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: "polynomial lower bound for distributed graph coloring in a weak local model"
  Abstract: We show an $\Omega\big(\Delta^{\frac{1}{3}-\frac{\eta}{3}}\big)$ lower bound on the runtime of any deterministic distributed $\mathcal{O}\big(\Delta^{1+\eta}\big)$-graph coloring algorithm in a weak variant of the \LOCAL\ model. #R##N#In particular, given a network graph \mbox{$G=(V,E)$}, in the weak \LOCAL\ model nodes communicate in synchronous rounds and they can use unbounded local computation. We assume that the nodes have no identifiers, but that instead, the computation starts with an initial valid vertex coloring. A node can \textbf{broadcast} a \textbf{single} message of \textbf{unbounded} size to its neighbors and receives the \textbf{set of messages} sent to it by its neighbors. That is, if two neighbors of a node $v\in V$ send the same message to $v$, $v$ will receive this message only a single time; without any further knowledge, $v$ cannot know whether a received message was sent by only one or more than one neighbor. #R##N#Neighborhood graphs have been essential in the proof of lower bounds for distributed coloring algorithms, e.g., \cite{linial92,Kuhn2006On}. Our proof analyzes the recursive structure of the neighborhood graph of the respective model to devise an $\Omega\big(\Delta^{\frac{1}{3}-\frac{\eta}{3}}\big)$ lower bound on the runtime for any deterministic distributed $\mathcal{O}\big(\Delta^{1+\eta}\big)$-graph coloring algorithm. #R##N#Furthermore, we hope that the proof technique improves the understanding of neighborhood graphs in general and that it will help towards finding a lower (runtime) bound for distributed graph coloring in the standard \LOCAL\ model. Our proof technique works for one-round algorithms in the standard \LOCAL\ model and provides a simpler and more intuitive proof for an existing $\Omega(\Delta^2)$ lower bound.

Connected through hyperedge HE-1 (induced by source paper "faster deterministic distributed coloring through recursive list coloring"):
  with members:
    - "towards the locality of vizing s theorem"
    - "distributed approximation algorithms for maximum matching in graphs and hypergraphs"
    - "improved distributed delta coloring"
    - "the complexity of distributed edge coloring with small palettes"
    - "deterministic distributed edge coloring with fewer colors"
    - "deterministic distributed edge coloring via hypergraph maximal matching"
    - "adapting sequential algorithms to the distributed setting"
    - "on derandomizing local distributed algorithms"

Connected through hyperedge HE-2 (induced by source paper "efficient deterministic distributed coloring with small bandwidth"):
  with members:
    - "faster deterministic distributed coloring through recursive list coloring"
    - "on the use of randomness in local distributed graph algorithms"
    - "deterministic distributed dominating set approximation in the congest model"
    - "delta 1 coloring in the congested clique model"
    - "local distributed algorithms in highly dynamic networks"
    - "the complexity of delta 1 coloring incongested clique massively parallel computation and centralized local computation"
    - "quadratic and near quadratic lower bounds for the congest model"
    - "adapting sequential algorithms to the distributed setting"

Connected through hyperedge HE-3 (induced by source paper "distributed computing in the asynchronous local model"):
  with members:
    - "improved deterministic distributed matching via rounding"
    - "on the complexity of local distributed graph problems"
    - "local conflict coloring"
    - "weak models of distributed computing with connections to modal logic"

Connected through hyperedge HE-4 (induced by source paper "a time hierarchy theorem for the local model"):
  with members:
    - "the complexity of distributed edge coloring with small palettes"
    - "lcl problems on grids"
    - "lopsidependency in the moser tardos framework beyond the lopsided lovasz local lemma"
    - "distributed degree splitting edge coloring and orientations"
    - "survey of distributed decision"
    - "an exponential separation between randomized and deterministic complexity in the local model"
    - "on the complexity of local distributed graph problems"
    - "commutativity in the algorithmic lovasz local lemma"

Connected through hyperedge HE-5 (induced by source paper "locally iterative distributed delta 1 coloring below szegedy vishwanathan barrier and applications to self stabilization and to restricted bandwidth models"):
  with members:
    - "symmetry breaking in the congest model time and message efficient algorithms for ruling sets"
    - "deterministic distributed edge coloring via hypergraph maximal matching"
    - "derandomizing local distributed algorithms under bandwidth restrictions"
    - "on the complexity of local distributed graph problems"
    - "optimal dynamic distributed mis"
    - "a fast network decomposition algorithm and its applications to constant time distributed computation"
    - "toward more localized local algorithms removing assumptions concerning global knowledge"
    - "the locality of distributed symmetry breaking"

Connected through hyperedge HE-6 (induced by source paper "on the complexity of local distributed graph problems"):
  with members:
    - "distributed degree splitting edge coloring and orientations"
    - "distributed delta 1 coloring in sublogarithmic rounds"
    - "an exponential separation between randomized and deterministic complexity in the local model"
    - "a hierarchy of local decision"
    - "distributed strong diameter network decomposition"
    - "a fast network decomposition algorithm and its applications to constant time distributed computation"
    - "local conflict coloring"
    - "node labels in local decision"

Connected through hyperedge HE-7 (induced by source paper "distributed delta 1 coloring in sublogarithmic rounds"):
  with members:
    - "the complexity of distributed edge coloring with small palettes"
    - "a time hierarchy theorem for the local model"
    - "simple and near optimal distributed coloring for sparse graphs"
    - "a distributed 2 epsilon approximation for vertex cover in o log delta epsilon log log delta rounds"
    - "an exponential separation between randomized and deterministic complexity in the local model"
    - "a fast network decomposition algorithm and its applications to constant time distributed computation"
    - "local conflict coloring"
    - "an improved distributed algorithm for maximal independent set"

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.DC(Distributed, Parallel, and Cluster Computing)