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 "the 4 3 additive spanner exponent is tight"):
  Abstract: A spanner is a sparse subgraph that approximately preserves the pairwise distances of the original graph. It is well known that there is a smooth tradeoff between the sparsity of a spanner and the quality of its approximation, so long as distance error is measured multiplicatively. A central open question in the field is to prove or disprove whether such a tradeoff exists also in the regime of additive error. That is, is it true that for all $e>0$, there is a constant $k_e$ such that every graph has a spanner on $O(n^{1+e})$ edges that preserves its pairwise distances up to $+k_e$? Previous lower bounds are consistent with a positive resolution to this question, while previous upper bounds exhibit the beginning of a tradeoff curve: all graphs have $+2$ spanners on $O(n^{3/2})$ edges, $+4$ spanners on $\tilde{O}(n^{7/5})$ edges, and $+6$ spanners on $O(n^{4/3})$ edges. However, progress has mysteriously halted at the $n^{4/3}$ bound, and despite significant effort from the community, the question has remained open for all $0<e<1/3$. #R##N#Our main result is a surprising negative resolution of the open question, even in a highly generalized setting. We show a new information theoretic incompressibility bound: there is no mathematical function that compresses graphs into $O(n^{4/3 - e})$ bits so that distance information can be recovered within $+n^{o(1)}$ error. As a special case of our theorem, we get a tight lower bound on the sparsity of additive spanners: the $+6$ spanner on $O(n^{4/3})$ edges cannot be improved in the exponent, even if any subpolynomial amount of additive error is allowed. Our theorem implies new lower bounds for related objects as well; for example, the twenty-year-old $+4$ emulator on $O(n^{4/3})$ edges also cannot be improved in the exponent unless the error allowance is polynomial.

Includes members:
  Member "a hierarchy of lower bounds for sublinear additive spanners":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "linear size distance preservers":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "weighted additive spanners")
  Member "very sparse additive spanners and emulators":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "lower bounds on sparse spanners emulators and diameter reducing shortcuts")
  Member "better distance preservers and additive spanners":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "additive spanners a simple construction":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "weighted additive spanners")
  Member "bypassing erd h o s girth conjecture hybrid stretch and sourcewise spanners":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "efficient enumeration of subgraphs and induced subgraphs with bounded girth")
  Member "on pairwise spanners":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "weighted additive spanners")
  Member "collective additive tree spanners of bounded tree breadth graphs with generalizations and consequences":
    also connected through other hyperedges:
      (none)

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.DS(Data Structures and Algorithms)