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 "thieves on sesame street model extraction of bert based apis"):
  Abstract: We study the problem of model extraction in natural language processing, in which an adversary with only query access to a victim model attempts to reconstruct a local copy of that model. Assuming that both the adversary and victim model fine-tune a large pretrained language model such as BERT (Devlin et al. 2019), we show that the adversary does not need any real training data to successfully mount the attack. In fact, the attacker need not even use grammatical or semantically meaningful queries: we show that random sequences of words coupled with task-specific heuristics form effective queries for model extraction on a diverse set of NLP tasks, including natural language inference and question answering. Our work thus highlights an exploit only made feasible by the shift towards transfer learning methods within the NLP community: for a query budget of a few hundred dollars, an attacker can extract a model that performs only slightly worse than the victim model. Finally, we study two defense strategies against model extraction---membership classification and API watermarking---which while successful against naive adversaries, are ineffective against more sophisticated ones.

Includes members:
  Member "boolq exploring the surprising difficulty of natural yes no questions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "natural language qa approaches using reasoning with external knowledge")
  Member "right for the wrong reasons diagnosing syntactic heuristics in natural language inference":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adversarial filters of dataset biases")
  Member "high fidelity extraction of neural network models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "entangled watermarks as a defense against model extraction")
  Member "zero shot knowledge transfer via adversarial belief matching":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "generative low bitwidth data free quantization")
  Member "learning and evaluating general linguistic intelligence":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "parameter space factorization for zero shot learning across tasks and languages")
  Member "a framework for the extraction of deep neural networks by leveraging public data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "entangled watermarks as a defense against model extraction")
  Member "membership inference attacks on sequence to sequence models":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "data and model dependencies of membership inference attack")
  Member "prediction poisoning utility constrained defenses against model stealing attacks":
    also connected through other hyperedges:
      (none)

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)