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 "recovering dropped pronouns in chinese conversations via modeling their referents"):
  Abstract: Pronouns are often dropped in Chinese sentences, and this happens more frequently in conversational genres as their referents can be easily understood from context. Recovering dropped pronouns is essential to applications such as Information Extraction where the referents of these dropped pronouns need to be resolved, or Machine Translation when Chinese is the source language. In this work, we present a novel end-to-end neural network model to recover dropped pronouns in conversational data. Our model is based on a structured attention mechanism that models the referents of dropped pronouns utilizing both sentence-level and word-level information. Results on three different conversational genres show that our approach achieves a significant improvement over the current state of the art.

Includes members:
  Member "analogical reasoning on chinese morphological and semantic relations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dynamic knowledge routing network for target guided open domain conversation")
  Member "translating pro drop languages with reconstruction models":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "go from the general to the particular multi domain translation with domain transformation networks")
  Member "deep reinforcement learning for chinese zero pronoun resolution":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "generating persona consistent dialogues by exploiting natural language inference")
  Member "structured attention networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep adaptive semantic logic dasl compiling declarative knowledge into deep neural networks")
  Member "hierarchical recurrent attention network for response generation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a survey of natural language generation techniques with a focus on dialogue systems past present and future directions")
  Member "a novel approach to dropped pronoun translation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "when a good translation is wrong in context context aware machine translation improves on deixis ellipsis and lexical cohesion")
  Member "tracking the world state with recurrent entity networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "the next decade in ai four steps towards robust artificial intelligence")
  Member "key value memory networks for directly reading documents":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "attention over parameters for dialogue systems")

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)