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 "playing log n questions over sentences"):
  Abstract: We propose a two-agent game wherein a questioner must be able to conjure discerning questions between sentences, incorporate responses from an answerer, and keep track of a hypothesis state. The questioner must be able to understand the information required to make its final guess, while also being able to reason over the game's text environment based on the answerer's responses. We experiment with an end-to-end model where both agents can learn simultaneously to play the game, showing that simultaneously achieving high game accuracy and producing meaningful questions can be a difficult trade-off.

Includes members:
  Member "hotpotqa a dataset for diverse explainable multi hop question answering":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a study of the tasks and models in machine reading comprehension")
  Member "learning to describe differences between pairs of similar images":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adjusting image attributes of localized regions with low level dialogue")
  Member "learning cooperative visual dialog agents with deep reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "grad cam visual explanations from deep networks via gradient based localization")
  Member "learning to disambiguate by asking discriminative questions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "why does a visual question have different answers")
  Member "interpretable semantic textual similarity":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a deep network model for paraphrase detection in short text messages")
  Member "constructing datasets for multi hop reading comprehension across documents":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "natural language qa approaches using reasoning with external knowledge")
  Member "end to end memory networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning video object segmentation from unlabeled videos")
  Member "a large annotated corpus for learning natural language inference":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "contextual lensing of universal sentence representations")

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)