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: "partial sums computation in polar codes decoding"
  Abstract: Polar codes are the first error-correcting codes to provably achieve the channel capacity but with infinite codelengths. For finite codelengths the existing decoder architectures are limited in working frequency by the partial sums computation unit. We explain in this paper how the partial sums computation can be seen as a matrix multiplication. Then, an efficient hardware implementation of this product is investigated. It has reduced logic resources and interconnections. Formalized architectures, to compute partial sums and to generate the bits of the generator matrix k^n, are presented. The proposed architecture allows removing the multiplexing resources used to assigned to each processing elements the required partial sums.

Connected through hyperedge HE-1 (induced by source paper "towards practical software stack decoding of polar codes"):
  with members:
    - "fast sequential decoding of polar codes"
    - "fast list decoders for polar codes"
    - "flexible and low complexity encoding and decoding of systematic polar codes"
    - "llr based successive cancellation list decoding of polar codes"
    - "fast polar decoders algorithm and implementation"
    - "improved successive cancellation decoding of polar codes"
    - "list decoding of polar codes"
    - "hardware architectures for successive cancellation decoding of polar codes"

Connected through hyperedge HE-2 (induced by source paper "recursive descriptions of polar codes"):
  with members:
    - "soft decision decoding of reed muller codes recursive lists"
    - "on metric sorting for successive cancellation list decoding of 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"
    - "binary polarization kernels from code decompositions"
    - "a scalable successive cancellation decoder for 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.AR(Hardware Architecture)