human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "local wl invariance and hidden shades of regularity"):
  Abstract: The $k$-dimensional Weisfeiler-Leman algorithm ($k$-WL) is a powerful tool for testing isomorphism of two given graphs. We aim at investigating the ability of $k$-WL to capture properties of vertices (or small sets of vertices) in a single input graph $G$. In general, $k$-WL computes a canonical coloring of $k$-tuples of vertices of $G$, which determines a canonical coloring of $s$-tuples for each $s$ between 1 and $k$. We say that a property (or a numerical parameter) of $s$-tuples is $k$-invariant if it is determined by the tuple color. Our main result establishes $k$-invariance of the parameters counting the number of extensions of an $s$-tuple of vertices to a given subgraph pattern $F$. We state a sufficient condition for $k$-invariance in terms of the treewidth of $F$ and its homomorphic images, using suitable variants of these concepts for graphs with $s$ designated roots. As an application, we observe some non-obvious regularity properties of strongly regular graphs: For example, if $G$ is strongly regular, then the number of paths of length 6 between vertices $x$ and $y$ in $G$ depends only on whether or not $x$ and $y$ are adjacent (and the length 6 is here optimal). Despite the fact that $k$-WL indistinguishability of vertex tuples implies high degree of regularity, we prove, on the negative side, that no fixed dimension $k$ suffices for $k$-WL to recognize global symmetry of a graph. Specifically, for every $k$, there is a graph $G$ whose vertex set is colored by $k$-WL uniformly while $G$ is not vertex-transitive.

Includes members:
  Member "identifiability of graphs with small color classes by the weisfeiler leman algorithm":
    also connected through other hyperedges:
      (none)
  Member "on the weisfeiler leman dimension of fractional packing":
    also connected through other hyperedges:
      (none)
  Member "a survey on graph kernels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "generalization and representational limits of graph neural networks")
  Member "on weisfeiler leman invariance subgraph counts and related graph properties":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "can graph neural networks count substructures")
  Member "homomorphisms are a good basis for counting small subgraphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "tight bounds for planar strongly connected steiner subgraph with fixed number of terminals and extensions")
  Member "benchmark graphs for practical graph isomorphism":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning to sample hard instances for graph algorithms")
  Member "on the combinatorial power of the weisfeiler lehman algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a survey on the expressive power of graph neural networks")
  Member "graph isomorphism in quasipolynomial time":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "hypergraph isomorphism for groups with restricted composition factors")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CC(Computational Complexity)