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 "interactive classification by asking informative questions"):
  Abstract: Natural language systems often rely on a single, potentially ambiguous input to make one final prediction, which may simplify the problem but degrade end user experience. Instead of making predictions with the natural language query only, we ask the user for additional information using a small number of binary and multiple-choice questions in order to better help users accomplish their goals while minimizing their effort. At each turn, our system decides between asking the most informative question or making the final classification prediction. Our approach enables bootstrapping the system using simple crowdsourcing annotations without expensive human-to-human interaction data. Evaluation demonstrates that our method substantially increases classification accuracy, while effectively balancing the number of questions with the improvement to final accuracy.

Includes members:
  Member "asking clarifying questions in open domain information seeking conversations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a tool for conducting user studies on mobile devices")
  Member "user intent prediction in information seeking conversations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "iart intent aware response ranking with transformers in information seeking conversation systems")
  Member "joint learning of interactive spoken content retrieval and trainable user simulator":
    also connected through other hyperedges:
      (none)
  Member "adversarial domain adaptation for duplicate question detection":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "adversarial domain adaptation for machine reading comprehension")
  Member "vision based navigation with language based assistance via imitation learning with indirect intervention":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "environment agnostic multitask learning for natural language grounded navigation")
  Member "coqa a conversational question answering challenge":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a survey on contextual embeddings")
  Member "playing 20 question game with policy based reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning to ask question based sequential bayesian product search")
  Member "learning to ask knowledge acquisition via 20 questions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "learning to ask question based sequential bayesian product search")

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)