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 the dispersions of the gel fand pinsker channel and dirty paper coding"):
  Abstract: This paper studies second-order coding rates for memoryless channels with a state sequence known non-causally at the encoder. In the case of finite alphabets, an achievability result is obtained using constant-composition random coding, and by using a small fraction of the block to transmit the type of the state sequence. For error probabilities less than 1/2, it is shown that the second-order rate improves on an existing one based on i.i.d. random coding. In the Gaussian case (dirty paper coding) with an almost-sure power constraint, an achievability result is obtained used using random coding over the surface of a sphere, and using a small fraction of the block to transmit a quantized description of the state power. It is shown that the second-order asymptotics are identical to the single-user Gaussian channel of the same input power without a state.

Includes members:
  Member "second order asymptotics for the gaussian mac with degraded message sets":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "second order region for gray wyner network")
  Member "second order coding rates for channels with state":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "second order and moderate deviation analysis of a block fading channel with deterministic and energy harvesting power constraints")
  Member "on the dispersions of three network information theory problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "gaussian multiple and random access in the finite blocklength regime")
  Member "a technique for deriving one shot achievability results in network information theory":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exponential strong converse for successive refinement with causal decoder side information")
  Member "non asymptotic output statistics of random binning and its applications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "physical layer security in the finite blocklength regime over fading channels")
  Member "second order rate region of constant composition codes for the multiple access channel":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "gaussian multiple and random access in the finite blocklength regime")
  Member "non asymptotic and second order achievability bounds for coding with side information":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "second order asymptotics for the gaussian mac with degraded message sets")
  Member "a finite blocklength perspective on gaussian multi access channels":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a proof of the strong converse theorem for gaussian multiple access 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)