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Researcher profile

Zhong Wang

Zhong Wang contributes to research discovery and scholarly infrastructure.

ResearcherAffiliation not importedOpen to collaborate
cond-mat.mes-hallcond-mat.quant-gasphysics.opticsquant-phArtificial Intelligenceastro-ph.GAComputer Visioncond-mat.mtrl-scicond-mat.str-elCryptography and SecurityMultimediaSound

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Published work

7 published item(s)

preprint2026arXiv

Asking Back: Interaction-Layer Antidistillation Watermarks

Detecting unauthorized knowledge distillation from a deployed LLM API is hard because the defender controls neither the attacker's training pipeline nor the next-token logits. Existing defenses operate on the teacher's output tokens -- biasing the next-token distribution (green-list watermarks, cryptographic schemes, antidistillation sampling) or rewriting outputs after generation. Recent work shows a paraphrasing attacker can strip these signals without losing the underlying knowledge. We propose interaction-layer antidistillation watermarks, which move the trace one layer higher, into the teacher's interaction behavior: the defender wraps the teacher with a system prompt that intermittently induces a behavioral marker -- an explicit follow-up question, a low-frequency variant, or a declarative restatement. An oblivious distiller inherits the behavior, and the defender audits via black-box queries with a human-validated LLM-as-judge (Cohen's kappa = 0.84/0.78 on strong/style rubrics). Across 63 LoRA-distilled students under a Llama-3.3-70B-Instruct teacher (35,343 judged samples), behavioral watermarks transfer at 88.9% (Gemma) / 80.9% (OLMo) / 45.2% (Qwen) relative fidelity (H1, H2). Under non-adaptive DIPPER paraphrasing, robustness decomposes into a teacher-self ceiling (about 66.4%) and student-relative retention of 21-112%, with OLMo preserving the watermark above the teacher itself (H3, F-Amp). Low-density (about 20%) explicit and implicit declarative variants transfer above per-family baseline (H4, F-Style). An N=20 in-lab study (pre-registered Latin-square) shows all marker variants within 0.22 Likert step of baseline; TOST, Friedman, and Bonferroni-Wilcoxon support H5. The interaction layer is a viable design locus for antidistillation watermarking, complementary to token-, model-, and reasoning-trace-layer defenses.

0 citations0 reviewsNo code linkedOpen access
preprint2026arXiv

Representing Sounds as Neural Amplitude Fields: A Benchmark of Coordinate-MLPs and A Fourier Kolmogorov-Arnold Framework

Although Coordinate-MLP-based implicit neural representations have excelled in representing radiance fields, 3D shapes, and images, their application to audio signals remains underexplored. To fill this gap, we investigate existing implicit neural representations, from which we extract 3 types of positional encoding and 16 commonly used activation functions. Through combinatorial design, we establish the first benchmark for Coordinate-MLPs in audio signal representations. Our benchmark reveals that Coordinate-MLPs require complex hyperparameter tuning and frequency-dependent initialization, limiting their robustness. To address these issues, we propose Fourier-ASR, a novel framework based on the Fourier series theorem and the Kolmogorov-Arnold representation theorem. Fourier-ASR introduces Fourier Kolmogorov-Arnold Networks (Fourier-KAN), which leverage periodicity and strong nonlinearity to represent audio signals, eliminating the need for additional positional encoding. Furthermore, a Frequency-adaptive Learning Strategy (FaLS) is proposed to enhance the convergence of Fourier-KAN by capturing high-frequency components and preventing overfitting of low-frequency signals. Extensive experiments conducted on natural speech and music datasets reveal that: (1) well-designed positional encoding and activation functions in Coordinate-MLPs can effectively improve audio representation quality; and (2) Fourier-ASR can robustly represent complex audio signals without extensive hyperparameter tuning. Looking ahead, the continuity and infinite resolution of implicit audio representations make our research highly promising for tasks such as audio compression, synthesis, and generation. The source code will be released publicly to ensure reproducibility. The code is available at https://github.com/lif314/Fourier-ASR.

0 citations0 reviewsNo code linkedOpen access
preprint2025arXiv

SmartSplat: Feature-Smart Gaussians for Scalable Compression of Ultra-High-Resolution Images

Recent advances in generative AI have accelerated the production of ultra-high-resolution visual content, posing significant challenges for efficient compression and real-time decoding on end-user devices. Inspired by 3D Gaussian Splatting, recent 2D Gaussian image models improve representation efficiency, yet existing methods struggle to balance compression ratio and reconstruction fidelity in ultra-high-resolution scenarios. To address this issue, we propose SmartSplat, a highly adaptive and feature-aware GS-based image compression framework that supports arbitrary image resolutions and compression ratios. SmartSplat leverages image-aware features such as gradients and color variances, introducing a Gradient-Color Guided Variational Sampling strategy together with an Exclusion-based Uniform Sampling scheme to improve the non-overlapping coverage of Gaussian primitives in pixel space. In addition, we propose a Scale-Adaptive Gaussian Color Sampling method to enhance color initialization across scales. Through joint optimization of spatial layout, scale, and color initialization, SmartSplat efficiently captures both local structures and global textures using a limited number of Gaussians, achieving high reconstruction quality under strong compression. Extensive experiments on DIV8K and a newly constructed 16K dataset demonstrate that SmartSplat consistently outperforms state-of-the-art methods at comparable compression ratios and exceeds their compression limits, showing strong scalability and practical applicability. The code is publicly available at https://github.com/lif314/SmartSplat.

0 citations0 reviewsNo code linkedOpen access
preprint2023arXiv

Scalable synthesis and characterization of multilayer $γ$-graphyne, new carbon crystals with a small direct bandgap

$γ$-Graphyne is the most symmetric sp2/sp1 allotrope of carbon, which can be viewed as graphene uniformly expanded through insertion of two-carbon acetylenic units between all the aromatic rings. To date, synthesis of bulk $γ$-graphyne has remained a challenge. We here report the synthesis of multilayer $γ$-graphyne through crystallization-assisted irreversible cross-coupling polymerization. Comprehensive characterization of this new carbon phase is described, including synchrotron X-ray diffraction, electron diffraction, lateral force microscopy, Raman and infrared spectroscopy, and cyclic voltammetry. Experiments indicate that $γ$-graphyne is a 0.48 eV bandgap semiconductor, with a hexagonal a-axis spacing of 6.88 Å and an interlayer spacing of 3.48 Å, which is consistent with theoretical predictions. The observed crystal structure has an aperiodic sheet stacking. The material is thermally stable up to 240 $^\circ$C but undergoes a transformation at higher temperatures. While conventional 2D polymerizations and reticular chemistry rely on error correction through reversibility, we demonstrate that a periodic covalent lattice can be synthesized under purely kinetic control. The reported methodology is scalable and inspires extension to other allotropes of the graphyne family.

0 citations0 reviewsNo code linkedOpen access
preprint2022arXiv

Non-Hermitian Edge Burst

We unveil an unexpected non-Hermitian phenomenon, dubbed edge burst, in non-Hermitian quantum dynamics. Specifically, in a class of non-Hermitian quantum walk in periodic lattices with open boundary condition, an exceptionally large portion of loss occurs at the system boundary. The physical origin of this edge burst is found to be an interplay between two unique non-Hermitian phenomena: non-Hermitian skin effect and imaginary gap closing. Furthermore, we establish a universal bulk-edge scaling relation underlying the non-Hermitian edge burst. Our predictions are experimentally accessible in various non-Hermitian systems including quantum-optical and cold-atom platforms.

0 citations0 reviewsNo code linkedOpen access
preprint2020arXiv

ALMA Imaging of the CO(7-6) Line Emission in the Submillimeter Galaxy LESS 073 at redshift 4.755$^\star$

In this paper we present our imaging observations on the CO(7-6) line and its underlying continuum emission of the young submillimeter galaxy LESS 073 at redshift 4.755, using the Atacama Large Millimeter/submillimeter Array (ALMA). At the achieved resolution of $\sim$$1^{\prime\prime}.2\times0^{\prime\prime}.9$ ($8\times6$~kpc$^2$), the CO(7-6) emission is largely unresolved (with a deconvolved size of $1^{\prime\prime}.1(\pm0^{\prime\prime}.5) \times 0^{\prime\prime}.9(\pm0^{\prime\prime}.8)$), and the continuum emission is totally unresolved. The CO(7-6) line emission has an integrated flux of $0.86\pm0.08$~Jy km/s, and a line width of $343\pm40$ km/s. The continuum emission has a flux density of 0.51 mJy. By fitting the observed far-infrared (FIR) spectral energy distribution of LESS 073 with a single-temperature modified blackbody function, we obtained a dust temperature $T_{\rm dust}=57.6\pm3.5$ K, 60-to-100 $μ$m flux density ratio $f_{60}/f_{100}=0.86\pm0.08$, and total infrared luminosity $L_{\rm IR}=(5.8\pm0.9) \times 10^{12}~L_\odot$. The SED-fit-based $f_{60}/f_{100}$ is consistent with those estimated from various line ratios as advocated by our earlier work, indicating that those proposed line-ratio-based method can be used to practically derive $f_{60}/f_{100}$ for high-$z$ sources. The total molecular gas mass of LESS 073 is $(3.3\pm1.7) \times10^{10}~M_\odot$, and the inferred gas depletion time is about 43 Myr.

0 citations0 reviewsNo code linkedOpen access
preprint2019arXiv

Observation of non-Hermitian bulk-boundary correspondence in quantum dynamics

Bulk-boundary correspondence, a central principle in topological matter relating bulk topological invariants to edge states, breaks down in a generic class of non-Hermitian systems that have so far eluded experimental effort. Here we theoretically predict and experimentally observe non-Hermitian bulk-boundary correspondence, a fundamental generalization of the conventional bulk-boundary correspondence, in discrete-time non-unitary quantum-walk dynamics of single photons. We experimentally demonstrate photon localizations near boundaries even in the absence of topological edge states, thus confirming the non-Hermitian skin effect. Facilitated by our experimental scheme of edge-state reconstruction, we directly measure topological edge states, which match excellently with non-Bloch topological invariants calculated from localized bulk-state wave functions. Our work unequivocally establishes the non-Hermitian bulk-boundary correspondence as a general principle underlying non-Hermitian topological systems, and paves the way for a complete understanding of topological matter in open systems.

0 citations0 reviewsNo code linkedOpen access