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 "polyglot semantic parsing in apis"):
  Abstract: Traditional approaches to semantic parsing (SP) work by training individual models for each available parallel dataset of text-meaning pairs. In this paper, we explore the idea of polyglot semantic translation, or learning semantic parsing models that are trained on multiple datasets and natural languages. In particular, we focus on translating text to code signature representations using the software component datasets of Richardson and Kuhn (2017a,b). The advantage of such models is that they can be used for parsing a wide variety of input natural languages and output programming languages, or mixed input languages, using a single unified model. To facilitate modeling of this type, we develop a novel graph-based decoding framework that achieves state-of-the-art performance on the above datasets, and apply this method to two other benchmark SP tasks.

Includes members:
  Member "a language for function signature representations":
    also connected through other hyperedges:
      (none)
  Member "the code2text challenge text generation in source libraries":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a neural model for generating natural language summaries of program subroutines")
  Member "a parallel corpus of python functions and documentation strings for automated code documentation and code generation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "trans 3 a transformer based framework for unifying code summarization and code search")
  Member "neural machine translation for low resource languages":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "revisiting low resource neural machine translation a case study")
  Member "a survey of machine learning for big code and naturalness":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the convergence of artificial intelligence and distributed ledger technology a scoping review and future research agenda")
  Member "neural semantic parsing over multiple knowledge bases":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "semantic parsing with dual learning")
  Member "addressing the data sparsity issue in neural amr parsing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "amr parsing as sequence to graph transduction")
  Member "function assistant a tool for nl querying of apis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a language for function signature representations")

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)