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 "knowledge aware conversational semantic parsing over web tables"):
  Abstract: Conversational semantic parsing over tables requires knowledge acquiring and reasoning abilities, which have not been well explored by current state-of-the-art approaches. Motivated by this fact, we propose a knowledge-aware semantic parser to improve parsing performance by integrating various types of knowledge. In this paper, we consider three types of knowledge, including grammar knowledge, expert knowledge, and external resource knowledge. First, grammar knowledge empowers the model to effectively replicate previously generated logical form, which effectively handles the co-reference and ellipsis phenomena in conversation Second, based on expert knowledge, we propose a decomposable model, which is more controllable compared with traditional end-to-end models that put all the burdens of learning on trial-and-error in an end-to-end way. Third, external resource knowledge, i.e., provided by a pre-trained language model or an entity typing model, is used to improve the representation of question and table for a better semantic understanding. We conduct experiments on the SequentialQA dataset. Results show that our knowledge-aware model outperforms the state-of-the-art approaches. Incremental experimental results also prove the usefulness of various knowledge. Further analysis shows that our approach has the ability to derive the meaning representation of a context-dependent utterance by leveraging previously generated outcomes.

Includes members:
  Member "learning to map context dependent sentences to executable formal queries":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "how far are we from effective context modeling an exploratory study on semantic parsing in context")
  Member "sqlnet generating structured queries from natural language without reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "schema2qa answering complex queries on the structured web with a neural model")
  Member "situated mapping of sequential instructions to actions with single step reward observation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "editing based sql query generation for cross domain context dependent questions")
  Member "deep contextualized word representations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "memory augmented policy optimization for program synthesis and semantic parsing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "automl zero evolving machine learning algorithms from scratch")
  Member "structvae tree structured latent variable models for semi supervised semantic parsing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a probabilistic formulation of unsupervised text style transfer")
  Member "it was the training data pruning too":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning to generalize from sparse and underspecified rewards")
  Member "from language to programs bridging reinforcement learning and maximum marginal likelihood":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "why build an assistant in minecraft")

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)