human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "canonisation and definability for graphs of bounded rank width"
  Abstract: We prove that the combinatorial Weisfeiler-Leman algorithm of dimension $(3k+4)$ is a complete isomorphism test for the class of all graphs of rank width at most $k$. Rank width is a graph invariant that, similarly to tree width, measures the width of a certain style of hierarchical decomposition of graphs; it is equivalent to clique width. It was known that isomorphism of graphs of rank width $k$ is decidable in polynomial time (Grohe and Schweitzer, FOCS 2015), but the best previously known algorithm has a running time $n^{f(k)}$ for a non-elementary function $f$. Our result yields an isomorphism test for graphs of rank width $k$ running in time $n^{O(k)}$. Another consequence of our result is the first polynomial time canonisation algorithm for graphs of bounded rank width. Our second main result is that fixed-point logic with counting captures polynomial time on all graph classes of bounded rank width.

Connected through hyperedge HE-1 (induced by source paper "a linear upper bound on the weisfeiler leman dimension of graphs of bounded genus"):
  with members:
    - "a finite model theoretic view on propositional proof complexity"
    - "weisfeiler and leman go neural higher order graph neural networks"
    - "definable ellipsoid method sums of squares proofs and the isomorphism problem"
    - "the weisfeiler leman dimension of planar graphs is at most 3"
    - "on the combinatorial power of the weisfeiler lehman algorithm"
    - "semi supervised classification with graph convolutional networks"
    - "upper bounds on the quantifier depth for graph differentiation in first order logic"
    - "graph isomorphism in quasipolynomial time"

Connected through hyperedge HE-2 (induced by source paper "the power of the weisfeiler leman algorithm to decompose graphs"):
  with members:
    - "towards a practical k dimensional weisfeiler leman algorithm"
    - "a linear upper bound on the weisfeiler leman dimension of graphs of bounded genus"
    - "weisfeiler and leman go neural higher order graph neural networks"
    - "lov asz meets weisfeiler and leman"
    - "the weisfeiler leman dimension of planar graphs is at most 3"
    - "on the combinatorial power of the weisfeiler lehman algorithm"
    - "graph isomorphism for unit square graphs"
    - "practical graph isomorphism ii"

Connected through hyperedge HE-3 (induced by source paper "graph isomorphism for h_1 h_2 free graphs an almost complete dichotomy"):
  with members:
    - "an improved isomorphism test for bounded tree width graphs"
    - "a faster isomorphism test for graphs of small degree"
    - "clique width for graph classes closed under complementation"
    - "graph isomorphism for unit square graphs"
    - "induced minor free graphs isomorphism and clique width"
    - "bounding the clique width of h free chordal graphs"
    - "colouring diamond free graphs"
    - "isomorphism testing for graphs of bounded rank width"

Question: Please tell me which class the center node 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.DS(Data Structures and Algorithms)