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 "new algorithms for maximum disjoint paths based on tree likeness"):
  Abstract: We study the classical NP-hard problems of finding maximum-size subsets from given sets of $k$ terminal pairs that can be routed via edge-disjoint paths (MaxEDP) or node-disjoint paths (MaxNDP) in a given graph. The approximability of MaxEDP/NDP is currently not well understood; the best known lower bound is $\Omega(\log^{1/2-\epsilon}{n})$, assuming NP$~\not\subseteq~$ZPTIME$(n^{\mathrm{poly}\log n})$. This constitutes a significant gap to the best known approximation upper bound of $O(\sqrt{n})$ due to Chekuri et al. (2006) and closing this gap is currently one of the big open problems in approximation algorithms. In their seminal paper, Raghavan and Thompson (Combinatorica, 1987) introduce the technique of randomized rounding for LPs; their technique gives an $O(1)$-approximation when edges (or nodes) may be used by $O(\frac{\log n}{\log\log n})$ paths. #R##N#In this paper, we strengthen the above fundamental results. We provide new bounds formulated in terms of the feedback vertex set number $r$ of a graph, which measures its vertex deletion distance to a forest. In particular, we obtain the following. #R##N#* For MaxEDP, we give an $O(\sqrt{r}\cdot \log^{1.5}{kr})$-approximation algorithm. As $r\leq n$, up to logarithmic factors, our result strengthens the best known ratio $O(\sqrt{n})$ due to Chekuri et al. #R##N#* Further, we show how to route $\Omega(\mathrm{OPT})$ pairs with congestion $O(\frac{\log{kr}}{\log\log{kr}})$, strengthening the bound obtained by the classic approach of Raghavan and Thompson. #R##N#* For MaxNDP, we give an algorithm that gives the optimal answer in time $(k+r)^{O(r)}\cdot n$. If $r$ is at most triple-exponential in $k$, this improves the best known algorithm for MaxNDP with parameter $k$, by Kawarabayashi and Wollan (STOC 2010). #R##N#We complement these positive results by proving that MaxEDP is NP-hard even for $r=1$, and MaxNDP is W$[1]$-hard for parameter $r$.

Includes members:
  Member "new hardness results for routing on disjoint paths":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an approximation algorithm for fully planar edge disjoint paths")
  Member "improved approximation for node disjoint paths in planar graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "an approximation algorithm for fully planar edge disjoint paths")
  Member "on routing disjoint paths in bounded treewidth graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the power of cut based parameters for computing edge disjoint paths")
  Member "maximum edge disjoint paths in k sums of graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "improved bounds for the excluded grid theorem")
  Member "a polylogarithimic approximation algorithm for edge disjoint paths with congestion 2":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "packing directed circuits quarter integrally")
  Member "routing in undirected graphs with constant congestion":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "an approximation algorithm for fully planar edge disjoint paths")
  Member "flow cut gaps for integer and fractional multiflows":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "network coding gaps for completion times of multiple unicasts")

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.DS(Data Structures and Algorithms)