arXiv subjects

Yuping Li

Publications and source records attributed to Yuping Li.

7 recordsLinked to original sources

arXiv2026

Omni-scale Learning-based Sequential Decision Framework for Order Fulfillment of Tote-handling Robotic Systems

Driven by the rapid expansion of e-commerce and small-batch production, the size of the intralogistics load unit of finished goods, semi-finished goods and raw materials is steadily shrinking. Totes are gradually replacing pallets as the primary handling and storage container. This shift has propelled tote-handling robotic systems to the forefront of automation order fulfillment centers. The order-fulfillment decisions of tote-handling robotic systems share a common order-tote-robot sequential decision-making nature. Existing studies primarily focus on decision mechanisms tailored to particular systems, making it difficult to generalize or transfer them to other contexts. We propose an Omni-scale Learning-based Sequential Decision Framework for Order Fulfillment of Tote-handling Robotic Systems (OLSF-TRS), a generalized and scalable sequential decision framework that combines structured combinatorial optimization with multi-agent reinforcement learning to coordinate order,tote, and robot decisions. On small-scale tote-handling robotic systems, OLSF-TRS achieves near-optimal performance with average optimality gaps below 3.5% across two distinct system configurations. In large-scale scenarios, OLSF-TRS consistently outperforms heuristic baselines across two different system types, reducing total tote movements by 8-12% and over 30% compared to SOTA rule-based approaches, while maintaining real-time responsiveness. These improvements translate into tangible operational benefits, including cost reduction, lower energy consumption, and enhanced throughput stability. The proposed framework delivers an efficient and unified order fulfillment decision-making framework for widely deployed tote-handling robotic systems,supporting high-quality order fulfillment in both e-commerce and industrial logistics sectors.

cs.RO↗

arXiv2024

Origin of the charge density wave state in BaFe$_2$Al$_9$

Recently, a first-order phase transition associated with charge density wave (CDW) has been observed at low temperatures in intermetallic compound BaFe$_2$Al$_9$. However, this transition is absent in its isostructural sister compound BaCo$_2$Al$_9$. Consequently, an intriguing question arises as to the underlying factors that differentiate BaFe$_2$Al$_9$ from BaCo$_2$Al$_9$ and drive the CDW transition in BaFe$_2$Al$_9$. Here, we set out to address this question by conducting a comparative \emph{ab initio} study of the electronic structures, lattice dynamics, \textcolor{black}{and electron-phonon interactions} of their high-temperature phases. We find that both compounds are dynamically stable with similar phonon dispersions. The electronic structure calculations reveal that both compounds are nonmagnetic metals; however, they exhibit distinct band structures around the Fermi level. In particular, BaFe$_2$Al$_9$ exhibits a higher density of states at the Fermi level with dominant partially filled Fe-$3d$ states and a more intricate Fermi surface. This leads to an electronic instability of BaFe$_2$Al$_9$ toward the CDW transition, which is manifested by the diverged electronic susceptibility at the CDW wave vector $\mathbf{q}_{\rm CDW}$=(0.5, 0, 0.3), observable in both the real and imaginary parts. Conversely, BaCo$_2$Al$_9$ does not display such behavior, aligning well with experimental observations. Although the electron-phonon interactions in BaFe$_2$Al$_9$ surpass those in BaCo$_2$Al$_9$ by two orders of magnitude, the strength is relatively weak at the CDW wave vector, suggesting that the CDW in BaFe$_2$Al$_9$ is primarily driven by electronic factors.

cond-mat.mtrl-sci↗

arXiv2020

Topology-Aware Hashing for Effective Control Flow Graph Similarity Analysis

Control Flow Graph (CFG) similarity analysis is an essential technique for a variety of security analysis tasks, including malware detection and malware clustering. Even though various algorithms have been developed, existing CFG similarity analysis methods still suffer from limited efficiency, accuracy, and usability. In this paper, we propose a novel fuzzy hashing scheme called topology-aware hashing (TAH) for effective and efficient CFG similarity analysis. Given the CFGs constructed from program binaries, we extract blended n-gram graphical features of the CFGs, encode the graphical features into numeric vectors (called graph signatures), and then measure the graph similarity by comparing the graph signatures. We further employ a fuzzy hashing technique to convert the numeric graph signatures into smaller fixed-size fuzzy hash signatures for efficient similarity calculation. Our comprehensive evaluation demonstrates that TAH is more effective and efficient compared to existing CFG comparison techniques. To demonstrate the applicability of TAH to real-world security analysis tasks, we develop a binary similarity analysis tool based on TAH, and show that it outperforms existing similarity analysis tools while conducting malware clustering.

cs.CR↗

arXiv2017

Hopf Algebraic Structure for Tagged Graphs and Topological Recursion

Using the shuffle structure of the graphs, we introduce a new kind of the Hopf algebraic structure for tagged graphs with, or without loops. Like a quantum group structure, its product is non-commutative. With the help of the Hopf algebraic structure, after taking account symmetry of the tagged graphs, we reconstruct the topological recursion on spectral curves proposed by B. Eynard and N. Orantin, which includes the one-loop equations of various matrix integrals as special cases.

math-ph↗

arXiv2017

Android Malware Clustering through Malicious Payload Mining

Clustering has been well studied for desktop malware analysis as an effective triage method. Conventional similarity-based clustering techniques, however, cannot be immediately applied to Android malware analysis due to the excessive use of third-party libraries in Android application development and the widespread use of repackaging in malware development. We design and implement an Android malware clustering system through iterative mining of malicious payload and checking whether malware samples share the same version of malicious payload. Our system utilizes a hierarchical clustering technique and an efficient bit-vector format to represent Android apps. Experimental results demonstrate that our clustering approach achieves precision of 0.90 and recall of 0.75 for Android Genome malware dataset, and average precision of 0.98 and recall of 0.96 with respect to manually verified ground-truth.

cs.CR↗

arXiv2015

From $r$-Spin Intersection Numbers to Hodge Integrals

Generalized Kontsevich Matrix Model (GKMM) with a certain given potential is the partition function of $r$-spin intersection numbers. We represent this GKMM in terms of fermions and expand it in terms of the Schur polynomials by boson-fermion correspondence, and link it with a Hurwitz partition function and a Hodge partition by operators in a $\widehat{GL}(\infty)$ group. Then, from a $W_{1+\infty}$ constraint of the partition function of $r$-spin intersection numbers, we get a $W_{1+\infty}$ constraint for the Hodge partition function. The $W_{1+\infty}$ constraint completely determines the Schur polynomials expansion of the Hodge partition function.

hep-th↗

arXiv2014

New Algebraic Structures from Hermitian One-Matrix Model

Virasoro constraint is the operator algebra version of one-loop equation for a Hermitian one-matrix model, and it plays an important role in solving the model. We construct the realization of the Virasoro constraint from the Conformal Field Theory (CFT) method. From multi-loop equations of the one-matrix model, we get a more general constraint. It can be expressed in terms of the operator algebras, which is the Virasoro subalgebra with extra parameters. In this sense, we named as generalized Virasoro constraint. We enlarge this algebra with central extension, this is a new kind of algebra, and the usual Virasoro algebra is its subalgebra. And we give a bosonic realization of its subalgebra.

math-ph↗