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 "adversarial language games for advanced natural language intelligence"):
  Abstract: While adversarial games have been well studied in various board games and electronic sports games, etc., such adversarial games remain a nearly blank field in natural language processing. As natural language is inherently an interactive game, we propose a challenging pragmatics game called Adversarial Taboo, in which an attacker and a defender compete with each other through sequential natural language interactions. The attacker is tasked with inducing the defender to speak a target word invisible to the defender, while the defender is tasked with detecting the target word before being induced by the attacker. In Adversarial Taboo, a successful attacker must hide its intention and subtly induce the defender, while a competitive defender must be cautious with its utterances and infer the intention of the attacker. To instantiate the game, we create a game environment and a competition platform. Sufficient pilot experiments and empirical studies on several baseline attack and defense strategies show promising and interesting results. Based on the analysis on the game and experiments, we discuss multiple promising directions for future research.

Includes members:
  Member "emergent tool use from multi agent autocurricula":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning zero sum simultaneous move markov games using function approximation and correlated equilibrium")
  Member "better automatic evaluation of open domain dialogue systems with contextualized embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards a human like open domain chatbot")
  Member "on evaluation of adversarial perturbations for sequence to sequence models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "adv bert bert is not robust on misspellings generating nature adversarial samples on bert")
  Member "universal adversarial triggers for attacking and analyzing nlp":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey on contextual embeddings")
  Member "egg a toolkit for research on emergence of language in games":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "towards graph representation learning in emergent communication")
  Member "robust neural machine translation with doubly adversarial inputs":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "freelb enhanced adversarial training for natural language understanding")
  Member "adversarial attacks on deep learning models in natural language processing a survey":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gradient based adversarial attacks on categorical sequence models via traversing an embedded world")
  Member "robust machine comprehension models via adversarial training":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a framework for evaluation of machine reading comprehension gold standards")

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)