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: "answer set solving with bounded treewidth revisited"
  Abstract: Parameterized algorithms are a way to solve hard problems more efficiently, given that a specific parameter of the input is small. In this paper, we apply this idea to the field of answer set programming (ASP). To this end, we propose two kinds of graph representations of programs to exploit their treewidth as a parameter. Treewidth roughly measures to which extent the internal structure of a program resembles a tree. Our main contribution is the design of parameterized dynamic programming algorithms, which run in linear time if the treewidth and weights of the given program are bounded. Compared to previous work, our algorithms handle the full syntax of ASP. Finally, we report on an empirical evaluation that shows good runtime behaviour for benchmark instances of low treewidth, especially for counting answer sets.

Connected through hyperedge HE-1 (induced by source paper "structural decompositions of epistemic logic programs"):
  with members:
    - "epistemic logic programs a different world view"
    - "treewidth and counting projected answer sets"
    - "te eth lower bounds for qbfs of bounded treewidth"
    - "splitting epistemic logic programs"
    - "the power of non ground rules in answer set programming"
    - "combining treewidth and backdoors for csp"
    - "clique width and directed width measures for answer set programming"
    - "backdoors to tractable answer set programming"

Connected through hyperedge HE-2 (induced by source paper "efficient contraction of large tensor networks for weighted model counting through graph decompositions"):
  with members:
    - "fast counting with tensor networks"
    - "benchmarking treewidth as a practical component of tensor network simulations"
    - "tensor comprehensions framework agnostic high performance machine learning abstractions"
    - "positive instance driven dynamic programming for treewidth"
    - "faq questions asked frequently"
    - "graph bisection with pareto optimization"
    - "era of big data processing a new approach via tensor networks and tensor decompositions"
    - "probabilistic planning via heuristic forward search and weighted model counting"

Connected through hyperedge HE-3 (induced by source paper "answer set solving exploiting treewidth and its limits"):
  with members:
    - "asp core 2 input language format"
    - "te eth lower bounds for qbfs of bounded treewidth"
    - "exploiting treewidth for projected model counting and its limits"
    - "counting complexity for reasoning in abstract argumentation"
    - "slightly superexponential parameterized problems"
    - "dynasp2 5 dynamic programming on tree decompositions in action"
    - "default logic and bounded treewidth"

Connected through hyperedge HE-4 (induced by source paper "treewidth and counting projected answer sets"):
  with members:
    - "te eth lower bounds for qbfs of bounded treewidth"
    - "exploiting treewidth for projected model counting and its limits"
    - "slightly superexponential parameterized problems"
    - "tractable answer set programming with weight constraints bounded treewidth is not enough"
    - "even faster integer multiplication"

Connected through hyperedge HE-5 (induced by source paper "a paraconsistent asp like language with tractable model generation"):
  with members:
    - "backdoors to tractable answer set programming"
    - "logical foundations and complexity of 4ql a query language with unrestricted negation"
    - "the dlv system for knowledge representation and reasoning"
    - "a hierarchy of tractable subsets for computing stable models"

Connected through hyperedge HE-6 (induced by source paper "default logic and bounded treewidth"):
  with members:
    - "dynasp2 5 dynamic programming on tree decompositions in action"
    - "strong backdoors for default logic"
    - "paradigms for parameterized enumeration"

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)