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: "average radius list recovery of random linear codes it really ties the room together"
  Abstract: We analyze the list-decodability, and related notions, of random linear codes. This has been studied extensively before: there are many different parameter regimes and many different variants. Previous works have used complementary styles of arguments---which each work in their own parameter regimes but not in others---and moreover have left some gaps in our understanding of the list-decodability of random linear codes. In particular, none of these arguments work well for list-recovery, a generalization of list-decoding that has been useful in a variety of settings. #R##N#In this work, we present a new approach, which works across parameter regimes and further generalizes to list-recovery. Our main theorem can establish better list-decoding and list-recovery results for low-rate random linear codes over large fields; list-recovery of high-rate random linear codes; and it can recover the rate bounds of Guruswami, Hastad, and Kopparty for constant-rate random linear codes (although with large list sizes).

Connected through hyperedge HE-1 (induced by source paper "improved decoding of folded reed solomon and multiplicity codes"):
  with members:
    - "linear time list recovery of high rate expander codes"
    - "high rate locally correctable and locally testable codes with sub polynomial query complexity"
    - "list decoding algorithms for lifted codes"
    - "folded codes from function field towers and improved optimal rate list decoding"
    - "subspace evasive sets"
    - "explicit codes achieving list decoding capacity error correction with optimal redundancy"

Connected through hyperedge HE-2 (induced by source paper "on the list decodability of random linear rank metric codes"):
  with members:
    - "some gabidulin codes cannot be list decoded efficiently at any radius"
    - "every list decodable code for high noise has abundant near optimal rate puncturings"
    - "on the list decodability of random linear codes with large error rates"
    - "bounds on list decoding gabidulin codes"
    - "on identity testing of tensors low rank recovery and compressed sensing"
    - "restricted isometry of fourier matrices and list decodability of random linear codes"
    - "on the list decodability of random linear codes"
    - "a rank metric approach to error control in random network coding"

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)