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 "scaffolding networks incremental learning and teaching through questioning"):
  Abstract: We introduce a new paradigm of learning for reasoning, understanding, and prediction, as well as the scaffolding network to implement this paradigm. The scaffolding network embodies an incremental learning approach that is formulated as a teacher-student network architecture to teach machines how to understand text and do reasoning. The key to our computational scaffolding approach is the interactions between the teacher and the student through sequential questioning. The student observes each sentence in the text incrementally, and it uses an attention-based neural net to discover and register the key information in relation to its current memory. Meanwhile, the teacher asks questions about the observed text, and the student network gets rewarded by correctly answering these questions. The entire network is updated continually using reinforcement learning. Our experimental results on synthetic and real datasets show that the scaffolding network not only outperforms state-of-the-art methods but also learns to do reasoning in a scalable way even with little human generated input.

Includes members:
  Member "a deep compositional framework for human like language acquisition in virtual environment":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "meta reinforcement learning with autonomous inference of subtask dependencies")
  Member "learning language games through interaction":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "spa verbal interactions between agents and avatars in shared virtual environments using propositional planning")
  Member "dialog based language learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "pseudo labeling and negative feedback learning for large scale multi label domain classification")
  Member "tracking the world state with recurrent entity networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the next decade in ai four steps towards robust artificial intelligence")
  Member "learning to compose neural networks for question answering":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "unsupervised question decomposition for question answering")
  Member "gated end to end memory networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a copy augmented sequence to sequence architecture gives good performance on task oriented dialogue")
  Member "link prediction using embedded knowledge graphs":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "language based image editing with recurrent attentive models")
  Member "learning end to end goal oriented dialog":
    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)