human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "dailydialog a manually labelled multi turn dialogue dataset"
  Abstract: We develop a high-quality multi-turn dialog dataset, DailyDialog, which is intriguing in several aspects. The language is human-written and less noisy. The dialogues in the dataset reflect our daily communication way and cover various topics about our daily life. We also manually label the developed dataset with communication intention and emotion information. Then, we evaluate existing approaches on DailyDialog dataset and hope it benefit the research field of dialog systems.

Connected through hyperedge HE-1 (induced by source paper "an empirical investigation of pre trained transformer language models for open domain dialogue generation"):
  with members:
    - "towards a human like open domain chatbot"
    - "a neural topical expansion framework for unstructured persona oriented dialogue generation"
    - "empgan multi resolution interactive empathetic dialogue generation"
    - "a pre training based personalized dialogue generation model with persona sparse data"
    - "fine grained sentence functions for short text conversation"
    - "the curious case of neural text degeneration"
    - "do massively pretrained language models make better storytellers"
    - "a discrete cvae for response generation on short text conversation"

Connected through hyperedge HE-2 (induced by source paper "posterior gan towards informative and coherent response generation with posterior generative adversarial network"):
  with members:
    - "improving neural conversational models with entropy based data filtering"
    - "dialogwae multimodal response generation with conditional wasserstein auto encoder"
    - "better conversations by modeling filtering and optimizing for coherence and diversity"
    - "a study of reinforcement learning for neural machine translation"
    - "generating informative and diverse conversational responses via adversarial information maximization"
    - "improving variational encoder decoders in dialogue generation"
    - "latent variable dialogue models and their diversity"
    - "adversarial learning for neural dialogue generation"

Connected through hyperedge HE-3 (induced by source paper "learning from easy to complex adaptive multi curricula learning for neural dialogue generation"):
  with members:
    - "improving neural conversational models with entropy based data filtering"
    - "recosa detecting the relevant contexts with self attention for multi turn dialogue generation"
    - "what makes a good conversation how controllable attributes affect human judgments"
    - "competence based curriculum learning for neural machine translation"
    - "simple and effective curriculum pointer generator networks for reading comprehension over long narratives"
    - "dialogwae multimodal response generation with conditional wasserstein auto encoder"
    - "better conversations by modeling filtering and optimizing for coherence and diversity"
    - "curriculum learning by transfer learning theory and experiments with deep networks"

Connected through hyperedge HE-4 (induced by source paper "a neural topical expansion framework for unstructured persona oriented dialogue generation"):
  with members:
    - "a pre training based personalized dialogue generation model with persona sparse data"
    - "an adversarial learning framework for a persona based multi turn dialogue model"
    - "exploiting persona information for diverse generation of conversational responses"
    - "refnet a reference aware network for background based conversation"
    - "thinking globally acting locally distantly supervised global to local knowledge selection for background based conversation"
    - "learning to speak and act in a fantasy text adventure game"
    - "personalized dialogue generation with diversified traits"
    - "learning personas from dialogue with attentive memory networks"

Connected through hyperedge HE-5 (induced by source paper "emptransfo a multi head transformer architecture for creating empathetic dialog systems"):
  with members:
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "the curious case of neural text degeneration"
    - "delivering cognitive behavioral therapy using a conversational socialrobot"
    - "huggingface s transformers state of the art natural language processing"
    - "affect driven dialog generation"
    - "bleu is not suitable for the evaluation of text simplification"
    - "towards empathetic open domain conversation models a new benchmark and dataset"
    - "personalizing dialogue agents i have a dog do you have pets too"

Connected through hyperedge HE-6 (induced by source paper "local contextual attention with hierarchical structure for dialogue act recognition"):
  with members:
    - "dialogue act classification with context aware self attention"
    - "self attention with relative position representations"
    - "unsupervised discrete sentence representation learning for interpretable neural dialog generation"
    - "a deep sequential model for discourse parsing on multi party dialogues"
    - "a context based approach for dialogue act recognition using simple recurrent neural networks"
    - "modeling localness for self attention networks"
    - "deep contextualized word representations"
    - "bert pre training of deep bidirectional transformers for language understanding"

Connected through hyperedge HE-7 (induced by source paper "dynamic knowledge routing network for target guided open domain conversation"):
  with members:
    - "towards coherent and engaging spoken dialog response generation using automatic conversation evaluators"
    - "end to end knowledge routed relational dialogue system for automatic diagnosis"
    - "target guided open domain conversation"
    - "analogical reasoning on chinese morphological and semantic relations"
    - "texar a modularized versatile and extensible toolkit for text generation"
    - "towards deep conversational recommendations"
    - "emergent communication through negotiation"
    - "conversational ai the science behind the alexa prize"

Connected through hyperedge HE-8 (induced by source paper "learning to compare for better training and evaluation of open domain natural language generation models"):
  with members:
    - "unifying human and statistical evaluation for natural language generation"
    - "bertscore evaluating text generation with bert"
    - "judge the judges a large scale evaluation study of neural language models for online review generation"
    - "hierarchical neural story generation"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "the price of debiasing automatic metrics in natural language evaluation"
    - "attention is all you need"
    - "get to the point summarization with pointer generator networks"

Question: Please tell me which class the center node 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)