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 "learning autocomplete systems as a communication game"):
  Abstract: We study textual autocomplete---the task of predicting a full sentence from a partial sentence---as a human-machine communication game. Specifically, we consider three competing goals for effective communication: use as few tokens as possible (efficiency), transmit sentences faithfully (accuracy), and be learnable to humans (interpretability). We propose an unsupervised approach which tackles all three desiderata by constraining the communication scheme to keywords extracted from a source sentence for interpretability and optimizing the efficiency-accuracy tradeoff. Our experiments show that this approach results in an autocomplete system that is 52% more accurate at a given efficiency level compared to baselines, is robust to user variations, and saves time by nearly 50% compared to typing full sentences.

Includes members:
  Member "pythia ai assisted code completion system":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "core automating review recommendation for code changes")
  Member "seq 3 differentiable sequence to sequence to sequence autoencoder for unsupervised abstractive sentence compression":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "summae zero shot abstractive text summarization using length agnostic auto encoders")
  Member "learning deep hidden nonlinear dynamics from aggregate data":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning stochastic behaviour of aggregate data")
  Member "unsupervised sentence compression using denoising auto encoders":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "ted a pretrained unsupervised summarization model with theme modeling and denoising")
  Member "planning inference and pragmatics in sequential language games":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "emergence of pragmatics from referential game between theory of mind agents")
  Member "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "generating sentences by editing prototypes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sequential latent knowledge selection for knowledge grounded dialogue")
  Member "learning cooperative visual dialog agents with deep reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "grad cam visual explanations from deep networks via gradient based localization")

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)