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 "parameterized compilation lower bounds for restricted cnf formulas"):
  Abstract: We show unconditional parameterized lower bounds in the area of knowledge compilation, more specifically on the size of circuits in decomposable negation normal form (DNNF) that encode CNF-formulas restricted by several graph width measures. In particular, we show that #R##N#- there are CNF formulas of size $n$ and modular incidence treewidth $k$ whose smallest DNNF-encoding has size $n^{\Omega(k)}$, and #R##N#- there are CNF formulas of size $n$ and incidence neighborhood diversity $k$ whose smallest DNNF-encoding has size $n^{\Omega(\sqrt{k})}$. #R##N#These results complement recent upper bounds for compiling CNF into DNNF and strengthen---quantitatively and qualitatively---known conditional low\-er bounds for cliquewidth. Moreover, they show that, unlike for many graph problems, the parameters considered here behave significantly differently from treewidth.

Includes members:
  Member "complexity and approximability of parameterized max csps":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal sparsification for some binary csps using low degree polynomials")
  Member "understanding model counting for beta acyclic cnf formulas":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "approximate counting csp seen from the other side")
  Member "no small nondeterministic read once branching programs for cnfs of bounded treewidth":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "connecting knowledge compilation classes and width parameters")
  Member "between treewidth and clique width":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "measuring what matters a hybrid approach to dynamic programming with treewidth")
  Member "on obdds for cnfs of bounded treewidth":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "connecting knowledge compilation classes and width parameters")
  Member "satisfiability of acyclic and almost acyclic cnf formulas":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "complexity and approximability of parameterized max csps")
  Member "a knowledge compilation map":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "abstracting probabilistic models a logical perspective")

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.AI(Artificial Intelligence)