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 "look up and adapt a one shot semantic parser"):
  Abstract: Computing devices have recently become capable of interacting with their end users via natural language. However, they can only operate within a limited "supported" domain of discourse and fail drastically when faced with an out-of-domain utterance, mainly due to the limitations of their semantic parser. In this paper, we propose a semantic parser that generalizes to out-of-domain examples by learning a general strategy for parsing an unseen utterance through adapting the logical forms of seen utterances, instead of learning to generate a logical form from scratch. Our parser maintains a memory consisting of a representative subset of the seen utterances paired with their logical forms. Given an unseen utterance, our parser works by looking up a similar utterance from the memory and adapting its logical form until it fits the unseen utterance. Moreover, we present a data generation strategy for constructing utterance-logical form pairs from different domains. Our results show an improvement of up to 68.8% on one-shot parsing under two different evaluation settings compared to the baselines.

Includes members:
  Member "seq2sql generating structured queries from natural language using reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scalable neural methods for reasoning with a symbolic knowledge base")
  Member "zero shot transfer learning for semantic parsing":
    also connected through other hyperedges:
      (none)
  Member "decoupling structure and lexicon for zero shot semantic parsing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning semantic parsers from denotations with latent structured alignments and abstract programs")
  Member "generating sentences by editing prototypes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sequential latent knowledge selection for knowledge grounded dialogue")
  Member "towards zero shot frame semantic parsing for domain scaling":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "zero resource cross domain named entity recognition")
  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 "cross domain semantic parsing via paraphrasing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "paraphrase generation with latent bag of words")
  Member "language to logical form with neural attention":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "unsupervised question decomposition for question answering")

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)