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 "improving knowledge aware dialogue generation via knowledge base question answering"):
  Abstract: Neural network models usually suffer from the challenge of incorporating commonsense knowledge into the open-domain dialogue systems. In this paper, we propose a novel knowledge-aware dialogue generation model (called TransDG), which transfers question representation and knowledge matching abilities from knowledge base question answering (KBQA) task to facilitate the utterance understanding and factual knowledge selection for dialogue generation. In addition, we propose a response guiding attention and a multi-step decoding strategy to steer our model to focus on relevant features for response generation. Experiments on two benchmark datasets demonstrate that our model has robust superiority over compared methods in generating informative and fluent dialogues. Our code is available at https://github.com/siat-nlp/TransDG.

Includes members:
  Member "learning to select knowledge for response generation in dialog systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "low resource knowledge grounded dialogue generation")
  Member "response generation by context aware prototype editing":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "relevance promoting language model for short text conversation")
  Member "a knowledge grounded neural conversation model":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "non autoregressive neural dialogue generation")
  Member "improved neural relation detection for knowledge base question answering":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "neural relation prediction for simple question answering over knowledge graph")
  Member "flexible end to end dialogue system for knowledge grounded conversation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "improving neural conversational models with entropy based data filtering")
  Member "deep reinforcement learning for dialogue generation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "generative adversarial networks in computer vision a survey and taxonomy")
  Member "incorporating copying mechanism in sequence to sequence learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "question answering on freebase via relation extraction and textual evidence":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "realistic re evaluation of knowledge graph completion methods an experimental study")

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)