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: "qbf as an alternative to courcelle s theorem"
  Abstract: We propose reductions to quantified Boolean formulas (QBF) as a new approach to showing fixed-parameter linear algorithms for problems parameterized by treewidth. We demonstrate the feasibility of this approach by giving new algorithms for several well-known problems from artificial intelligence that are in general complete for the second level of the polynomial hierarchy. By reduction from QBF we show that all resulting algorithms are essentially optimal in their dependence on the treewidth. Most of the problems that we consider were already known to be fixed-parameter linear by using Courcelle's Theorem or dynamic programming, but we argue that our approach has clear advantages over these techniques: on the one hand, in contrast to Courcelle's Theorem, we get concrete and tight guarantees for the runtime dependence on the treewidth. On the other hand, we avoid tedious dynamic programming and, after showing some normalization results for CNF-formulas, our upper bounds often boil down to a few lines.

Connected through hyperedge HE-1 (induced by source paper "te eth lower bounds for qbfs of bounded treewidth"):
  with members:
    - "treewidth and counting projected answer sets"
    - "exploiting treewidth for projected model counting and its limits"
    - "counting complexity for reasoning in abstract argumentation"
    - "evaluating qbf solvers quantifier alternations matter"
    - "slightly superexponential parameterized problems"
    - "parameterized complexity results for exact bayesian network structure learning"
    - "backdoors to tractable answer set programming"

Connected through hyperedge HE-2 (induced by source paper "graph width measures for cnf encodings with auxiliary variables"):
  with members:
    - "connecting knowledge compilation classes and width parameters"
    - "connecting width and structure in knowledge compilation"
    - "circuit treewidth sentential decision and query compilation"
    - "understanding model counting for beta acyclic cnf formulas"
    - "strong backdoors to bounded treewidth sat"
    - "a knowledge compilation map"

Connected through hyperedge HE-3 (induced by source paper "revisiting graph width measures for cnf encodings"):
  with members:
    - "connecting knowledge compilation classes and width parameters"
    - "connecting width and structure in knowledge compilation"
    - "circuit treewidth sentential decision and query compilation"
    - "model counting for formulas of bounded clique width"
    - "strong backdoors to bounded treewidth sat"
    - "a knowledge compilation map"

Connected through hyperedge HE-4 (induced by source paper "counting complexity for reasoning in abstract argumentation"):
  with members:
    - "paradigms for parameterized enumeration"
    - "dynpartix a dynamic programming reasoner for abstract argumentation"

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.AI(Artificial Intelligence)