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Researcher profile

Huimin Wang

Huimin Wang contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
Artificial IntelligenceComputer Visioncond-mat.mtrl-sciMachine LearningMultiagent Systemsphysics.chem-ph

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Published work

3 published item(s)

preprint2026arXiv

AllocMV: Optimal Resource Allocation for Music Video Generation via Structured Persistent State

Generating long-horizon music videos (MVs) is frequently constrained by prohibitive computational costs and difficulty maintaining cross-shot consistency. We propose AllocMV, a hierarchical framework formulating music video synthesis as a Multiple-Choice Knapsack Problem (MCKP). AllocMV represents the video's persistent state as a compact, structured object comprising character entities, scene priors, and sharing graphs, produced by a global planner prior to realization. By estimating segment saliency from multimodal cues, a group-level MCKP solver based on dynamic programming optimally allocates resources across High-Gen, Mid-Gen, and Reuse branches. For repetitive musical motifs, we implement a divergence-based forking strategy that reuses visual prefixes to reduce costs while ensuring motif-level continuity. Evaluated via the Cost-Quality Ratio (CQR), AllocMV achieves an optimal trade-off between perceived quality and resource expenditure under strict budgetary and rhythmic constraints.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

The consistent behavior of negative Poissons ratio with interlayer interactions

Negative Poissons ratio (NPR) is of great interest due to the novel applications in lots of fields. Films are the most commonly used form in practical applications, which involves multiple layers. However, the effect of interlayer interactions on the NPR is still unclear. In this study, based on first principles calculations, we systematically investigate the effect of interlayer interactions on the NPR by comparably studying single-layer graphene, few-layer graphene, h-BN, and graphene-BN heterostructure. It is found that they almost have the same geometry-strain response. Consequently, the NPR in bilayer graphene, triple-layer graphene, and graphene-BN heterostructure are consistent with that in single-layer graphene and h-BN. The fundamental mechanism lies in that the response to strain of the orbital coupling are consistent under the effect of interlayer interactions. The deep understanding of the NPR with the effect of interlayer interactions as achieved in this study is beneficial for the future design and development of micro-/nanoscale electromechanical devices with novel functions based on nanostructures.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

The record low thermal conductivity of monolayer Cuprous Iodide (CuI) with direct wide bandgap

Two-dimensional materials have attracted lots of research interests due to the fantastic properties that are unique to the bulk counterparts. In this paper, from the state-of-the-art first-principles, we predicted the stable structure of monolayer counterpart of the γ-CuI (Cuprous Iodide), which is a p-type wide bandgap semiconductor. The monolayer CuI presents multifunctional superiority in terms of electronic, optical, and thermal transport properties. Specifically, the ultralow thermal conductivity of 0.116 Wm-1K-1 is predicted for monolayer CuI, which is much lower than γ-CuI (0.997 Wm-1K-1) and other typical semiconductors. Moreover, an ultrawide direct bandgap of 3.57 eV is found in monolayer CuI, which is larger than γ-CuI (2.95-3.1 eV), promoting the applications in nano-/optoelectronics with better optical performance. The ultralow thermal conductivity and direct wide bandgap of monolayer CuI as reported in this study would promise its potential applications in transparent and wearable electronics.

0 citations0 reviewsNo code linkedOpen access