human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "on sat representations of xor constraints"):
  Abstract: We consider the problem of finding good representations, via boolean conjunctive normal forms F clause-sets, of systems S of XOR-constraints x 1i¾ź'i¾źx n =e, e∈{0,1} also called parity constraints, i.e., systems of linear equations over the two-element field. These representations are to be used as parts of SAT problems F *i¾źF, such that F * has "good" properties for SAT solving. The basic quality criterion is "arc consistency", that is, for every partial assignment i¾ź to the variables of S, all assignments x i =e forced by i¾ź are determined by unit-clause propagation on the result i¾ź* F of the application. We show there is no arc-consistent representation of polynomial size for arbitrary S. The proof combines the basic method by Bessiere et al. 2009 [2] on the relation between monotone circuits and "consistency checkers", adapted and simplified in the underlying report Gwynne et al. [10], with the lower bound on monotone circuits for monotone span programs in Babai et al. 1999 [1]. On the other side, our basic positive result is that computing an arc-consistent representation is fixed-parameter tractable in the number m of equations of S. To obtain stronger representations, instead of mere arc-consistency we consider the class    ${\mathcal{PC}}$    of propagation-complete clause-sets, as introduced in Bordeaux et al. 2012 [4]. The stronger criterion is now    $F \in{\mathcal{PC}}$   , which requires for all partial assignments, possibly involving also the auxiliary new variables in F, that forced assignments can be determined by unit-clause propagation. We analyse the basic translation, which for m=1 lies in    ${\mathcal{PC}}$   , but fails badly so already for m=2, and we show how to repair this.

Includes members:
  Member "generalising unit refutation completeness and slur via nested input resolution":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "towards a theory of good sat representations")
  Member "simulating parity reasoning extended version":
    also connected through other hyperedges:
      (none)
  Member "trading inference effort versus size in cnf knowledge compilation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards a theory of good sat representations")
  Member "hardness measures and resolution lower bounds":
    also connected through other hyperedges:
      (none)
  Member "towards a theory of good sat representations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "generalising unit refutation completeness and slur via nested input resolution")
  Member "unit contradiction versus unit propagation":
    also connected through other hyperedges:
      (none)
  Member "extending clause learning sat solvers with complete parity reasoning extended version":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "simulating parity reasoning extended version")
  Member "circuit complexity and decompositions of global constraints":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "bounds on the size of pc and urc formulas")

Question: Please tell me which class the source paper 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)