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 "continual adaptation for efficient machine communication"):
  Abstract: To communicate with new partners in new contexts, humans rapidly form new linguistic conventions. Recent language models trained with deep neural networks are able to comprehend and produce the existing conventions present in their training data, but are not able to flexibly and interactively adapt those conventions on the fly as humans do. We introduce a repeated reference task as a benchmark for models of adaptation in communication and propose a regularized continual learning framework that allows an artificial agent initialized with a generic language model to more accurately and efficiently communicate with a partner over time. We evaluate this framework through simulations on COCO and in real-time reference game experiments with human partners.

Includes members:
  Member "a neural model of adaptation in reading":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "using priming to uncover the organization of syntactic representations in neural language models")
  Member "recasting gradient based meta learning as hierarchical bayes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "is the meta learning idea able to improve the generalization of deep neural networks on the standard supervised learning")
  Member "personalized language model for query auto completion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "clara clinical report auto completion")
  Member "online gradient based mixtures for transfer modulation in meta learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi step model agnostic meta learning convergence and improved algorithms")
  Member "deep online learning via meta learning continual adaptation for model based rl":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a neural dirichlet process mixture model for task free continual learning")
  Member "context aware captions from context agnostic supervision":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "adversarially guided self play for adopting social conventions")
  Member "colors in context a pragmatic neural model for grounded language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "towards learning a generic agent for vision and language navigation via pre training")
  Member "low rank rnn adaptation for context aware language modeling":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "c textgen conditional text generation for harmonious human machine interaction")

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)