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 "using a kg copy network for non goal oriented dialogues"):
  Abstract: Non-goal oriented, generative dialogue systems lack the ability to generate answers with grounded facts. A knowledge graph can be considered an abstraction of the real world consisting of well-grounded facts. This paper addresses the problem of generating well grounded responses by integrating knowledge graphs into the dialogue systems response generation process, in an end-to-end manner. A dataset for nongoal oriented dialogues is proposed in this paper in the domain of soccer, conversing on different clubs and national teams along with a knowledge graph for each of these teams. A novel neural network architecture is also proposed as a baseline on this dataset, which can integrate knowledge graphs into the response generation process, producing well articulated, knowledge grounded responses. Empirical evidence suggests that the proposed model performs better than other state-of-the-art models for knowledge graph integrated dialogue systems.

Includes members:
  Member "incorporating joint embeddings into goal oriented dialogues with multi task learning":
    also connected through other hyperedges:
      (none)
  Member "improving response selection in multi turn dialogue systems by incorporating domain knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "convert efficient and accurate conversational representations from transformers")
  Member "mem2seq effectively incorporating knowledge bases into end to end task oriented dialog systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "complex sequential question answering towards learning to converse over linked question answer pairs with a knowledge graph":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the keen universe an ecosystem for knowledge graph embeddings with a focus on reproducibility and transferability")
  Member "improving retrieval modeling using cross convolution networks and multi frequency word embedding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "improving response selection in multi turn dialogue systems by incorporating domain knowledge")
  Member "a trustworthy responsible and interpretable system to handle chit chat in conversational bots":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "qnamaker data to bot in 2 minutes")
  Member "a knowledge grounded neural conversation model":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "non autoregressive neural dialogue generation")
  Member "chat detection in an intelligent assistant combining task oriented and non task oriented spoken dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "qnamaker data to bot in 2 minutes")

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)