfully constrain local response interpretation, and demonstrate a deployment-oriented approach to robust diagnosis in heterogeneous industrial environments.
Yu Sha, Jun-Qi Tao, Di-Xin Zhou et al.· 0 citations
Experiments show that POC-VLM consistently outperforms representative data-driven, multimodal and domain-specific diagnostic methods, while demonstrating robust performance under varying sampling rates, noise levels and observation durations.
Yu Sha, Jun-Qi Tao, De-Yu Wang et al.· 0 citations
Large language models (LLMs) increasingly mediate human decisions and communication, yet their behavioural regularities remain difficult to characterize systematically. We develop a cross-linguistic psychometric profiling framework and evaluate nine LLMs using seven psychological instruments, with five repeated adminis...
Yu Sha, Jun-Qi Tao, Di-Xin Zhou et al.· 1 citation
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