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 "on taking advantage of multiple requests in error correcting codes"):
  Abstract: In most notions of locality in error correcting codes -- notably locally recoverable codes (LRCs) and locally decodable codes (LDCs) -- a decoder seeks to learn a single symbol of a message while looking at only a few symbols of the corresponding codeword. However, suppose that one wants to recover r > 1 symbols of the message. The two extremes are repeating the single-query algorithm r times (this is the intuition behind LRCs with availability, primitive multiset batch codes, and PIR codes) or simply running a global decoding algorithm to recover the whole thing. In this paper, we investigate what can happen in between these two extremes: at what value of r does repetition stop being a good idea? In order to begin to study this question we introduce robust batch codes, which seek to find r symbols of the message using m queries to the codeword, in the presence of erasures. We focus on the case where r = m, which can be seen as a generalization of the MDS property. Surprisingly, we show that for this notion of locality, repetition is optimal even up to very large values of $r = \Omega(k)$.

Includes members:
  Member "local list recovery of high rate tensor codes and applications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "linear time erasure list decoding of expander codes")
  Member "locality via partially lifted codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "pir codes with short block length")
  Member "on multi point local decoding of reed muller codes":
    also connected through other hyperedges:
      (none)
  Member "cooperative local repair in distributed storage":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "locally recoverable j affine variety codes")
  Member "high rate locally correctable and locally testable codes with sub polynomial query complexity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "complexity theory game theory and economics the barbados lectures")
  Member "repair locality with multiple erasure tolerance":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on optimal locally repairable codes and generalized sector disk codes")
  Member "locality and availability in distributed storage":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on optimal locally repairable codes and generalized sector disk codes")
  Member "codes with locality for two erasures":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "new bounds on the field size for maximally recoverable codes instantiating grid like topologies")

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.IT(Information Theory)