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 "empgan multi resolution interactive empathetic dialogue generation"):
  Abstract: Conventional emotional dialogue system focuses on generating emotion-rich replies. Studies on emotional intelligence suggest that constructing a more empathetic dialogue system, which is sensitive to the users' expressed emotion, is a crucial step towards a more humanized human-machine conversation. However, obstacles to establishing such an empathetic conversational system are still far beyond current progress: 1) Simply considering the sentence-level emotions while neglecting the more precise token-level emotions may lead to insufficient emotion perceptivity. 2) Merely relying on the dialogue history but overlooking the potential of user feedback for the generated responses further aggravates the insufficient emotion perceptivity deficiencies. #R##N#To address the above challenges, we propose the EmpGAN, a multi-resolution adversarial empathetic dialogue generation model to generate more appropriate and empathetic responses. To capture the nuances of user feelings sufficiently, EmpGAN generates responses by jointly taking both the coarse-grained sentence-level and fine-grained token-level emotions into account. Moreover, an interactive adversarial learning framework is introduced to further identify whether the generated responses evoke emotion perceptivity in dialogues regarding both the dialogue history and user feedback. Experiments show that our model outperforms the state-of-the-art baseline by a significant margin in terms of both content quality as well as the emotion perceptivity. In particular, the distinctiveness on the DailyDialog dataset is increased up to 129%.

Includes members:
  Member "affect driven dialog generation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "emptransfo a multi head transformer architecture for creating empathetic dialog systems")
  Member "a syntactically constrained bidirectional asynchronous approach for emotional conversation generation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a simple dual decoder model for generating response with sentiment")
  Member "towards empathetic open domain conversation models a new benchmark and dataset":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "emptransfo a multi head transformer architecture for creating empathetic dialog systems")
  Member "an affect rich neural conversational model with biased attention and weighted cross entropy loss":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "knowledge enriched transformer for emotion detection in textual conversations")
  Member "emotional chatting machine emotional conversation generation with internal and external memory":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "an empirical investigation of pre trained transformer language models for open domain dialogue generation")
  Member "mojitalk generating emotional responses at scale":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "generating emotionally aligned responses in dialogues using affect control theory")
  Member "dailydialog a manually labelled multi turn dialogue dataset":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "an empirical investigation of pre trained transformer language models for open domain dialogue generation")
  Member "adversarial learning for neural dialogue generation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "non autoregressive neural dialogue generation")

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)