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 "the complexity of approximately counting in 2 spin systems on k uniform bounded degree hypergraphs"):
  Abstract: One of the most important recent developments in the complexity of approximate counting is the classification of the complexity of approximating the partition functions of antiferromagnetic 2-spin systems on bounded-degree graphs. This classification is based on a beautiful connection to the so-called uniqueness phase transition from statistical physics on the infinite $\Delta$-regular tree. Our objective is to study the impact of this classification on unweighted 2-spin models on $k$-uniform hypergraphs. As has already been indicated by Yin and Zhao, the connection between the uniqueness phase transition and the complexity of approximate counting breaks down in the hypergraph setting. Nevertheless, we show that for every non-trivial symmetric $k$-ary Boolean function $f$ there exists a degree bound $\Delta_0$ so that for all $\Delta \geq \Delta_0$ the following problem is NP-hard: given a $k$-uniform hypergraph with maximum degree at most $\Delta$, approximate the partition function of the hypergraph 2-spin model associated with $f$. It is NP-hard to approximate this partition function even within an exponential factor. By contrast, if $f$ is a trivial symmetric Boolean function (e.g., any function $f$ that is excluded from our result), then the partition function of the corresponding hypergraph 2-spin model can be computed exactly in polynomial time.

Includes members:
  Member "inapproximability of the partition function for the antiferromagnetic ising and hard core models":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "lower bounds for testing graphical models colorings and antiferromagnetic ising models")
  Member "counting hypergraph matchings up to uniqueness threshold":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on local distributed sampling and counting")
  Member "approximation via correlation decay when strong spatial mixing fails":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fast sampling and counting k sat solutions in the local lemma regime")
  Member "fptas for counting monotone cnf":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "computing the independence polynomial in shearer s region for the lll")
  Member "inapproximability after uniqueness phase transition in two spin systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "bis hardness for 2 spin systems on bipartite bounded degree graphs in the tree non uniqueness region")
  Member "approximation algorithms for two state anti ferromagnetic spin systems on bounded degree graphs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "efficient distance approximation for structured high dimensional distributions via learning")
  Member "correlation decay up to uniqueness in spin systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "spectral independence in high dimensional expanders and applications to the hardcore model")
  Member "computational transition at the uniqueness threshold":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "spectral independence in high dimensional expanders and applications to the hardcore model")

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)