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 "tight hardness for shortest cycles and paths in sparse graphs"):
  Abstract: Fine-grained reductions have established equivalences between many core problems with $\tilde{O}(n^3)$-time algorithms on $n$-node weighted graphs, such as Shortest Cycle, All-Pairs Shortest Paths (APSP), Radius, Replacement Paths, Second Shortest Paths, and so on. These problems also have $\tilde{O}(mn)$-time algorithms on $m$-edge $n$-node weighted graphs, and such algorithms have wider applicability. Are these $mn$ bounds optimal when $m \ll n^2$? #R##N#Starting from the hypothesis that the minimum weight $(2\ell+1)$-Clique problem in edge weighted graphs requires $n^{2\ell+1-o(1)}$ time, we prove that for all sparsities of the form $m = \Theta(n^{1+1/\ell})$, there is no $O(n^2 + mn^{1-\epsilon})$ time algorithm for $\epsilon>0$ for \emph{any} of the below problems: #R##N#Minimum Weight $(2\ell+1)$-Cycle in a directed weighted graph, #R##N#Shortest Cycle in a directed weighted graph, #R##N#APSP in a directed or undirected weighted graph, #R##N#Radius (or Eccentricities) in a directed or undirected weighted graph, #R##N#Wiener index of a directed or undirected weighted graph, #R##N#Replacement Paths in a directed weighted graph, #R##N#Second Shortest Path in a directed weighted graph, #R##N#Betweenness Centrality of a given node in a directed weighted graph. #R##N#That is, we prove hardness for a variety of sparse graph problems from the hardness of a dense graph problem. Our results also lead to new conditional lower bounds from several related hypothesis for unweighted sparse graph problems including $k$-cycle, shortest cycle, Radius, Wiener index and APSP.

Includes members:
  Member "tree edit distance cannot be computed in strongly subcubic time unless apsp can":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "new algorithms and hardness for incremental single source shortest paths in directed graphs")
  Member "finding even cycles faster via capped k walks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "graph pattern detection hardness for all induced patterns and faster non induced cycles")
  Member "fine grained complexity and conditional hardness for sparse graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "improved distance queries and cycle counting by frobenius normal form")
  Member "polynomial representations of threshold functions and algorithmic applications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "approximating text to pattern hamming distances")
  Member "the input output complexity of triangle enumeration":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "instance and output optimal parallel algorithms for acyclic joins")
  Member "powers of tensors and fast matrix multiplication":
    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 "faster all pairs shortest paths via circuit complexity":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deterministic algorithms for decremental approximate shortest paths faster and simpler")
  Member "algorithmic applications of baur strassen s theorem shortest cycles diameter and matchings":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "dynamic approximate shortest paths and beyond subquadratic and worst case update time")

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)