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Ben Li

Publications and source records attributed to Ben Li.

At least 19 recordsLinked to original sources
arXiv2026

Magnetic-configuration design for reliable Heisenberg exchange parameters

The determination of magnetic exchange interactions is essential for the quantitative description and predictive modeling of magnetic materials. In this work, we present a neighbor-shell-based screening method for selecting magnetic configurations suitable for extracting Heisenberg exchange parameters beyond nearest-neighbor from density functional theory (DFT) calculations. Using only the structure, the proposed approach identifies the linear independence of neighbor-shell contributions before any first-principles calculations instead of relying on trial-and-error generation of magnetic configurations. We apply the proposed approach to two representative classes of magnetic configurations: random spin states and spin spirals, and validate its predictions against direct DFT fitting for Fe and MnF$_2$. We show that only parameters obtained when all relevant neighbor-shell contributions are linearly independent remain transferable to other magnetic configurations. The proposed method provides practical guidance for selecting magnetic configurations for reliable exchange-parameter extraction and may also benefit other neighbor-shell-based models.

cond-mat.mtrl-sci↗
arXiv2026

C2Dex: Contact-Consistent Reconstruction and Retargeting for Dexterous Manipulation from Monocular Video

High-quality demonstrations for dexterous robot manipulation are costly and difficult to collect, whereas monocular human videos provide a scalable source of diverse manipulation behaviors. However, transferring such demonstrations to dexterous robots remains challenging: monocular hand-object interaction (HOI) reconstruction often produces temporally unstable contacts and physically implausible interactions, while conventional retargeting methods struggle to preserve task-relevant contacts and local interaction geometry across different hand embodiments. We present C2Dex, a video-to-dexterous-manipulation framework built around a shared interaction representation: stable object-side contacts recovered by aggregating noisy frame-wise observations in the canonical object space. These stable contacts serve a dual role: as trajectory-level constraints that guide reconstruction toward temporally coherent and physically plausible human HOI trajectories, and as explicit transfer targets for the dexterous hand, where Laplacian interaction optimization preserves the local hand-object geometry across embodiments and residual reinforcement learning refines the trajectory in simulation. Experiments on DexYCB and TACO show that C2Dex achieves end-to-end trajectory success rates of 57.78% and 26.67%, respectively, substantially outperforming the strongest baselines (17.78% and 10.00%) under identical evaluation criteria. Real-robot replay experiments further demonstrate physical feasibility across diverse contact-rich manipulation tasks. Project page: https://k-jie.github.io/C2Dex/

cs.RO↗
arXiv2026

CL-Anomaly: Layer-Adaptive Mixture-of-Experts with Multimodal Large Language Model for Continual Learning in Anomaly Detection

Multimodal Large Language Models (MLLMs) excel in diverse vision tasks, but full-parameter retraining is computationally expensive as real-world knowledge evolves. Existing continual learning methods often suffer from semantic entanglement in parameter spaces across tasks, impeding the continuous deployment of models. This challenge is especially pronounced in Anomaly Detection (AD), which exhibits triple heterogeneity across modalities, domains, and defect scale variability, significantly complicating multi-task knowledge transfer. In this paper, we propose CL-Anomaly, a parameter-efficient fine-tuning framework based on an isolation-sharing collaboration to enable continual learning for anomaly detection with MLLMs. We introduce the task-private expert PrivLoRA, which physically isolates task-specific subspaces in the parameter space to prevent semantic entanglement of anomaly knowledge in diverse scenarios. The Layer-Adaptive Shared Experts maintain cross-task representations within a unified feature space, enabling knowledge sharing between previous and new tasks. Furthermore, we propose a Layer-Adaptive Knowledge Transfer strategy that automatically selects and dynamically updates the layer-wise key shared experts of each task via a momentum-based mechanism, promoting effective knowledge transfer across related anomaly detection tasks. Extensive experiments across three continual learning scenarios for anomaly detection, including class-incremental, cross-domain, and cross-modal, demonstrate that CL-Anomaly outperforms state-of-the-art methods. Code is available at https://github.com/WenDongyp/CL-Anomaly.

cs.CV↗
arXiv2026

Suppressed diffusion and gamma-ray emission from the Cygnus bubble

Recent gamma-ray observations indicate that star clusters can be efficient particle accelerators. In particular, LHAASO has detected diffuse gamma-ray emission from Cygnus OB2 extending to $\gtrsim$ PeV energies, indicating that particles are accelerated to at least $\gtrsim$1 PeV. In this work, we study the gamma-ray emission from the Cygnus region assuming particle acceleration either at the termination shock of the cluster wind (WTS) or in an unspecified source at the bubble center, taken to be either steady or bursting. We numerically solve the transport equation for non-thermal particles in all scenarios and derive their spatial and spectral distributions throughout the bubble. We then calculate the gamma-ray emission from pp interactions, including the contribution from particles interacting with the surrounding molecular cloud, which may help explain the extended emission observed by LHAASO. We also include the penetration of Galactic cosmic rays (GCRs) and the resulting shock reacceleration. The predicted emission is compared with Fermi-LAT, HAWC and LHAASO observations. For three diffusion models, we find that a spatially dependent Bohm diffusion coefficient is required to reproduce both the spectrum and morphology in the cluster wind scenario. Penetrating GCRs can contribute significantly to the gamma-ray emission above $\sim$300 TeV. A suppressed diffusion coefficient with respect to the Galactic average in a region extending to at least 150 pc from the cluster center is needed to reproduce the LHAASO morphology. Our conclusion is that explaining both the spectrum and morphology of the $\sim$PeV emission with hadrons accelerated in a non-relativistic steady source requires extreme assumptions. We also speculate on the possibility that some of the highest-energy gamma rays may originate from sources behind the Cygnus association.

astro-ph.HE↗
arXiv2026

CelloCut: Constructive Watertight Remeshing via Tetrahedral Cell Cuts

Watertight remeshing aims to recover a surface that induces a globally consistent interior--exterior partition of 3D space. However, for meshes with complex topology, single-layer structures, or large missing regions, inferring such a partition from local surface geometry is inherently ambiguous. As a result, existing methods often produce surface-accurate yet volumetrically inconsistent reconstructions, e.g., closely spaced double shells. The key insight of this work is that watertight remeshing should be treated as a volumetric partitioning problem rather than a surface-level repair task. To this end, we propose CelloCut, a constructive framework that formulates watertight conversion as a binary labeling problem over a Delaunay tetrahedral partition of space. We solve this via graph-cut energy minimization with one-sided constraints that preserve proxy-supported interior evidence and weighted interface penalties that discourage unsupported newly introduced boundaries. By computing a globally consistent volumetric partition, CelloCut guarantees a strictly watertight output by construction and strongly suppresses pseudo-watertight artifacts such as double shells, even under severe topological defects. Experimental results on two newly introduced challenging benchmarks, CelloScan and CelloFill, as well as standard ModelNet10 dataset, demonstrate that CelloCut significantly outperforms state-of-the-art methods, particularly in handling complex topologies and single-layer structures, producing compact and volumetrically consistent solid reconstructions. The project page is available at https://rangeryx-66.github.io/CelloCut/.

cs.GR↗
arXiv2025

LiteVGGT: Boosting Vanilla VGGT via Geometry-aware Cached Token Merging

3D vision foundation models like Visual Geometry Grounded Transformer (VGGT) have advanced greatly in geometric perception. However, it is time-consuming and memory-intensive for long sequences, limiting application to large-scale scenes beyond hundreds of images. To address this, we propose LiteVGGT, achieving up to 10x speedup and substantial memory reduction, enabling efficient processing of 1000-image scenes. We derive two key insights for 3D reconstruction: (1) tokens from local image regions have inherent geometric correlations, leading to high similarity and computational redundancy; (2) token similarity across adjacent network layers remains stable, allowing for reusable merge decisions. Guided by these, we design a simple yet efficient strategy, dubbed geometry-aware cached token merging. We analyze each token's geometric importance, optimizing anchor token selection to better preserve key information for reconstruction. We also cache and reuse merge indices across layers, substantially reducing latency with minimal accuracy impact. This strategy retains VGGT's core performance, enabling efficient fine-tuning and FP8 quantization for further gains. Extensive experiments validate LiteVGGT's effectiveness, scalability, and robustness. Project page: https://garlicba.github.io/LiteVGGT/

cs.CV↗
arXiv2025

Synergy of Rashba and Topological Effects for High-Performance Bismuth-Based Thermoelectrics

Band convergence is a key strategy for enhancing thermoelectric (TE) performance. Herein, we demonstrate a promising approach to enhance band convergence through inducing Rashba splitting in topological insulators. Theoretically designed Janus $\beta$-Bi$_2$Se$_2$Te and $\beta$-Bi$_2$Te$_2$Se exhibited inherent topological band inversion and Rashba splitting due to the strong spin-orbit coupling (SOC) with broken inversion symmetry. These characteristics synergistically improve band convergence, leading to a substantially enhanced power factor. Meanwhile, the Janus structural asymmetry suppresses lattice thermal conductivity. Consequently, Janus structures achieve boosted TE performance, especially for $\beta$-Bi$_2$Se$_2$Te, peaking figure of merit ($zT$) of 2.82. This work establishes a new framework for designing Janus topological compounds with high TE performance by the synergistic effect of Rashba splitting and band inversion.

cond-mat.mtrl-sci↗
arXiv2025

VITON-DRR: Details Retention Virtual Try-on via Non-rigid Registration

Image-based virtual try-on aims to fit a target garment to a specific person image and has attracted extensive research attention because of its huge application potential in the e-commerce and fashion industries. To generate high-quality try-on results, accurately warping the clothing item to fit the human body plays a significant role, as slight misalignment may lead to unrealistic artifacts in the fitting image. Most existing methods warp the clothing by feature matching and thin-plate spline (TPS). However, it often fails to preserve clothing details due to self-occlusion, severe misalignment between poses, etc. To address these challenges, this paper proposes a detail retention virtual try-on method via accurate non-rigid registration (VITON-DRR) for diverse human poses. Specifically, we reconstruct a human semantic segmentation using a dual-pyramid-structured feature extractor. Then, a novel Deformation Module is designed for extracting the cloth key points and warping them through an accurate non-rigid registration algorithm. Finally, the Image Synthesis Module is designed to synthesize the deformed garment image and generate the human pose information adaptively. {Compared with} traditional methods, the proposed VITON-DRR can make the deformation of fitting images more accurate and retain more garment details. The experimental results demonstrate that the proposed method performs better than state-of-the-art methods.

cs.CV↗
arXiv2025

The Amazon Nova Family of Models: Technical Report and Model Card

We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highly-capable multimodal model with the best combination of accuracy, speed, and cost for a wide range of tasks. Amazon Nova Lite is a low-cost multimodal model that is lightning fast for processing images, video, documents and text. Amazon Nova Micro is a text-only model that delivers our lowest-latency responses at very low cost. Amazon Nova Canvas is an image generation model that creates professional grade images with rich customization controls. Amazon Nova Reel is a video generation model offering high-quality outputs, customization, and motion control. Our models were built responsibly and with a commitment to customer trust, security, and reliability. We report benchmarking results for core capabilities, agentic performance, long context, functional adaptation, runtime performance, and human evaluation.

cs.AI↗
arXiv2025

Potential Contribution of Young Pulsar Wind Nebulae to Galactic High-Energy Neutrino Emission

Pulsar wind nebulae (PWNe), especially the young ones, are among the most energetic astrophysical sources in the Galaxy. It is usually believed that the spin-down energy injected from the pulsars is converted into magnetic field and relativistic electrons, but the possible presence of proton acceleration inside PWNe cannot be ruled out. Previous works have estimated the neutrino emission from PWNe using various source catalogs measured in gamma-rays. However, such results rely on the sensitivity of TeV gamma-ray observations and may omit the contribution by unresolved sources. Here we estimate the potential neutrino emission from a synthetic population of PWNe in the Galaxy with a focus on the ones that are still in the free expansion phase. In the calculation, we model the temporal evolution of the free-expanding PWNe and consider the transport of protons inside the PWNe. The Crab nebula is treated as a standard template for young PWNe to evaluate some model parameters, such as the energy conversion fraction of relativistic protons and the target gas density for the hadronic process, which are relevant to neutrino production. In the optimistic case, the neutrino flux from the simulated young PWNe may constitute to 5% of the measured flux by IceCube around 100 TeV. At higher energy around 1 PeV, the neutrino emission from the population highly depends on the injection spectral shape, and also on the emission of the nearby prominent sources.

astro-ph.HE↗
arXiv2023

Beliaev damping in Bose gas

According to the Bogoliubov theory the low energy behaviour of the Bose gas at zero temperature can be described by non-interacting bosonic quasiparticles called phonons. In this work the damping rate of phonons at low momenta, the so-called Beliaev damping, is explained and computed with simple arguments involving the Fermi Golden Rule and Bogoliubov's quasiparticles.

math-ph↗
arXiv2023

Non-Hermitian Optical Parametric Systems with Anti-parity-time Symmetry

The continuous advancements in ultrafast lasers, characterized by high pulse energy, great average power, and ultrashort pulse duration, have opened up new frontiers and applications in various fields such as high-energy-density science. In this study, we investigated the implementation of non-Hermitian nonlinear parametric amplification by introducing anti-parity-time (anti-PT) symmetry to three-wave interaction processes. By exploring the parameter space defined by the coupling coefficient, phase mismatch, and absorption, we categorized the behavior of the non-Hermitian optical parametric system into four distinct quadrants, representing unbroken/broken anti-PT symmetry and amplification/attenuation, and amplification-attenuation boundaries and exceptional lines can be observed in such parametric space. Through simulations of the dynamical behavior of the interacting waves, we demonstrated the rich evolutions of the signal and idler waves in systems belonging to the respective quadrants and near exceptional points, revealed by the unique performance of eigenmodes. Our findings provide insights into the evaluation of energy flow direction in optical parametric amplification engineering by the directly linked parameter space, which contribute to a deeper understanding of photonics and laser science, potentially leading to new applications in these fields.

physics.optics↗
arXiv2021

Prospect of Detecting X-Ray Halos Around Middle-Aged Pulsars with eROSITA

The detection of extended TeV $\gamma$-ray emission (dubbed "TeV halos") from Geminga and Monogem pulsars by HAWC collaboration implies that the halo-like morphologies around middle-aged pulsars may be common. The $\gamma$-rays above 10 TeV are thought to arise from inverse Compton (IC) scattering of relativistic electrons/positrons in the pulsar halos off cosmic microwave background photons. In the meanwhile, these electrons and positrons can produce X-ray synchrotron emission in the interstellar magnetic field, resulting in a diffuse emission in the X-ray band (namely X-ray halos). Here, we study the prospect of detecting X-ray halos with eROSITA from 10 middle-aged pulsars with characteristic age larger than tens of thousands of years in the ATNF pulsar catalog. Assuming a benchmark value (i.e., $B = 3 \rm \, \mu G$) for the magnetic field, most of the X-ray halos are found to be bright enough to be detectable by eROSITA in the energy range of 0.5-2 keV during its four-year all-sky survey. Among these pulsar halos, three are supposed to produce X-ray fluxes above the eROSITA sensitivity of the first all-sky survey. Given the good angular resolution and the large field of view, eROSITA is expected to be able to measure the spatial distribution of the X-ray halos from sub-pc scale up to tens of pc scale. The intensity profiles of the X-ray halos are very useful to constrain the magnetic field and the energy-dependence of the diffusion coefficient in the pulsar halos.

astro-ph.HE↗
arXiv2020

Metrics and Isometries for Convex Functions

We introduce a class of functional analogs of the symmetric difference metric on the space of coercive convex functions on $\mathbb{R}^n$ with full-dimensional domain. We show that convergence with respect to these metrics is equivalent to epi-convergence. Furthermore, we give a full classification of all isometries with respect to some of the new metrics. Moreover, we introduce two new functional analogs of the Hausdorff metric on the spaces of coercive convex functions and super-coercive convex functions, respectively, and prove equivalence to epi-convergence.

math.FA↗
arXiv2020

Affine invariant maps for log-concave functions

Affine invariant points and maps for sets were introduced by Gr\"unbaum to study the symmetry structure of convex sets. We extend these notions to a functional setting. The role of symmetry of the set is now taken by evenness of the function. We show that among the examples for affine invariant points are the classical center of gravity of a log-concave function and its Santal\'o point. We also show that the recently introduced floating functions and the John- and L\"owner functions are examples of affine invariant maps. Their centers provide new examples of affine invariant points for log-concave functions.

math.FA↗
arXiv2020

The Maximum Surface Area Polyhedron with Five Vertices Inscribed in the Sphere $\mathbb{S}^2$

This article focuses on the problem of analytically determining the optimal placement of five points on the unit sphere $\mathbb{S}^2$ so that the surface area of the convex hull of the points is maximized. It is shown that the optimal polyhedron has a trigonal bipyramidal structure with two vertices placed at the north and south poles and the other three vertices forming an equilateral triangle inscribed in the equator. This result confirms a conjecture of Akkiraju, who conducted a numerical search for the maximizer. As an application to crystallography, the surface area discrepancy is considered as a measure of distortion between an observed coordination polyhedron and an ideal one. The main result yields a formula for the surface area discrepancy of any coordination polyhedron with five vertices.

math.MG↗