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 "conversational ai the science behind the alexa prize"):
  Abstract: Conversational agents are exploding in popularity. However, much work remains in the area of social conversation as well as free-form conversation over a broad range of domains and topics. To advance the state of the art in conversational AI, Amazon launched the Alexa Prize, a 2.5-million-dollar university competition where sixteen selected university teams were challenged to build conversational agents, known as socialbots, to converse coherently and engagingly with humans on popular topics such as Sports, Politics, Entertainment, Fashion and Technology for 20 minutes. The Alexa Prize offers the academic community a unique opportunity to perform research with a live system used by millions of users. The competition provided university teams with real user conversational data at scale, along with the user-provided ratings and feedback augmented with annotations by the Alexa team. This enabled teams to effectively iterate and make improvements throughout the competition while being evaluated in real-time through live user interactions. To build their socialbots, university teams combined state-of-the-art techniques with novel strategies in the areas of Natural Language Understanding, Context Modeling, Dialog Management, Response Generation, and Knowledge Acquisition. To support the efforts of participating teams, the Alexa Prize team made significant scientific and engineering investments to build and improve Conversational Speech Recognition, Topic Tracking, Dialog Evaluation, Voice User Experience, and tools for traffic management and scalability. This paper outlines the advances created by the university teams as well as the Alexa Prize team to achieve the common goal of solving the problem of Conversational AI.

Includes members:
  Member "slugbot an application of a novel and scalable open domain socialbot framework":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "beyond turing intelligent agents centered on the user")
  Member "just ask building an architecture for extensible self service spoken language understanding":
    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 "predicting causes of reformulation in intelligent assistants":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "advancing the state of the art in open domain dialog systems through the alexa prize")
  Member "opennmt open source toolkit for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "prophetnet predicting future n gram for sequence to sequence pre training")
  Member "rubystar a non task oriented mixture model dialog system":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "improving neural conversational models with entropy based data filtering")
  Member "lstm based conversation models":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a survey of natural language generation techniques with a focus on dialogue systems past present and future directions")
  Member "a hierarchical latent variable encoder decoder model for generating dialogues":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "attention over parameters for dialogue systems")
  Member "a neural network approach to context sensitive generation of conversational responses":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "non autoregressive neural dialogue generation")

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.AI(Artificial Intelligence)