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 "amr similarity metrics from principles"):
  Abstract: Different metrics have been proposed to compare Abstract Meaning Representation (AMR) graphs. The canonical Smatch metric (Cai and Knight, 2013) aligns variables from one graph to another and compares the matching triples. The recently released SemBleu metric (Song and Gildea, 2019) is based on the machine-translation metric Bleu (Papineni et al., 2002), increasing computational efficiency by ablating a variable-alignment step and aiming at capturing more global graph properties. #R##N#Our aims are threefold: i) we establish criteria that allow us to perform a principled comparison between metrics of symbolic meaning representations like AMR; ii) we undertake a thorough analysis of Smatch and SemBleu where we show that the latter exhibits some undesirable properties. E.g., it violates the identity of indiscernibles rule and introduces biases that are hard to control; iii) we propose a novel metric S2match that is more benevolent to only very slight meaning deviations and targets the fulfilment of all established criteria. We assess its suitability and show its advantages over Smatch and SemBleu.

Includes members:
  Member "core semantic first a top down approach for amr parsing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "broad coverage semantic parsing as transduction")
  Member "automatic accuracy prediction for amr parsing":
    also connected through other hyperedges:
      (none)
  Member "structural neural encoders for amr to text generation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "modeling global and local node contexts for text generation from knowledge graphs")
  Member "sembleu a robust metric for amr parsing evaluation":
    also connected through other hyperedges:
      (none)
  Member "amr parsing as sequence to graph transduction":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "rewarding smatch transition based amr parsing with reinforcement learning")
  Member "sema an extended semantic evaluation metric for amr":
    also connected through other hyperedges:
      (none)
  Member "amr normalization for fairer evaluation":
    also connected through other hyperedges:
      (none)
  Member "a graph to sequence model for amr to text generation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "modeling global and local node contexts for text generation from knowledge graphs")

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.CL(Computation and Language)