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 "sequence to sequence learning for task oriented dialogue with dialogue state representation"):
  Abstract: Classic pipeline models for task-oriented dialogue system require explicit modeling the dialogue states and hand-crafted action spaces to query a domain-specific knowledge base. Conversely, sequence-to-sequence models learn to map dialogue history to the response in current turn without explicit knowledge base querying. In this work, we propose a novel framework that leverages the advantages of classic pipeline and sequence-to-sequence models. Our framework models a dialogue state as a fixed-size distributed representation and use this representation to query a knowledge base via an attention mechanism. Experiment on Stanford Multi-turn Multi-domain Task-oriented Dialogue Dataset shows that our framework significantly outperforms other sequence-to-sequence based baseline models on both automatic and human evaluation.

Includes members:
  Member "relevance of unsupervised metrics in task oriented dialogue for evaluating natural language generation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cbag conditional biomedical abstract generation")
  Member "key value retrieval networks for task oriented dialogue":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "learning symmetric collaborative dialogue agents with dynamic knowledge graph embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "crwiz a framework for crowdsourcing real time wizard of oz dialogues")
  Member "latent intention dialogue models":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sequential latent knowledge selection for knowledge grounded dialogue")
  Member "composite task completion dialogue policy learning via hierarchical deep reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "emptransfo a multi head transformer architecture for creating empathetic dialog systems")
  Member "composite task completion dialogue policy learning via hierarchical deep reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "emptransfo a multi head transformer architecture for creating empathetic dialog systems")
  Member "hybrid code networks practical and efficient end to end dialog control with supervised and reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "a copy augmented sequence to sequence architecture gives good performance on task oriented dialogue":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "recent advances and challenges in task oriented dialog system")

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)