human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "polarization adjusted convolutional pac codes fano decoding vs list decoding"):
  Abstract: In the Shannon lecture at the 2019 International Symposium on Information Theory (ISIT), Arikan proposed to employ a one-to-one convolutional transform as a pre-coding step before polar transform. The resulting codes of this concatenation are called {\em polarization-adjusted convolutional (PAC) codes}. In this scheme, a pair of polar mapper and demapper as pre- and post-processing devices are deployed around a memoryless channel, which provides polarized information to an outer decoder leading to improved error correction performance of outer code. In this paper, the implementations of list decoding and Fano decoding for PAC codes are first investigated. Then, in order to reduce the complexity of sequential decoding of PAC/polar codes, we propose (i) an adaptive heuristic metric, (ii) tree search constraints for backtracking to avoid exploration of unlikely sub-paths, and (iii) tree search strategies consistent with the pattern of error occurrence in polar codes. These contribute to reducing the average decoding time complexity up to 85\%, with only a relatively small degradation in error correction performance. Additionally, as an important ingredient in Fano decoding of PAC/polar codes, an efficient computation method for the intermediate LLRs and partial sums is provided. This method is necessary for backtracking and avoids storing the intermediate information or restarting the decoding process.

Includes members:
  Member "on pre transformed polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a soft cancellation decoder for parity check polar codes")
  Member "from sequential decoding to channel polarization and back again":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a soft cancellation decoder for parity check polar codes")
  Member "parity check polar coding for 5g and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a soft cancellation decoder for parity check polar codes")
  Member "a randomized construction of polar subcodes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on distance properties of convolutional polar codes")
  Member "llr based successive cancellation list decoding of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "on the origin of polar coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "capacity achieving guessing random additive noise decoding")
  Member "a rm polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "decoder tailored polar code design using the genetic algorithm")
  Member "a low complexity improved successive cancellation decoder for polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "shifted pruning for list decoding of polar codes")

Question: Please tell me which class the source paper 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)