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: "on oblivious branching programs with bounded repetition that cannot efficiently compute cnfs of bounded treewidth"
  Abstract: In this paper we study complexity of an extension of ordered binary decision diagrams (OBDDs) called $c$-OBDDs on CNFs of bounded (primal graph) treewidth. In particular, we show that for each $k$ there is a class of CNFs of treewidth $k \geq 3$ for which the equivalent $c$-OBDDs are of size $\Omega(n^{k/(8c-4)})$. Moreover, this lower bound holds if $c$-OBDD is non-deterministic and semantic. Our second result uses the above lower bound to separate the above model from sentential decision diagrams (SDDs). In order to obtain the lower bound, we use a structural graph parameter called matching width. Our third result shows that matching width and pathwidth are linearly related.

Connected through hyperedge HE-1 (induced by source paper "on the relative succinctness of sentential decision diagrams"):
  with members:
    - "a superpolynomial lower bound for the size of non deterministic complement of an unambiguous automaton"
    - "non fpt lower bounds for structural restrictions of decision dnnf"
    - "circuit treewidth sentential decision and query compilation"
    - "sdds are exponentially more succinct than obdds"
    - "new limits for knowledge compilation and applications to exact model counting"
    - "on the read once property of branching programs and cnfs of bounded treewidth"
    - "lower bounds for exact model counting and applications in probabilistic databases"
    - "the language of search"

Connected through hyperedge HE-2 (induced by source paper "two types of branching programs with bounded repetition that cannot efficiently compute monotone 3 cnfs"):
  with members:
    - "no small nondeterministic read once branching programs for cnfs of bounded treewidth"

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.CC(Computational Complexity)