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 "assisted common information with an application to secure two party sampling"):
  Abstract: An important subclass of secure multiparty computation is secure sampling: two parties output samples of a pair of jointly distributed random variables such that neither party learns more about the other party's output than what its own output reveals. The parties make use of a setup—correlated random variables with a different distribution—as well as unlimited noiseless communication. An upperbound on the rate of producing samples of a desired distribution from a given setup is presented. The region of tension developed in this paper measures how well the dependence between a pair of random variables can be resolved by a piece of common information. The bounds on rate are a consequence of a monotonicity property; a protocol between two parties can only lower the tension between their views. Connections are drawn between the region of tension and the notion of common information. A generalization of the Gacs-Korner common information, called the assisted common information, which takes into account almost common information ignored by Gacs-Korner common information is defined. The region of tension is shown to be related to the rate regions of both the assisted common information and the Gray-Wyner systems (and,  a fortiori , Wyner's common information).

Includes members:
  Member "assisted common information further results":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the efficiency of classical and quantum secure function evaluation")
  Member "commitment capacity of discrete memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the commitment capacity of unfair noisy channels")

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)