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: "universal polar codes"
  Abstract: Polar codes, invented by Arikan in 2009, are known to achieve the capacity of any binary-input memoryless output-symmetric channel. One of the few drawbacks of the original polar code construction is that it is not universal. This means that the code has to be tailored to the channel if we want to transmit close to capacity. #R##N#We present two "polar-like" schemes which are capable of achieving the compound capacity of the whole class of binary-input memoryless output-symmetric channels with low complexity. #R##N#Roughly speaking, for the first scheme we stack up $N$ polar blocks of length $N$ on top of each other but shift them with respect to each other so that they form a "staircase." Coding then across the columns of this staircase with a standard Reed-Solomon code, we can achieve the compound capacity using a standard successive decoder to process the rows (the polar codes) and in addition a standard Reed-Solomon erasure decoder to process the columns. Compared to standard polar codes this scheme has essentially the same complexity per bit but a block length which is larger by a factor $O(N \log_2(N)/\epsilon)$, where $\epsilon$ is the gap to capacity. #R##N#For the second scheme we first show how to construct a true polar code which achieves the compound capacity for a finite number of channels. We achieve this by introducing special "polarization" steps which "align" the good indices for the various channels. We then show how to exploit the compactness of the space of binary-input memoryless output-symmetric channels to reduce the compound capacity problem for this class to a compound capacity problem for a finite set of channels. This scheme is similar in spirit to standard polar codes, but the price for universality is a considerably larger blocklength. #R##N#We close with what we consider to be some interesting open problems.

Connected through hyperedge HE-1 (induced by source paper "polar codes and their quantum domain counterparts"):
  with members:
    - "reinforcement learning for nested polar code construction"
    - "decoder tailored polar code design using the genetic algorithm"
    - "genetic algorithm based polar code construction for the awgn channel"
    - "improved bit flipping algorithm for successive cancellation decoding of polar codes"
    - "design of polar codes in 5g new radio"
    - "belief propagation decoding of polar codes on permuted factor graphs"
    - "improved successive cancellation flip decoding of polar codes based on error distribution"
    - "belief propagation list decoding of polar codes"

Connected through hyperedge HE-2 (induced by source paper "explicit codes for the wiretap channel a unified design framework"):
  with members:
    - "a new wiretap channel model and its strong secrecy capacity"
    - "empirical and strong coordination via soft covering with polar codes"
    - "coding schemes for achieving strong secrecy at negligible cost"
    - "semantic security capacity for wiretap channels of type ii"
    - "achieving secrecy capacity of the wiretap channel and broadcast channel with a confidential component"
    - "polar coding for the broadcast channel with confidential messages a random binning analogy"
    - "how to achieve the capacity of asymmetric channels"
    - "an information theoretic approach to secret sharing"

Connected through hyperedge HE-3 (induced by source paper "list decoding of universal polar codes"):
  with members:
    - "polar codes for the deletion channel weak and strong polarization"
    - "universal polarization for processes with memory"
    - "performance bounds of concatenated polar coding schemes"
    - "soft decision decoding of reed muller codes recursive lists"
    - "fast polarization for processes with memory"
    - "polar coding for processes with memory"
    - "joint successive cancellation decoding of polar codes over intersymbol interference channels"
    - "polar codes with dynamic frozen symbols and their decoding by directed search"

Connected through hyperedge HE-4 (induced by source paper "capacity approaching polar codes with long codewords and successive cancellation decoding based on improved gaussian approximation"):
  with members:
    - "decoder tailored polar code design using the genetic algorithm"
    - "a comparative study of polar code constructions for the awgn channel"
    - "does gaussian approximation work well for the long length polar code construction"
    - "list decoding of polar codes"
    - "on finite length performance of polar codes stopping sets error floor and concatenated design"
    - "how to construct polar codes"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "the compound capacity of polar codes"

Connected through hyperedge HE-5 (induced by source paper "polar coding for common message only wiretap broadcast channel"):
  with members:
    - "achieving secrecy capacity of the wiretap channel and broadcast channel with a confidential component"
    - "polar coding for the broadcast channel with confidential messages a random binning analogy"
    - "efficient one way secret key agreement and private channel coding via polarization"
    - "achieving the secrecy capacity of wiretap channels using polar codes"
    - "polar codes are optimal for lossy source coding"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "on the role of mmse estimation in approaching the information theoretic limits of linear gaussian channels shannon meets wiener"

Connected through hyperedge HE-6 (induced by source paper "on polar coding for binary dirty paper"):
  with members:
    - "finite length scaling for polar codes"
    - "improved bounds on the finite length scaling of polar codes"
    - "list decoding of polar codes"
    - "polar write once memory codes"
    - "fixed length lossy compression in the finite blocklength regime"
    - "polar codes are optimal for lossy source coding"

Connected through hyperedge HE-7 (induced by source paper "channel coding at low capacity"):
  with members:
    - "polar codes with a stepped boundary"
    - "recursive list decoding for reed muller codes"
    - "beta beta bounds finite blocklength analog of the golden formula"
    - "relaxed polar codes"
    - "achieving the uniform rate region of general multiple access channels by polar coding"
    - "coding in the finite blocklength regime bounds based on laplace integrals and their asymptotic approximations"
    - "polar codes for broadcast channels"
    - "asymptotic estimates in information theory with non vanishing error probabilities"

Connected through hyperedge HE-8 (induced by source paper "strong coordination of signals and actions over noisy channels with two sided state information"):
  with members:
    - "persuasion with limited communication capacity"
    - "strong coordination of signals and actions over noisy channels"
    - "information design for strategic coordination of autonomous devices with non aligned utilities"
    - "joint coordination channel coding for strong coordination over noisy channels based on polar codes"
    - "empirical and strong coordination via soft covering with polar codes"
    - "polar coding for empirical coordination of signals and actions over noisy channels"
    - "secure cascade channel synthesis"
    - "polar coding for the broadcast channel with confidential messages a random binning analogy"

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)