arXiv subjects

Shuai Liu

Publications and source records attributed to Shuai Liu.

At least 37 records · Page 2Linked to original sources

arXiv2026

Locality-Aware Density Control for Efficient Gaussian-based Image Representation

2D Gaussian Splatting is an attractive direction for image representation due to its explicit formulation, fast rasterization, and favorable decoding efficiency. The representation quality of this paradigm depends on the proper allocation of Gaussian capacity to the demanding regions. However, existing methods fail to allocate Gaussian capacity efficiently during optimization: under-reconstructed content is often refined in a fragmented pixel-wise manner, while neighboring optimized Gaussians with similar attributes are redundantly retained. This inefficiency motivates the need for a density control framework that jointly addresses insufficient allocation in under-reconstructed regions and redundant allocation in over-reconstructed regions. Our key insight is that this framework should exploit two complementary forms of locality: the local continuity of reconstruction errors in image space for improved Gaussian allocation, and the local similarity of neighboring Gaussians in Gaussian space for redundant elimination. Based on this insight, we propose Locality-Aware Density Control (LocoADC), a plug-and-play framework that improves Gaussian capacity utilization through Region-wise Gaussian Densification (RGD) and Similarity-Driven Gaussian Merging (SDGM) strategies, together with a local color consistency constraint for more reliable merging. Extensive experiments on diverse datasets show that LocoADC consistently improves multiple baselines by enabling more effective local Gaussian allocation, including a 2.93 dB PSNR gain over GI on the CLIC dataset under the same 30k Gaussian budget. Code is available at: \textit{https://github.com/ChenJiaCong-1005/LocoADC}.

cs.CV↗

arXiv2026

Gravitational Wave Astronomy With TianQin

The opening of the gravitational wave window has significantly enhanced our capacity to explore the universe's most extreme and dynamic sector. In the mHz frequency range, a diverse range of compact objects, from the most massive black holes at the farthest reaches of the Universe to the lightest white dwarfs in our cosmic backyard, generate a complex and dynamic symphony of gravitational wave signals. Once recorded by gravitational wave detectors, these unique fingerprints have the potential to decipher the birth and growth of cosmic structures over a wide range of scales, from stellar binaries and stellar clusters to galaxies and large-scale structures. The TianQin space-borne gravitational wave mission is scheduled for launch in the 2030s, with an operational lifespan of five years. It will facilitate pivotal insights into the history of our universe. This document presents a concise overview of the detectable sources of TianQin, outlining their characteristics, the challenges they present, and the expected impact of the TianQin observatory on our understanding of them.

astro-ph.GA↗

arXiv2026

Optical Detuning Strategies for Shielded Loop Resonators

Purpose: To compare detuning performance and evaluate the power requirements of optical detuning methods, and to demonstrate the feasibility of an optically detuned four-channel receive array. Methods: Four optical detuning methods were compared in simulations, bench tests, and phantom measurements at 3T against conventional galvanic detuning. Passive detuning was also tested as an additional wireless detuning option. Optical power requirements for the detuning networks were investigated, and a flexible, optically detuned 4-channel shielded-loop resonator (SLR) array was constructed and tested in vivo. Results: A photodiode-PIN diode combination exhibited the highest unloaded Q (68.6) and Q ratio (1.9), with detuning performance and signal-to-noise ratio comparable to that of galvanic detuning at an optical power of 10 mW. Using this detuning strategy, in vivo images of the knee and brain were successfully acquired with a 4-channel flexible array. Conclusion: Optical detuning is a practical alternative to conventional galvanic detuning in flexible SLR arrays. With advances in optical signal and power transmission, optimizing optical detuning while meeting manageable power requirements is an important step toward fully optical receive-coil arrays. This study provides a baseline for the total optical power required for active detuning in such optical coil systems.

eess.SY↗

arXiv2026

Spin-Squeezing-Enhanced Charging for Quantum Dicke Batteries

High-power Dicke quantum batteries (QBs) typically exploit collective superradiance, whereas intrinsic matter-matter interactions are conventionally considered detrimental. Here, we propose a counterintuitive paradigm: these interactions can be controlled and repurposed as a synergistic resource to enhance charging power and capacity. In the low-excitation limit, transverse interactions induce collective spin squeezing, causing critical mode softening and an exponential enhancement of effective coupling, which significantly boosts charging power. At higher excitations, these interactions act as a macroscopic nonlinear torque. By appropriately aligning this torque, we effectively lower phase-space dynamical barriers, guiding the system along optimal rapid-charging paths. Importantly, this cooperative enhancement remains highly robust under realistic dissipation, outperforming ideal, dissipationless Dicke QBs in specific regimes. Our results provide a blueprint for exploiting matter interactions to design dissipation-resistant, high-performance many-body QBs.

quant-ph↗

arXiv2026

Randomized Exploration for Linear Bandits via Absolute Perturbations

In stochastic linear bandits, the canonical Upper Confidence Bound (UCB) algorithm admits a simple frequentist regret analysis but can be computationally demanding, while Thompson Sampling (TS) is computationally attractive yet typically harder to analyze due to its non-optimistic nature. We propose Absolute Thompson Sampling (ATS), a simple modification of TS that ensures optimism in expectation by replacing the signed exploration noise with its absolute value. This preserves the computational efficiency of TS while avoiding the technically involved anti-concentration arguments common in TS analyses, enabling a simple UCB-style regret analysis. We show that ATS achieves $\tilde{O}(d^{3/2}\sqrt{K})$ regret, matching existing bounds for TS in linear bandits. We further introduce Ensemble Absolute Thompson Sampling (EATS), which takes the maximum over multiple absolute perturbations with normalization by the ensemble size. As the ensemble size grows, EATS converges to the UCB objective, recovering UCB behavior in the limit. Experiments show that moderate ensemble sizes already yield strong performance. Our results point to a bridge between randomized exploration and deterministic optimism both in theory and practice.

cs.LG↗

arXiv2026

A Watermark for Vision-Language-Action and World Action Models

Vision-language-action (VLA) models and world-action models (WAM) are the generative models now driving general-purpose robot control, turning raw camera input directly into motor commands. They are increasingly deployed as black-box services, where a partner runs the policy through an interface while the owner keeps the weights private. Training such a model takes proprietary data and heavy computational power, making the deployed model itself a valuable intellectual property. To address this, we propose the \emph{keyed latent-provenance verification} method, which fingerprints the policy through the seed of the Gaussian noise vector that the models draw before generation. At the injection stage, the owner swaps this seed for a keyed one with the same distribution as ordinary noise, so the fingerprinted actions are statistically identical to those of an ordinary run and an adversary watching the output finds no signal to detect or remove. At the verification stage, the owner runs the suspect model under authorized access and records the action channels the robot executes, a partial and possibly post-processed view of the policy's output. From this view, the verifier recovers the seed by gradient-based maximum a posteriori (MAP) optimization, tests it for the secret key to score each rollout, and aggregates these scores into a single decision on whether the suspect model belongs to the owner. We evaluate the method on two representative models across two robot suites. The experiments cover detection of the fingerprint, identification of which of several keys a suspect carries, robustness to a range of attacks, and an analysis of why the design works. Across both models, the fingerprint can be detected reliably with little change to task performance, and it remains detectable under output-side removal attacks and weight-level edits.

cs.CR↗

arXiv2026

How to be Non-Human : A Thematic Analysis of Animal Embodiment in VR Games

This study employs a reflexive thematic analysis to systematically examine the design patterns of 48 first-person Virtual reality (VR) animal avatar games. The research identifies four primary design themes: Animal Biomimicry, Limited Animal Simulation, Hybrid HumanAnimal Features, and Human Behavior with Animal Avatar. The analysis reveals that approximately 77 percent of the games remain grounded in human-centered interaction logic, with animal forms primarily serving as visual representations. The study highlights the core tension between authenticity and usability in current VR animal avatar design, and points toward design opportunities for achieving more authentic animal avatar's interactive experience through directions such as controller innovation, unconventional body mapping, and dynamic feedback. This research provides a thematic classification framework for understanding the representation of non-human perspectives in VR games.

cs.HC↗

arXiv2026

Exploration via linearly perturbed loss minimisation

We introduce exploration via linear loss perturbations (EVILL), a randomised exploration method for structured stochastic bandit problems that works by solving for the minimiser of a linearly perturbed regularised negative log-likelihood function. We show that, for the case of generalised linear bandits, EVILL reduces to perturbed history exploration (PHE), a method where exploration is done by training on randomly perturbed rewards. In doing so, we provide a simple and clean explanation of when and why random reward perturbations give rise to good bandit algorithms. We propose data-dependent perturbations not present in previous PHE-type methods that allow EVILL to match the performance of Thompson-sampling-style parameter-perturbation methods, both in theory and in practice. Moreover, we show an example outside generalised linear bandits where PHE leads to inconsistent estimates, and thus linear regret, while EVILL remains performant. Like PHE, EVILL can be implemented in just a few lines of code.

cs.LG↗

arXiv2026

A Systematic NLTE Study of Very Metal-Poor Stars with Metallicity Down to $-4.3$ dex. II. Lithium Abundance and New Insight to the Lithium Plateau

Metal-poor stars are crucially important for understanding the early Galaxy, first stars, and the Universe. In this series of papers, we present a homogeneous non-local thermodynamic equilibrium (NLTE) abundances analysis of 12 elements for 103 very/extremely metal-poor (VMP/EMP) stars with metallicity down to $-4.3$ dex. The sample was selected from the LAMOST survey and observed by the high-resolution spectroscopy of Subaru. In this paper, we present the NLTE abundances and evolution of lithium in these stars. We report different lithium behaviors corresponding to different evolutionary stages and their signatures: 1) The Spite Plateau shows a slightly positive slope, indicating increasing lithium abundance with increasing metallicity. Most significantly, it appears to extend to lower metallicities as previously suggested, calling into question the reality of the so-called 'meltdown' at low metallicity; 2) We confirm a lithium plateau for lower red giant branch (LRGB) stars with A(Li) $= 1.13$ dex in our sample, while lithium abundance drops rapidly to A(Li)$<0.5$ as stars continue to evolve to higher stage. 3) We identify four Li-rich stars in our sample across different evolutionary stages, showing complex and multiple lithium production mechanisms in VMP/EMP stars. These findings suggest that early Galactic lithium enrichment results from a complex interplay between depletion and production processes.

astro-ph.SR↗

arXiv2026

Learning What to Recommend: Minimax Optimal Simple Regret in Logistic Bandits

We study stochastic logistic bandits with $d$-dimensional action features under the simple-regret objective, where a learner uses $T$ rounds of exploration to output a single final action. The logistic structure is essential here: because the informativeness of an action depends on the local curvature of the sigmoid, actions that are best for immediate reward need not be the most useful for identifying the best final recommendation. We show that the first-order minimax difficulty is governed by $κ_*$, the inverse slope of the sigmoid at the optimal action. The lower bound is realized by a shifted saturated hard family in which saturation simultaneously limits the information available about the final decision and controls the value loss from a wrong recommendation. This reveals a hard mechanism distinct from cumulative-regret constructions, even though online-to-batch reductions recover the same leading order in expectation. We then develop two curvature-aware algorithms: \MULog, a pure-exploration method whose final recommendation satisfies a high-probability upper bound of order $\tilde O(d/\sqrt{κ_* T})$, matching the lower bound up to logarithmic factors, and \THATS, a Thompson-sampling-style method that provides a computationally lighter alternative. Experiments on both hard and easy geometries support the same picture: informative low-reward actions can make instances substantially easier, and the curvature-aware methods exploit this structure especially effectively.

cs.LG↗

arXiv2026

Heralded Generation of Multipartite Free-Electron W-State Entanglement

We propose a heralded protocol for generating multipartite free-electron entanglement from atomic $W_N$ resources in a sideband-resolved interaction regime. The scheme consists of $N$ independent electron--atom interaction arms, where each free electron couples locally to one two-level system. For uniform couplings and common detuning, the dynamics is solved analytically within the rotating-wave approximation. Projecting the atoms onto the all-ground state maps the initial atomic excitation manifold onto the electronic upper-sideband manifold and prepares an exact $N$-electron $W_N$-type state. The heralding probability is obtained in closed form for resonant and detuned regimes. At resonance, the optimal success probability obeys the large-$N$ scaling $P_{G_N}^{\max}\sim e^{-1}/N$. The heralded state retains the multipartite entanglement structure of the atomic resource, as shown for arbitrary $N$ and illustrated explicitly for $N=3$. Detuning, weak symmetry breaking, beyond-rotating-wave corrections, and Gaussian coupling envelopes are discussed. The protocol provides a scalable route toward multipartite free-electron entanglement generation from localized atomic resources within quantum electron optics.

quant-ph↗

arXiv2026

A Network Transformation Mapping Approach to Synchronization of Multi-Agent Systems With Disconnected Switching Topologies

This paper focuses on the multi-agent synchronization problem with an open-loop unstable leader and followers under the switching topologies. For this issue, the typical approach is intermittent communication (including a spanning tree intermittently) or fast switching strategy. We here consider a more general scenario where each communication link between two agents is randomly disconnected and reconnected, and the durations of both the disconnected intervals and the connected intervals follow negative exponential distributions. To handle this issue, we propose a network transformation mapping method that divides the communication network into reachable and unreachable parts at any time. A node can access the leader's information and synchronize only when it lies in the reachable part; otherwise, it cannot. For each node, the synchronization speed is designed such that its convergence amplitude in the reachable part exceeds its divergence amplitude in the unreachable part. Hence, all nodes achieve asymptotic synchronization over the entire time domain. We further develop adaptive strategies for coupling gains to reduce the computational complexity introduced by the network transformation mapping. The proposed method is also applicable to jointly connected switching topologies and distributed observers under topologies that lack a spanning tree at any time. Finally, two numerical simulations -- synchronous control of multi-one-link manipulator systems and multi-motor systems based on Fieldbus -- are provided to demonstrate the effectiveness of our approach.

math.DS↗

arXiv2026

Heralded Entanglement Transfer from Entangled Atomic Pair to Free Electrons

We propose a protocol that transfers entanglement from an entangled atomic two-level-system (TLS) resource to a pair of free electrons in an energy-sideband ladder via local electron-TLS interactions. In a controlled rotating-wave regime, closed-form reduced states are derived. TLS heralding then prepares a maximally entangled electron state in a two-dimensional single-excitation manifold, with a simple dependence on the initial TLS resource entanglement. Numerical integration of the full bilinear Hamiltonian quantifies the impacts of detuning and pulse shaping and identifies the leading beyond-rotating-wave corrections. The results establish a heralded route to entangled free electrons and will facilitate further advances in quantum electron optics.

quant-ph↗

arXiv2026

A PPA-Driven 3D-IC Partitioning Selection Framework with Surrogate Models

3D-IC netlist partitioning is commonly optimized using proxy objectives, while final PPA is treated as a costly evaluation rather than an optimization signal. This proxy-driven paradigm makes it difficult to reliably translate additional PPA evaluations into better PPA outcomes. To bridge this gap, we present DOPP (D-Optimal PPA-driven partitioning selection), an approach that bridges the gap between proxies and true PPA metrics. Across eight 3D-IC designs, our framework improves PPA over Open3DBench (average relative improvements of 9.99% congestion, 7.87% routed wirelength, 7.75% WNS, 21.85% TNS, and 1.18% power). Compared with exhaustive evaluation over the full candidate set, DOPP achieves comparable best-found PPA while evaluating only a small fraction of candidates, substantially reducing evaluation cost. By parallelizing evaluations, our method delivers these gains while maintaining wall-clock runtime comparable to traditional baselines.

cs.LG↗

arXiv2026

GW231123 Formation from Population III Stars: Isolated Binary Evolution

GW231123 is a merger of two black holes (BHs) with estimated masses exceeding $100\;{\rm M}_{\odot}$, making them the most massive BHs discovered to date via gravitational wave (GW) observations. We investigate whether GW231123-like events can originate from isolated Population (Pop) III binary stars using binary population synthesis calculations. Our findings indicate that isolated Pop III binaries can produce GW231123-like events at a rate sufficient to explain the discovery of GW231123, provided that three conditions are met: (i) Pop III stars evolve with inefficient convective overshooting, (ii) the $^{12}\text{C}(α, γ)^{16}\text{O}$ rate is $2σ$ lower than the standard value, and (iii) Pop III binary stars share the same orbital parameters as Pop I/II binary stars at the initial time. In contrast, GW190521 -- the most massive BH merger in the Gravitational Wave Transient Catalog 3 -- can be formed from isolated Pop III binaries even with the standard $^{12}\text{C}(α, γ)^{16}\text{O}$ rate. We demonstrate that the discovery of GW231123 is increasingly constraining the parameter ranges of single star evolution models, under the assumption that these GW events originate from isolated binary evolution.

astro-ph.SR↗

arXiv2026

LoViF 2026 The First Challenge on Weather Removal in Videos

This paper presents a review of the LoViF 2026 Challenge on Weather Removal in Videos. The challenge encourages the development of methods for restoring clean videos from inputs degraded by adverse weather conditions such as rain and snow, with an emphasis on achieving visually plausible and temporally consistent results while preserving scene structure and motion dynamics. To support this task, we introduce a new short-form WRV dataset tailored for video weather removal. It consists of 18 videos 1,216 synthesized frames paired with 1,216 real-world ground-truth frames at a resolution of 832 x 480, and is split into training, validation, and test sets with a ratio of 1:1:1. The goal of this challenge is to advance robust and realistic video restoration under real-world weather conditions, with evaluation protocols that jointly consider fidelity and perceptual quality. The challenge attracted 37 participants and received 5 valid final submissions with corresponding fact sheets, contributing to progress in weather removal for videos. The project is publicly available at https://www.codabench.org/competitions/13462/.

cs.CV↗

arXiv2026

STGV: Spatio-Temporal Hash Encoding for Gaussian-based Video Representation

2D Gaussian Splatting (2DGS) has recently become a promising paradigm for high-quality video representation. However, existing methods employ content-agnostic or spatio-temporal feature overlapping embeddings to predict canonical Gaussian primitive deformations, which entangles static and dynamic components in videos and prevents modeling their distinct properties effectively. These result in inaccurate predictions for spatio-temporal deformations and unsatisfactory representation quality. To address these problems, this paper proposes a Spatio-Temporal hash encoding framework for Gaussian-based Video representation (STGV). By decomposing video features into learnable 2D spatial and 3D temporal hash encodings, STGV effectively facilitates the learning of motion patterns for dynamic components while maintaining background details for static elements. In addition, we construct a more stable and consistent initial canonical Gaussian representation through a key frame canonical initialization strategy, preventing from feature overlapping and a structurally incoherent geometry representation. Experimental results demonstrate that our method attains better video representation quality (+0.98 PSNR) against other Gaussian-based methods and achieves competitive performance in downstream video tasks.

cs.CV↗

arXiv2026

Adversarial Video Promotion Against Text-to-Video Retrieval

Thanks to the development of cross-modal models, text-to-video retrieval (T2VR) is advancing rapidly, but its robustness remains largely unexamined. Existing attacks against T2VR are designed to push videos away from queries, i.e., suppressing the ranks of videos, while the attacks that pull videos towards selected queries, i.e., promoting the ranks of videos, remain largely unexplored. These attacks can be more impactful as attackers may gain more views/clicks for financial benefits and widespread (mis)information. To this end, we pioneer the first attack against T2VR to promote videos adversarially, dubbed the Video Promotion attack (ViPro). We further propose Modal Refinement (MoRe) to capture the finer-grained, intricate interaction between visual and textual modalities to enhance black-box transferability. Comprehensive experiments cover 2 existing baselines, 3 leading T2VR models, 3 prevailing datasets with over 10k videos, evaluated under 3 scenarios. All experiments are conducted in a multi-target setting to reflect realistic scenarios where attackers seek to promote the video regarding multiple queries simultaneously. We also evaluated our attacks for defences and imperceptibility. Overall, ViPro surpasses other baselines by over $30/10/4\%$ for white/grey/black-box settings on average. Our work highlights an overlooked vulnerability, provides a qualitative analysis on the upper/lower bound of our attacks, and offers insights into potential counterplays. Code will be publicly available at https://github.com/michaeltian108/ViPro.

cs.CV↗