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 "communication for generating correlation a unifying survey"):
  Abstract: The task of manipulating correlated random variables in a distributed setting has received attention in the fields of both Information Theory and Computer Science. Often shared correlations can be converted, using a little amount of communication, into perfectly shared uniform random variables. Such perfect shared randomness, in turn, enables the solutions of many tasks. Even the reverse conversion of perfectly shared uniform randomness into variables with a desired form of correlation turns out to be insightful and technically useful. In this survey article, we describe progress-to-date on such problems and lay out pertinent measures, achievability results, limits of performance, and point to new directions.

Includes members:
  Member "secret key capacity for multipleaccess channel with public feedback":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "communication for generating correlation a survey")
  Member "exact exponent for soft covering":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a correlation measure based on vector valued l_p norms")
  Member "exact channel synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "communication for generating correlation a survey")
  Member "strong converse using change of measure arguments":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "communication for generating correlation a survey")
  Member "coding for positive rate in the source model key agreement problem":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "biometric and physical identifiers with correlated noise for controllable private authentication")
  Member "wiretap channels nonasymptotic fundamental limits":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "resource allocation for secure multi user downlink miso urllc systems")
  Member "channel resolvability theorems for general sources and channels":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "communication for generating correlation a survey")
  Member "strong functional representation lemma and applications to coding theorems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "sharp bounds for mutual covering")

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)