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 "weighted additive spanners"):
  Abstract: A \emph{spanner} of a graph $G$ is a subgraph $H$ that approximately preserves shortest path distances in $G$. Spanners are commonly applied to compress computation on metric spaces corresponding to weighted input graphs. Classic spanner constructions can seamlessly handle edge weights, so long as error is measured \emph{multiplicatively}. In this work, we investigate whether one can similarly extend constructions of spanners with purely \emph{additive} error to weighted graphs. These extensions are not immediate, due to a key lemma about the size of shortest path neighborhoods that fails for weighted graphs. Despite this, we recover a suitable amortized version, which lets us prove direct extensions of classic $+2$ and $+4$ unweighted spanners (both all-pairs and pairwise) to $+2W$ and $+4W$ weighted spanners, where $W$ is the maximum edge weight. For a technical reason, the $+6$ unweighted spanner becomes a $+8W$ weighted spanner; closing this error gap is an interesting remaining open problem.

Includes members:
  Member "some general structure for extremal sparsification problems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "graph spanners a tutorial review")
  Member "almost shortest paths and pram distance oracles in weighted graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "shortest path centrality and the all pairs shortest paths problem via vc dimension theory")
  Member "lower bounds on sparse spanners emulators and diameter reducing shortcuts":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "graph spanners a tutorial review")
  Member "a hierarchy of lower bounds for sublinear additive spanners":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exponentially faster shortest paths in the congested clique")
  Member "linear size distance preservers":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "some general structure for extremal sparsification problems")
  Member "better distance preservers and additive spanners":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "the 4 3 additive spanner exponent is tight":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "graph spanners a tutorial review")
  Member "additive spanners a simple construction":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "some general structure for extremal sparsification problems")

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.DM(Discrete Mathematics)