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: "identity testing for constant width and commutative read once oblivious abps"
  Abstract: We give improved hitting-sets for two special cases of Read-once Oblivious Arithmetic Branching Programs (ROABP). First is the case of an ROABP with known variable order. The best hitting-set known for this case had cost $(nw)^{O(\log n)}$, where $n$ is the number of variables and $w$ is the width of the ROABP. Even for a constant-width ROABP, nothing better than a quasi-polynomial bound was known. We improve the hitting-set complexity for the known-order case to $n^{O(\log w)}$. In particular, this gives the first polynomial time hitting-set for constant-width ROABP (known-order). However, our hitting-set works only over those fields whose characteristic is zero or large enough. To construct the hitting-set, we use the concept of the rank of partial derivative matrix. Unlike previous approaches whose basic building block is a monomial map, we use a polynomial map. #R##N#The second case we consider is that of commutative ROABP. The best known hitting-set for this case had cost $d^{O(\log w)}(nw)^{O(\log \log w)}$, where $d$ is the individual degree. We improve this hitting-set complexity to $(ndw)^{O(\log \log w)}$. We get this by achieving rank concentration more efficiently.

Connected through hyperedge HE-1 (induced by source paper "small hitting sets for tiny arithmetic circuits or how to turn bad designs into good"):
  with members:
    - "on the complexity of partial derivatives"
    - "bipartite perfect matching is in quasi nc"
    - "the chasm at depth four and tensor rank old results new insights"
    - "a deterministic polynomial time algorithm for non commutative rational identity testing"
    - "progress on polynomial identity testing ii"
    - "on identity testing of tensors low rank recovery and compressed sensing"
    - "geometric complexity theory v equivalence between blackbox derandomization of polynomial identity testing and derandomization of noether s normalization lemma"
    - "algebraic independence and blackbox identity testing"

Connected through hyperedge HE-2 (induced by source paper "identity testing for constant width and any order read once oblivious arithmetic branching programs"):
  with members:
    - "identity testing and lower bounds for read k oblivious algebraic branching programs"
    - "hitting sets for roabp and sum of set multilinear circuits"
    - "deterministic identity testing for sum of read once oblivious arithmetic branching programs"
    - "arithmetic circuits the chasm at depth four gets wider"

Connected through hyperedge HE-3 (induced by source paper "quasi polynomial hitting sets for circuits with restricted parse trees"):
  with members:
    - "hitting sets for roabp and sum of set multilinear circuits"
    - "deterministic identity testing for sum of read once oblivious arithmetic branching programs"
    - "quasipolynomial time identity testing of non commutative and read once oblivious algebraic branching programs"

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)