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: "code design for short blocks a survey"
  Abstract: The design of block codes for short information blocks (e.g., a thousand or less information bits) is an open research problem which is gaining relevance thanks to emerging applications in wireless communication networks. In this work, we review some of the most recent code constructions targeting the short block regime, and we compare then with both finite-length performance bounds and classical error correction coding schemes. We will see how it is possible to effectively approach the theoretical bounds, with different performance vs. decoding complexity trade-offs.

Connected through hyperedge HE-1 (induced by source paper "decoder tailored polar code design using the genetic algorithm"):
  with members:
    - "genetic algorithm based polar code construction for the awgn channel"
    - "design of polar codes in 5g new radio"
    - "belief propagation list decoding of polar codes"
    - "mitigating clipping effects on error floors under belief propagation decoding of polar codes"
    - "polar code construction for list decoding"
    - "comparison of polar decoders with existing low density parity check and turbo decoders"
    - "minimum distance based construction of multi kernel polar codes"
    - "improving belief propagation decoding of polar codes using scattered exit charts"

Connected through hyperedge HE-2 (induced by source paper "optimizing polar codes compatible with off the shelf ldpc decoders"):
  with members:
    - "design of polar codes in 5g new radio"
    - "belief propagation list decoding of polar codes"
    - "sparse graphs for belief propagation decoding of polar codes"
    - "fast list decoders for polar codes"
    - "flexible length polar codes through graph based augmentation"
    - "a rm polar codes"
    - "from polar to reed muller codes a technique to improve the finite length performance"
    - "polar codes with dynamic frozen symbols and their decoding by directed search"

Connected through hyperedge HE-3 (induced by source paper "efficient scheduling for the massive random access gaussian channel"):
  with members:
    - "a joint graph based coding scheme for the unsourced random access gaussian channel"
    - "a coupled compressive sensing scheme for unsourced multiple access"
    - "massive multiple access based on superposition raptor codes for cellular m2m communications"
    - "gaussian multiple access via compute and forward"
    - "massive non orthogonal multiple access for cellular iot potentials and limitations"
    - "capacity of gaussian many access channels"
    - "sign compute resolve for tree splitting random access"
    - "massive machine type communications in 5g physical and mac layer solutions"

Connected through hyperedge HE-4 (induced by source paper "shaped on off keying using polar codes"):
  with members:
    - "probabilistic parity shaping for linear codes"
    - "protograph based ldpc code design for probabilistic shaping with on off keying"
    - "polar coded pulse position modulation for the poisson channel"
    - "divergence scaling of fixed length binary output one to one distribution matching"
    - "constant composition distribution matching"
    - "how to achieve the capacity of asymmetric channels"
    - "list decoding of polar codes"
    - "how to construct polar codes"

Connected through hyperedge HE-5 (induced by source paper "segmentation discarding ordered statistic decoding for linear block codes"):
  with members:
    - "short block length codes for ultra reliable low latency communications"
    - "performance comparison of short length error correcting codes"

Connected through hyperedge HE-6 (induced by source paper "polar coding with chemical reaction networks"):
  with members:
    - "short block length codes for ultra reliable low latency communications"

Connected through hyperedge HE-7 (induced by source paper "deep learning methods for improved decoding of linear codes"):
  with members:
    - "an introduction to deep learning for the physical layer"
    - "performance bounds of concatenated polar coding schemes"
    - "scaling deep learning based decoding of polar codes via partitioning"
    - "rnn decoding of linear block codes"
    - "detection algorithms for communication systems using deep learning"
    - "neural offset min sum decoding"
    - "on deep learning based channel decoding"
    - "learning to decode linear codes using deep learning"

Connected through hyperedge HE-8 (induced by source paper "memory management in successive cancellation based decoders for multi kernel polar codes"):
  with members:
    - "a multi kernel multi code polar decoder architecture"
    - "low complexity puncturing and shortening of polar codes"
    - "minimum distance based construction of multi kernel polar codes"
    - "multi kernel construction of polar codes"
    - "binary polarization kernels from code decompositions"
    - "hardware architectures for successive cancellation decoding of polar codes"

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)