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 "zero shot cross lingual dialogue systems with transferable latent variables"):
  Abstract: Despite the surging demands for multilingual task-oriented dialog systems (e.g., Alexa, Google Home), there has been less research done in multilingual or cross-lingual scenarios. Hence, we propose a zero-shot adaptation of task-oriented dialogue system to low-resource languages. To tackle this challenge, we first use a set of very few parallel word pairs to refine the aligned cross-lingual word-level representations. We then employ a latent variable model to cope with the variance of similar sentences across different languages, which is induced by imperfect cross-lingual alignments and inherent differences in languages. Finally, the experimental results show that even though we utilize much less external resources, our model achieves better adaptation performance for natural language understanding task (i.e., the intent detection and slot filling) compared to the current state-of-the-art model in the zero-shot scenario.

Includes members:
  Member "incorporating word and subword units in unsupervised machine translation using language model rescoring":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "zero resource cross domain named entity recognition")
  Member "loss in translation learning bilingual word mapping with a retrieval criterion":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "effective cross lingual transfer of neural machine translation models without shared vocabularies")
  Member "universal neural machine translation for extremely low resource languages":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a brief survey of multilingual neural machine translation")
  Member "unsupervised discrete sentence representation learning for interpretable neural dialog generation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "toward interpretability of dual encoder models for dialogue response suggestions")
  Member "xl nbt a cross lingual neural belief tracking framework":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "xpersona evaluating multilingual personalized chatbot")
  Member "emo2vec learning generalized emotion representation by multi task training":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning to memorize in neural task oriented dialogue systems")
  Member "cross lingual transfer learning for multilingual task oriented dialog":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "latent intention dialogue models":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "sequential latent knowledge selection for knowledge grounded dialogue")

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)