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: "evaluating qbf solvers quantifier alternations matter"
  Abstract: We present an experimental study of the effects of quantifier alternations on the evaluation of quantified Boolean formula (QBF) solvers. The number of quantifier alternations in a QBF in prenex conjunctive normal form (PCNF) is directly related to the theoretical hardness of the respective QBF satisfiability problem in the polynomial hierarchy. We show empirically that the performance of solvers based on different solving paradigms substantially varies depending on the numbers of alternations in PCNFs. In related theoretical work, quantifier alternations have become the focus of understanding the strengths and weaknesses of various QBF proof systems implemented in solvers. Our results motivate the development of methods to evaluate orthogonal solving paradigms by taking quantifier alternations into account. This is necessary to showcase the broad range of existing QBF solving paradigms for practical QBF applications. Moreover, we highlight the potential of combining different approaches and QBF proof systems in solvers.

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"
    - "qbf as an alternative to courcelle s theorem"
    - "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 "qratpre effective qbf preprocessing via strong redundancy properties"):
  with members:
    - "expansion based qbf solving without recursion"
    - "on expansion and resolution in cegar based qbf solving"
    - "textsf qrat generalizing qrat by a more powerful qbf redundancy property"
    - "depqbf 6 0 a search based qbf solver beyond traditional qcdcl"
    - "the qbf gallery"
    - "clause term resolution and learning in the evaluation of quantified boolean formulas"

Connected through hyperedge HE-3 (induced by source paper "expansion based qbf solving without recursion"):
  with members:
    - "on expansion and resolution in cegar based qbf solving"
    - "encodings of bounded synthesis"
    - "depqbf 6 0 a search based qbf solver beyond traditional qcdcl"
    - "structural synthesis for gxw specifications"
    - "detecting unrealizability of distributed fault tolerant systems"
    - "conformant planning as a case study of incremental qbf solving"

Connected through hyperedge HE-4 (induced by source paper "depqbf 6 0 a search based qbf solver beyond traditional qcdcl"):
  with members:
    - "the qbf gallery"
    - "q resolution with generalized axioms"
    - "incrementally computing minimal unsatisfiable cores of qbfs via a clause group solver api"
    - "conformant planning as a case study of incremental qbf solving"
    - "incremental qbf solving"
    - "computing resolution path dependencies in linear time"
    - "clause term resolution and learning in the evaluation of quantified boolean formulas"

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.LO(Logic in Computer Science)