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: "lazy model expansion interleaving grounding with search"
  Abstract: Finding satisfying assignments for the variables involved in a set of constraints can be cast as a (bounded) model generation problem: search for (bounded) models of a theory in some logic. The state-of-the-art approach for bounded model generation for rich knowledge representation languages, like ASP, FO(.) and Zinc, is ground-and-solve: reduce the theory to a ground or propositional one and apply a search algorithm to the resulting theory. #R##N#An important bottleneck is the blowup of the size of the theory caused by the reduction phase. Lazily grounding the theory during search is a way to overcome this bottleneck. We present a theoretical framework and an implementation in the context of the FO(.) knowledge representation language. Instead of grounding all parts of a theory, justifications are derived for some parts of it. Given a partial assignment for the grounded part of the theory and valid justifications for the formulas of the non-grounded part, the justifications provide a recipe to construct a complete assignment that satisfies the non-grounded part. When a justification for a particular formula becomes invalid during search, a new one is derived; if that fails, the formula is split in a part to be grounded and a part that can be justified. #R##N#The theoretical framework captures existing approaches for tackling the grounding bottleneck such as lazy clause generation and grounding-on-the-fly, and presents a generalization of the 2-watched literal scheme. We present an algorithm for lazy model expansion and integrate it in a model generator for FO(ID), a language extending first-order logic with inductive definitions. The algorithm is implemented as part of the state-of-the-art FO(ID) Knowledge-Base System IDP. Experimental results illustrate the power and generality of the approach.

Connected through hyperedge HE-1 (induced by source paper "extensions to justification theory"):
  with members:
    - "answering the why in answer set programming a survey of explanation approaches"
    - "computing stable models of normal logic programs without grounding"

Connected through hyperedge HE-2 (induced by source paper "constraints lazy constraints or propagators in asp solving an empirical analysis"):
  with members:
    - "constraint answer set solver ezcsp and why integration schemas matter"
    - "the power of non ground rules in answer set programming"
    - "combining answer set programming and domain heuristics for solving hard industrial problems application paper"
    - "a model building framework for answer set programming with external computations"
    - "modeling variations of first order horn abduction in answer set programming"
    - "the dlvhex system for knowledge representation recent advances system description"
    - "optimizing phylogenetic supertrees using answer set programming"
    - "generating explanations for biomedical queries"

Connected through hyperedge HE-3 (induced by source paper "propagators and solvers for the algebra of modular systems"):
  with members:
    - "asp modulo csp the clingcon system"
    - "towards propagation logic control"

Connected through hyperedge HE-4 (induced by source paper "implementing a relevance tracker module"):
  with members:
    - "stable model counting and its application in probabilistic logic programming"

Connected through hyperedge HE-5 (induced by source paper "predicate logic as a modeling language modeling and solving some machine learning and data mining problems with idp3"):
  with members:
    - "predicate logic as a modelling language the idp system"
    - "a prototype of a knowledge based programming environment"
    - "xsb extending prolog with tabled logic programming"
    - "constraint propagation for first order logic and inductive definitions"
    - "grounding fo and fo id with bounds"
    - "the dlv system for knowledge representation and reasoning"
    - "efficient constraint propagation engines"
    - "well founded and stable semantics of logic programs with aggregates"

Connected through hyperedge HE-6 (induced by source paper "modeling variations of first order horn abduction in answer set programming using on demand constraints and flexible value invention"):
  with members:
    - "a model building framework for answer set programming with external computations"
    - "modeling variations of first order horn abduction in answer set programming"
    - "asperix a first order forward chaining approach for answer set computing"
    - "clingo asp control preliminary report"
    - "the ciff proof procedure for abductive logic programming with constraints theory implementation and experiments"

Connected through hyperedge HE-7 (induced by source paper "predicate logic as a modelling language the idp system"):
  with members:
    - "the third open answer set programming competition"
    - "an enhanced features extractor for a portfolio of constraint solvers"
    - "asp modulo csp the clingcon system"
    - "an empirical evaluation of portfolios approaches for solving csps"
    - "translation based constraint answer set solving"
    - "grounding fo and fo id with bounds"
    - "the dlv system for knowledge representation and reasoning"
    - "extending classical logic with inductive definitions"

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)