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: "incremental transformer with deliberation decoder for document grounded conversations"
  Abstract: Document Grounded Conversations is a task to generate dialogue responses when chatting about the content of a given document. Obviously, document knowledge plays a critical role in Document Grounded Conversations, while existing dialogue models do not exploit this kind of knowledge effectively enough. In this paper, we propose a novel Transformer-based architecture for multi-turn document grounded conversations. In particular, we devise an Incremental Transformer to encode multi-turn utterances along with knowledge in related documents. Motivated by the human cognitive process, we design a two-pass decoder (Deliberation Decoder) to improve context coherence and knowledge correctness. Our empirical study on a real-world Document Grounded Dataset proves that responses generated by our model significantly outperform competitive baselines on both context coherence and knowledge relevance.

Connected through hyperedge HE-1 (induced by source paper "low resource knowledge grounded dialogue generation"):
  with members:
    - "mass masked sequence to sequence pre training for language generation"
    - "disentangling factors of variation using few labels"
    - "learning to select knowledge for response generation in dialog systems"
    - "xlnet generalized autoregressive pretraining for language understanding"
    - "roberta a robustly optimized bert pretraining approach"
    - "from eliza to xiaoice challenges and opportunities with social chatbots"
    - "deep contextualized word representations"
    - "isolating sources of disentanglement in variational autoencoders"

Connected through hyperedge HE-2 (induced by source paper "sequential latent knowledge selection for knowledge grounded dialogue"):
  with members:
    - "long and diverse text generation with planning based hierarchical variational model"
    - "sequential latent spaces for modeling the intention during diverse image captioning"
    - "conversing by reading contentful neural conversation with on demand machine reading"
    - "improving grammatical error correction via pre training a copy augmented architecture with unlabeled data"
    - "acute eval improved dialogue evaluation with optimized questions and multi turn comparisons"
    - "deepcopy grounded response generation with hierarchical pointer networks"
    - "visualizing and understanding the effectiveness of bert"
    - "learning to select knowledge for response generation in dialog systems"

Connected through hyperedge HE-3 (induced by source paper "dialogue history integration into end to end signal to concept spoken language understanding systems"):
  with members:
    - "hyst a hybrid approach for flexible and accurate dialogue state tracking"
    - "context aware neural based dialog act classification on automatically generated transcriptions"
    - "sumbt slot utterance matching for universal and scalable belief tracking"
    - "do neural dialog systems use the conversation history effectively an empirical study"
    - "curriculum based transfer learning for an effective end to end spoken language understanding and domain portability"
    - "a hierarchical decoding model for spoken language understanding from unaligned data"
    - "probing for semantic classes diagnosing the meaning content of word embeddings"
    - "recent advances in end to end spoken language understanding"

Connected through hyperedge HE-4 (induced by source paper "bridging text and video a universal multimodal transformer for video audio scene aware dialog"):
  with members:
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "the curious case of neural text degeneration"
    - "multimodal transformer networks for end to end video grounded dialogue systems"
    - "videobert a joint model for video and language representation learning"
    - "wizard of wikipedia knowledge powered conversational agents"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "making the v in vqa matter elevating the role of image understanding in visual question answering"
    - "cider consensus based image description evaluation"

Connected through hyperedge HE-5 (induced by source paper "refnet a reference aware network for background based conversation"):
  with members:
    - "improving neural response diversity with frequency aware cross entropy loss"
    - "conversing by reading contentful neural conversation with on demand machine reading"
    - "challenges in building intelligent open domain dialog systems"
    - "knowledge aware conversation generation with explainable reasoning on augmented graphs"
    - "first principle study on honeycomb fluorated inte monolayer with large rashba spin splitting and direct bandgap"
    - "improving background based conversation with context aware knowledge pre selection"
    - "learning to select knowledge for response generation in dialog systems"
    - "knowledge aware conversation generation with reasoning on augmented graph"

Connected through hyperedge HE-6 (induced by source paper "thinking globally acting locally distantly supervised global to local knowledge selection for background based conversation"):
  with members:
    - "conversing by reading contentful neural conversation with on demand machine reading"
    - "refnet a reference aware network for background based conversation"
    - "knowledge aware conversation generation with explainable reasoning on augmented graphs"
    - "improving background based conversation with context aware knowledge pre selection"
    - "learning to select knowledge for response generation in dialog systems"
    - "wizard of wikipedia knowledge powered conversational agents"
    - "personalizing dialogue agents i have a dog do you have pets too"
    - "a dataset for document grounded conversations"

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)