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 "language coverage and generalization in rnn based continuous sentence embeddings for interacting agents"):
  Abstract: Continuous sentence embeddings using recurrent neural networks (RNNs), where variable-length sentences are encoded into fixed-dimensional vectors, are often the main building blocks of architectures applied to language tasks such as dialogue generation. While it is known that those embeddings are able to learn some structures of language (e.g. grammar) in a purely data-driven manner, there is very little work on the objective evaluation of their ability to cover the whole language space and to generalize to sentences outside the language bias of the training data. Using a manually designed context-free grammar (CFG) to generate a large-scale dataset of sentences related to the content of realistic 3D indoor scenes, we evaluate the language coverage and generalization abilities of the most common continuous sentence embeddings based on RNNs. We also propose a new embedding method based on arithmetic coding, AriEL, that is not data-driven and that efficiently encodes in continuous space any sentence from the CFG. We find that RNN-based embeddings underfit the training data and cover only a small subset of the language defined by the CFG. They also fail to learn the underlying CFG and generalize to unbiased sentences from that same CFG. We found that AriEL provides an insightful baseline.

Includes members:
  Member "independently recurrent neural network indrnn building a longer and deeper rnn":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on 3d skeleton based action recognition using learning method")
  Member "semi parametric topological memory for navigation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ego topo environment affordances from egocentric video")
  Member "chalet cornell house agent learning environment":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning to follow directions in street view")
  Member "building generalizable agents with a realistic and rich 3d environment":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "citylearn diverse real world environments for sample efficient navigation policy learning")
  Member "active neural localization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mvp unified motion and visual self supervised learning for large scale robotic navigation")
  Member "minos multimodal indoor simulator for navigation in complex environments":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "citylearn diverse real world environments for sample efficient navigation policy learning")
  Member "home a household multimodal environment":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "why build an assistant in minecraft")
  Member "gated attention architectures for task oriented language grounding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "language as a cognitive tool to imagine goals in curiosity driven exploration")

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)