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 "subspace packings"):
  Abstract: The Grassmannian ${\mathcal G}_q(n,k)$ is the set of all $k$-dimensional subspaces of the vector space $\mathbb{F}_q^n$. It is well known that codes in the Grassmannian space can be used for error-correction in random network coding. On the other hand, these codes are $q$-analogs of codes in the Johnson scheme, i.e. constant dimension codes. These codes of the Grassmannian ${\mathcal G}_q(n,k)$ also form a family of $q$-analogs of block designs and they are called \emph{subspace designs}. The application of subspace codes has motivated extensive work on the $q$-analogs of block designs.  In this paper, we examine one of the last families of $q$-analogs of block designs which was not considered before. This family called \emph{subspace packings} is the $q$-analog of packings. This family of designs was considered recently for network coding solution for a family of multicast networks called the generalized combination networks. A \emph{subspace packing} $t$-$(n,k,\lambda)^m_q$ is a set $\mathcal{S}$ of $k$-subspaces from ${\mathcal G}_q(n,k)$ such that each $t$-subspace of ${\mathcal G}_q(n,t)$ is contained in at most $\lambda$ elements of $\mathcal{S}$. The goal of this work is to consider the largest size of such subspace packings.

Includes members:
  Member "grassmannian codes with new distance measures for network coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the gap between scalar and vector solutions of generalized combination networks")
  Member "construction of subspace codes through linkage":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distance distributions of cyclic orbit codes")
  Member "vector network coding based on subspace codes outperforms scalar linear network coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "roos bound for skew cyclic codes in hamming and rank metric")
  Member "construction of large constant dimension codes with a prescribed minimum distance":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on some automorphisms of rational functions and their applications in rank metric 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)