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 "information minimization in emergent languages"):
  Abstract: There is a growing interest in studying the languages emerging when neural agents are jointly trained to solve tasks that require communication through discrete messages. We investigate here the information-theoretic complexity of such languages, focusing on the most basic two-agent, one-symbol, one-exchange setup. We find that, under common training procedures, the emergent languages are subject to an information minimization pressure: The mutual information between the communicating agent's inputs and the messages is close to the minimum that still allows the task to be solved. After verifying this information minimization property, we perform experiments showing that a stronger discrete-channel-driven information minimization pressure leads to increased robustness to overfitting and to adversarial attacks. We conclude by discussing the implications of our findings for the studies of artificial and natural language emergence, and for representation learning.

Includes members:
  Member "compositional obverter communication learning from raw visual input":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "emergent communication with world models")
  Member "the conditional entropy bottleneck":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "intelligence physics and information the tradeoff between accuracy and simplicity in machine learning")
  Member "how agents see things on visual representations in an emergent language game":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "towards graph representation learning in emergent communication")
  Member "emergence of linguistic communication from referential games with symbolic and pixel input":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the interaction between supervision and self play in emergent communication")
  Member "emergence of language with multi agent games learning to communicate with sequences of symbols":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the interaction between supervision and self play in emergent communication")
  Member "natural language does not emerge naturally in multi agent dialog":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the interaction between supervision and self play in emergent communication")
  Member "deep variational information bottleneck":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "intelligence physics and information the tradeoff between accuracy and simplicity in machine learning")
  Member "understanding deep learning requires rethinking generalization":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "train large then compress rethinking model size for efficient training and inference of transformers")

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)