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 robustness of neural dialog systems in a data efficient way with turn dropout"):
  Abstract: Neural network-based dialog models often lack robustness to anomalous, out-of-domain (OOD) user input which leads to unexpected dialog behavior and thus considerably limits such models' usage in mission-critical production environments. The problem is especially relevant in the setting of dialog system bootstrapping with limited training data and no access to OOD examples. In this paper, we explore the problem of robustness of such systems to anomalous input and the associated to it trade-off in accuracies on seen and unseen data. We present a new dataset for studying the robustness of dialog systems to OOD input, which is bAbI Dialog Task 6 augmented with OOD content in a controlled way. We then present turn dropout, a simple yet efficient negative sampling-based technique for improving robustness of neural dialog models. We demonstrate its effectiveness applied to Hybrid Code Network-family models (HCNs) which reach state-of-the-art results on our OOD-augmented dataset as well as the original one. Specifically, an HCN trained with turn dropout achieves state-of-the-art performance of more than 75% per-utterance accuracy on the augmented dataset's OOD turns and 74% F1-score as an OOD detector. Furthermore, we introduce a Variational HCN enhanced with turn dropout which achieves more than 56.5% accuracy on the original bAbI Task 6 dataset, thus outperforming the initially reported HCN's result.

Includes members:
  Member "challenging neural dialogue models with natural data memory networks fail on incremental phenomena":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "hybrid generative retrieval transformers for dialogue domain adaptation")
  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 "toward continual learning for conversational agents":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "transferable multi domain state generator for task oriented dialogue systems")
  Member "frames a corpus for adding memory to goal oriented dialogue systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "hybrid code networks practical and efficient end to end dialog control with supervised and reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "neural sentence embedding using only in domain sentences for out of domain sentence detection in dialog systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "out of domain detection for natural language understanding in dialog systems")
  Member "learning discourse level diversity for neural dialog models using conditional variational autoencoders":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "non autoregressive neural dialogue generation")
  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)