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: "2 log n 1 10 o 1 hardness for hypergraph coloring"
  Abstract: We show that it is quasi-NP-hard to color 2-colorable 8-uniform hypergraphs with $2^{(\log N)^{1/10-o(1)}}$ colors, where $N$ is the number of vertices. There has been much focus on hardness of hypergraph coloring recently. Guruswami, H{\aa}stad, Harsha, Srinivasan and Varma showed that it is quasi-NP-hard to color 2-colorable 8-uniform hypergraphs with $2^{2^{\Omega(\sqrt{\log\log N})}}$ colors. Their result is obtained by composing standard Label Cover with an inner-verifier based on Low Degree Long Code, using Reed-Muller code testing results by Dinur and Guruswami. Using a different approach, Khot and Saket constructed a new variant of Label Cover, and composed it with Quadratic Code to show quasi-NP-hardness of coloring 2-colorable 12-uniform hypergraphs with $2^{(\log N)^c}$ colors, for some $c$ around 1/20. Their construction of Label Cover is based on a new notion of superposition complexity for CSP instances. The composition with inner-verifier was subsequently improved by Varma, giving the same hardness result for 8-uniform hypergraphs. #R##N#Our construction uses both Quadratic Code and Low Degree Long Code, and builds upon the work by Khot and Saket. We present a different approach to construct CSP instances with superposition hardness by observing that when the number of assignments is odd, satisfying a constraint in superposition is the same as "odd-covering" the constraint. We employ Low Degree Long Code in order to keep the construction efficient. In the analysis, we also adapt and generalize one of the key theorems by Dinur and Guruswami in the context of analyzing probabilistically checkable proof systems.

Connected through hyperedge HE-1 (induced by source paper "robust multiplication based tests for reed muller codes"):
  with members:
    - "super polylogarithmic hypergraph coloring hardness via low degree long codes"
    - "reducing uniformity in khot saket hypergraph coloring hardness reductions"
    - "some improvements to total degree tests"
    - "making the long code shorter with applications to the unique games conjecture"

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.CC(Computational Complexity)