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 "building an application independent natural language interface"):
  Abstract: Traditional approaches to building natural language (NL) interfaces typically use a semantic parser to parse the user command and convert it to a logical form, which is then translated to an executable action in an application. However, it is still challenging for a semantic parser to correctly parse natural language. For a different domain, the parser may need to be retrained or tuned, and a new translator also needs to be written to convert the logical forms to executable actions. In this work, we propose a novel and application independent approach to building NL interfaces that does not need a semantic parser or a translator. It is based on natural language to natural language matching and learning, where the representation of each action and each user command are both in natural language. To perform a user intended action, the system only needs to match the user command with the correct action representation, and then execute the corresponding action. The system also interactively learns new (paraphrased) commands for actions to expand the action representations over time. Our experimental results show the effectiveness of the proposed approach.

Includes members:
  Member "spatialnli a spatial domain natural language interface to databases using spatial comprehension":
    also connected through other hyperedges:
      (none)
  Member "bridging the semantic gap with sql query logs in natural language interfaces to databases":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "break it down a question understanding benchmark")
  Member "seq2sql generating structured queries from natural language using reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "scalable neural methods for reasoning with a symbolic knowledge base")
  Member "transferable natural language interface to structured queries aided by adversarial generation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a sketch based system for semantic parsing")
  Member "nl2bash a corpus and semantic parser for natural language interface to the linux operating system":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "clai a platform for ai skills on the command line")
  Member "an end to end neural natural language interface for databases":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "char rnn and active learning for hashtag segmentation")
  Member "explain yourself a natural language interface for scrutable autonomous robots":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "explainable software for cyber physical systems es4cps report from the gi dagstuhl seminar 19023 january 06 11 2019 schloss dagstuhl")
  Member "mapping natural language commands to web elements":
    also connected through other hyperedges:
      (none)

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)