human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "a counter example to the mismatched decoding converse for binary input discrete memoryless channels"
  Abstract: This paper studies the mismatched decoding problem for binary-input discrete memoryless channels. An example is provided for which an achievable rate based on superposition coding exceeds the LM rate (Hui, 1983; Csisz\'ar-K\"orner, 1981), thus providing a counter-example to a previously reported converse result (Balakirsky, 1995). Both numerical evaluations and theoretical results are used in establishing this claim.

Connected through hyperedge HE-1 (induced by source paper "channel capacity of polar coding with a given polar mismatched successive cancellation decoder"):
  with members:
    - "a simple proof of fast polarization"
    - "on the scaling exponent of polar codes for binary input energy harvesting channels"
    - "a split reduced successive cancellation list decoder for polar codes"
    - "a low latency list successive cancellation decoding implementation for polar codes"
    - "a high throughput list decoder architecture for polar codes"
    - "fast list decoders for polar codes"
    - "symbol decision successive cancellation list decoder for polar codes"
    - "polar coding for processes with memory"

Connected through hyperedge HE-2 (induced by source paper "multiuser random coding techniques for mismatched decoding"):
  with members:
    - "on the reliability function of the discrete memoryless relay channel"
    - "expurgated random coding ensembles exponents refinements and connections"
    - "mismatched decoding error exponents second order rates and saddlepoint approximations"
    - "error exponent for multiple access channels lower bounds"

Question: Please tell me which class the center node 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)