arXiv subjects

Ben Yang

Publications and source records attributed to Ben Yang.

11 recordsLinked to original sources

arXiv2026

It Takes Two to Tango: A Holistic Simulator for Joint Order Scheduling and Multi-Agent Path Finding in Robotic Warehouses

The prevailing paradigm in Robotic Mobile Fulfillment Systems (RMFS) typically treats order scheduling and multi-agent pathfinding as isolated sub-problems. We argue that this decoupling is a fundamental bottleneck, masking the critical dependencies between high-level dispatching and low-level congestion. Existing simulators fail to bridge this gap, often abstracting away heterogeneous kinematics and stochastic execution failures. We propose WareRover, a holistic simulation platform that enforces a tight coupling between OS and MAPF via a unified, closed-loop optimization interface. Unlike standard benchmarks, WareRover integrates dynamic order streams, physics-aware motion constraints, and non-nominal recovery mechanisms into a single evaluation loop. Experiments reveal that SOTA algorithms often falter under these realistic coupled constraints, demonstrating that WareRover provides a necessary and challenging testbed for robust, next-generation warehouse coordination. The project and video is available at https://hhh-x.github.io/WareRover/.

cs.RO↗

arXiv2025

One-step Multi-view Clustering With Adaptive Low-rank Anchor-graph Learning

In light of their capability to capture structural information while reducing computing complexity, anchor graph-based multi-view clustering (AGMC) methods have attracted considerable attention in large-scale clustering problems. Nevertheless, existing AGMC methods still face the following two issues: 1) They directly embedded diverse anchor graphs into a consensus anchor graph (CAG), and hence ignore redundant information and numerous noises contained in these anchor graphs, leading to a decrease in clustering effectiveness; 2) They drop effectiveness and efficiency due to independent post-processing to acquire clustering indicators. To overcome the aforementioned issues, we deliver a novel one-step multi-view clustering method with adaptive low-rank anchor-graph learning (OMCAL). To construct a high-quality CAG, OMCAL provides a nuclear norm-based adaptive CAG learning model against information redundancy and noise interference. Then, to boost clustering effectiveness and efficiency substantially, we incorporate category indicator acquisition and CAG learning into a unified framework. Numerous studies conducted on ordinary and large-scale datasets indicate that OMCAL outperforms existing state-of-the-art methods in terms of clustering effectiveness and efficiency.

cs.LG↗

arXiv2023

Occupation Number Representation of Graph

In this paper, we propose a new way to represent graphs in quantum space. In that approach, we replace the rows of the adjacency matrix of the graph by state vectors in the occupation number representation. Unlike the traditional definition of graph states, we actually let the occupation number of a single-particle state denote the number of edges between each two adjacent vertices. This allows us to avoid taking into account the interaction between each two particles. Based on the creation and annihilation operators, we propose the edge creation and annihilation operators. With these two operators, we can implement the fundamental operation of adding and removing edges and vertices in a graph. Then all additional operations in the graph such as vertex contractions can be defined. Our method can be used to represent both simple and multigraphs. Directed and undirected graphs are also compatible with our approach. The method of representation proposed in this paper enriches the theory of graph representation in quantum space.

quant-ph↗

arXiv2022

TriNet: stabilizing self-supervised learning from complete or slow collapse on ASR

Self-supervised learning (SSL) models confront challenges of abrupt informational collapse or slow dimensional collapse. We propose TriNet, which introduces a novel triple-branch architecture for preventing collapse and stabilizing the pre-training. TriNet learns the SSL latent embedding space and incorporates it to a higher level space for predicting pseudo target vectors generated by a frozen teacher. Our experimental results show that the proposed method notably stabilizes and accelerates pre-training and achieves a relative word error rate reduction (WERR) of 6.06% compared to the state-of-the-art (SOTA) Data2vec for a downstream benchmark ASR task. We will release our code at https://github.com/tencent-ailab/.

eess.AS↗

arXiv2019

Self-decoupled tetrapodal perylene molecules for luminescence studies of isolated emitters on Au(111)

Self-decoupled tetrapodal perylene molecules were designed, synthesized, and deposited on the Au(111) surface through the electrosprayionization technique. Photoluminescence and lifetime measurements show that the chromophore groups of the designed molecules are welldecoupled from the gold substrate. Preliminary scanning tunneling microscopy induced luminescence measurements indicate theobservation of molecule-specific emissions from isolated single tetrapodal perylene molecules adsorbed directly on Au(111). The emergenceof significant emission when the tip is positioned at the molecular center suggests that there is a considerable vertical component of the transitiondipole of the designed molecule along the tip axial direction. Our results may open up a route for the realization of nanolight sourcesand plasmonic devices based on organic molecules.

physics.optics↗

arXiv2019

Visually Constructing the Chemical Structure of a Single Molecule by Scanning Raman Picoscopy

The strong spatial confinement of a nanocavity plasmonic field has made it possible to visualize the inner structure of a single molecule and even to distinguish its vibrational modes in real space. With such ever-improved spatial resolution, it is anticipated that full vibrational imaging of a molecule could be achieved to reveal molecular structural details. Here we demonstrate full Raman images of individual vibrational modes on the {\AA}ngstr\"om level for a single Mg-porphine molecule, revealing distinct characteristics of each vibrational mode in real space. Furthermore, by exploiting the underlying interference effect and Raman fingerprint database, we propose a new methodology for structural determination, coined as scanning Raman picoscopy, to show how such ultrahigh-resolution spectromicroscopic vibrational images can be used to visually assemble the chemical structure of a single molecule through a simple Lego-like building process.

physics.chem-ph↗

arXiv2016

1-color-avoiding paths, special tournaments, and incidence geometry

We discuss two approaches to a recent question of Loh: must a 3-colored transitive tournament on $N$ vertices have a 1-color-\emph{avoiding} path of vertex-length at least $N^{2/3}$? This question generalizes the Erd\H{o}s--Szekeres theorem on monotone subsequences. First, we define three canonical transformations on these tournaments called Color, Record, and Dual. We use these to establish a reduction to special tournaments with natural geometric and combinatorial properties. In many cases (including all known tight examples), these tournaments have recursive Gallai decompositions. Not all relevant tournaments have Gallai decompositions, but those that do satisfy the desired $N^{2/3}$ bound by recent work of Wagner, roughly analogous to earlier work of Fox, Grinshpun, and Pach on a similar \emph{undirected} problem. Second, we consider the related geometric problem of bounding \emph{slice-increasing} sets $S\subseteq [n]^3$, which---under an additional ordering hypothesis on $S$---was shown by Loh to be equivalent to the original question. In particular, we establish a rigorous connection from a problem of Szab\'o and Tardos, raise a stronger $L^2$-question on slice-counts, and mention a surprising overlap with the joints problem.

math.CO↗

arXiv2016

Generalizations of Joints Problem

We generalize the joints problem to sets of varieties and prove almost sharp bound on the number of joints. As a special case, given a set of $N$ $2$-planes in $\mathbb{R}^6$, the number of points at which three $2$-planes intersect and span $\mathbb{R}^6$ is at most $CN^{3/2+\epsilon}$. We also get almost sharp bound on the number of joints with multiplicities. The main tools are polynomial partitioning and induction on dimension.

math.CO↗

arXiv2014

Generalizations of the Szemer\'edi-Trotter Theorem

We generalize the Szemer\'edi-Trotter incidence theorem, to bound the number of complete \emph{flags} in higher dimensions. Specifically, for each $i=0,1,\ldots,d-1$, we are given a finite set $S_i$ of $i$-flats in $\R^d$ or in $\C^d$, and a (complete) flag is a tuple $(f_0,f_1,\ldots,f_{d-1})$, where $f_i\in S_i$ for each $i$ and $f_i\subset f_{i+1}$ for each $i=0,1,\ldots,d-2$. Our main result is an upper bound on the number of flags which is tight in the worst case. We also study several other kinds of incidence problems, including (i) incidences between points and lines in $\R^3$ such that among the lines incident to a point, at most $O(1)$ of them can be coplanar, (ii) incidences with Legendrian lines in $\R^3$, a special class of lines that arise when considering flags that are defined in terms of other groups, and (iii) flags in $\R^3$ (involving points, lines, and planes), where no given line can contain too many points or lie on too many planes. The bound that we obtain in (iii) is nearly tight in the worst case. Finally, we explore a group theoretic interpretation of flags, a generalized version of which leads us to new incidence problems.

math.CO↗

arXiv2013

Bounds of incidences between points and algebraic curves

We prove new bounds on the number of incidences between points and higher degree algebraic curves. The key ingredient is an improved initial bound, which is valid for all fields. Then we apply the polynomial method to obtain global bounds on $\mathbb{R}$ and $\mathbb{C}$.

math.CO↗

arXiv2013

Distributed Overlay Anycast Table using Space filling curves

In this paper we present the \emph{Distributed Overlay Anycast Table}, a structured overlay that implements application-layer anycast, allowing the discovery of the closest host that is a member of a given group. One application is in locality-aware peer-to-peer networks, where peers need to discover low-latency peers participating in the distribution of a particular file or stream. The DOAT makes use of network delay coordinates and a space filling curve to achieve locality-aware routing across the overlay, and Bloom filters to aggregate group identifiers. The solution is designed to optimise both accuracy and query time, which are essential for real-time applications. We simulated DOAT using both random and realistic node distributions. The results show that accuracy is high and query time is low.

cs.NI↗