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: "low latency software polar decoders"
  Abstract: The low-complexity encoding and decoding algorithms render polar codes attractive for use in SDR applications where computational resources are limited. In this chapter, we present low-latency software polar decoders that exploit modern processor capabilities. We show how adapting the algorithm at various levels can lead to significant improvements in latency and throughput , yielding polar decoders that are suitable for high-performance SDR applications on modern desktop processors and embedded-platform processors . These proposed decoders have an order of magnitude lower latency and memory footprint compared to state-of-the-art decoders, while maintaining comparable throughput . In addition, we present strategies and results for implementing polar decoders on graphical processing units . Finally, we show that the energy efficiency of the proposed decoders is comparable to state-of-the-art software polar decoders.

Connected through hyperedge HE-1 (induced by source paper "fast and flexible software polar list decoders"):
  with members:
    - "fast list decoders for polar codes"
    - "llr based successive cancellation list decoding of polar codes"
    - "fast polar decoders algorithm and implementation"
    - "increasing the speed of polar list decoders"
    - "a reduced latency list decoding algorithm for polar codes"
    - "list decoding of polar codes"
    - "an adaptive successive cancellation list decoder for polar codes with cyclic redundancy check"
    - "how to construct polar codes"

Connected through hyperedge HE-2 (induced by source paper "fast list decoders for polar codes"):
  with members:
    - "soft decision decoding of reed muller codes recursive lists"
    - "symbol decision successive cancellation list decoder for polar codes"
    - "flexible and low complexity encoding and decoding of systematic polar codes"
    - "llr based successive cancellation list decoding of polar codes"
    - "low latency list decoding of polar codes with double thresholding"
    - "fast polar decoders algorithm and implementation"
    - "increasing the speed of polar list decoders"
    - "an efficient list decoder architecture for polar codes"

Connected through hyperedge HE-3 (induced by source paper "flexible and low complexity encoding and decoding of systematic polar codes"):
  with members:
    - "on the error performance of systematic polar codes"
    - "fast polar decoders algorithm and implementation"
    - "from polar to reed muller codes a technique to improve the finite length performance"
    - "compound polar codes"
    - "how to construct polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "polar codes characterization of exponent bounds and constructions"

Connected through hyperedge HE-4 (induced by source paper "combining belief propagation and successive cancellation list decoding of polar codes on a gpu platform"):
  with members:
    - "a decision aided parallel sc list decoder for polar codes"
    - "algorithm and architecture for hybrid decoding of polar codes"
    - "list decoding of polar codes"
    - "an adaptive successive cancellation list decoder for polar codes with cyclic redundancy check"
    - "how to construct polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"

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)