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: "a retrieval based dialogue system utilizing utterance and context embeddings"
  Abstract: Finding semantically rich and computer-understandable representations for textual dialogues, utterances and words is crucial for dialogue systems (or conversational agents), as their performance mostly depends on understanding the context of conversations. Recent research aims at finding distributed vector representations (embeddings) for words, such that semantically similar words are relatively close within the vector-space. Encoding the "meaning" of text into vectors is a current trend, and text can range from words, phrases and documents to actual human-to-human conversations. In recent research approaches, responses have been generated utilizing a decoder architecture, given the vector representation of the current conversation. In this paper, the utilization of embeddings for answer retrieval is explored by using Locality-Sensitive Hashing Forest (LSH Forest), an Approximate Nearest Neighbor (ANN) model, to find similar conversations in a corpus and rank possible candidates. Experimental results on the well-known Ubuntu Corpus (in English) and a customer service chat dataset (in Dutch) show that, in combination with a candidate selection method, retrieval-based approaches outperform generative ones and reveal promising future research directions towards the usability of such a system.

Connected through hyperedge HE-1 (induced by source paper "training neural response selection for task oriented dialogue systems"):
  with members:
    - "passage re ranking with bert"
    - "semeval 2015 task 3 answer selection in community question answering"
    - "simple applications of bert for ad hoc document retrieval"
    - "a repository of conversational datasets"
    - "multi task deep neural networks for natural language understanding"
    - "bert post training for review reading comprehension and aspect based sentiment analysis"
    - "learning semantic textual similarity from conversations"
    - "improving response selection in multi turn dialogue systems by incorporating domain knowledge"

Connected through hyperedge HE-2 (induced by source paper "aloha artificial learning of human attributes for dialogue agents"):
  with members:
    - "the second conversational intelligence challenge convai2"
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "real time inference in multi sentence tasks with deep pretrained transformers"
    - "meetup a corpus of joint activity dialogues in a visual environment"
    - "bert for coreference resolution baselines and analysis"
    - "learning to speak and act in a fantasy text adventure game"
    - "keep calm and switch on preserving sentiment and fluency in semantic text exchange"
    - "game based video context dialogue"

Connected through hyperedge HE-3 (induced by source paper "knowledge incorporating esim models for response selection in retrieval based dialog systems"):
  with members:
    - "analyzing assumptions in conversation disentanglement research through the lens of a new dataset and model"
    - "enhance word representation for out of vocabulary on ubuntu dialogue corpus"
    - "key value retrieval networks for task oriented dialogue"
    - "a knowledge grounded neural conversation model"
    - "augmenting end to end dialog systems with commonsense knowledge"
    - "enhanced lstm for natural language inference"
    - "lstm based mixture of experts for knowledge aware dialogues"
    - "sequential matching network a new architecture for multi turn response selection in retrieval based chatbots"

Connected through hyperedge HE-4 (induced by source paper "conversational implicatures in english dialogue annotated dataset"):
  with members:
    - "a repository of conversational datasets"
    - "coqa a conversational question answering challenge"
    - "multiresolution recurrent neural networks an application to dialogue response generation"
    - "end to end lstm based dialog control optimized with supervised and reinforcement learning"
    - "squinky a corpus of sentence level formality informativeness and implicature"

Connected through hyperedge HE-5 (induced by source paper "contextual memory trees"):
  with members:
    - "learning efficient algorithms with hierarchical attentive memory"
    - "prototypical networks for few shot learning"
    - "fast and accurate entity recognition with iterated dilated convolutions"
    - "learning to remember rare events"
    - "search engine guided non parametric neural machine translation"
    - "one shot learning with memory augmented neural networks"
    - "scaling memory augmented neural networks with sparse reads and writes"
    - "logarithmic time online multiclass prediction"

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)