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: "vision and dialog navigation"
  Abstract: Robots navigating in human environments should use language to ask for assistance and be able to understand human responses. To study this challenge, we introduce Cooperative Vision-and-Dialog Navigation, a dataset of over 2k embodied, human-human dialogs situated in simulated, photorealistic home environments. The Navigator asks questions to their partner, the Oracle, who has privileged access to the best next steps the Navigator should take according to a shortest path planner. To train agents that search an environment for a goal location, we define the Navigation from Dialog History task. An agent, given a target object and a dialog history between humans cooperating to find that object, must infer navigation actions towards the goal in unexplored environments. We establish an initial, multi-modal sequence-to-sequence model and demonstrate that looking farther back in the dialog history improves performance. Sourcecode and a live interface demo can be found at this https URL

Connected through hyperedge HE-1 (induced by source paper "environment agnostic multitask learning for natural language grounded navigation"):
  with members:
    - "multi modal discriminative model for vision and language navigation"
    - "tactical rewind self correction via backtracking in vision and language navigation"
    - "domain agnostic learning with disentangled representations"
    - "valan vision and language agent navigation"
    - "stay on the path instruction fidelity in vision and language navigation"
    - "transferable representation learning in vision and language navigation"
    - "the regretful agent heuristic aided navigation through progress estimation"
    - "learning to navigate unseen environments back translation with environmental dropout"

Connected through hyperedge HE-2 (induced by source paper "towards learning a generic agent for vision and language navigation via pre training"):
  with members:
    - "tactical rewind self correction via backtracking in vision and language navigation"
    - "lxmert learning cross modality encoder representations from transformers"
    - "unicoder vl a universal encoder for vision and language by cross modal pre training"
    - "vilbert pretraining task agnostic visiolinguistic representations for vision and language tasks"
    - "robust navigation with language pretraining and stochastic sampling"
    - "videobert a joint model for video and language representation learning"
    - "vl bert pre training of generic visual linguistic representations"
    - "the regretful agent heuristic aided navigation through progress estimation"

Connected through hyperedge HE-3 (induced by source paper "large scale pretraining for visual dialog a simple state of the art baseline"):
  with members:
    - "image question answer synergistic network for visual dialog"
    - "exploring the limits of transfer learning with a unified text to text transformer"
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "lxmert learning cross modality encoder representations from transformers"
    - "uniter learning universal image text representations"
    - "reasoning visual dialogs with structural and partial observations"
    - "making history matter history advantage sequence training for visual dialog"
    - "dual attention networks for visual reference resolution in visual dialog"

Connected through hyperedge HE-4 (induced by source paper "vision language navigation with self supervised auxiliary reasoning tasks"):
  with members:
    - "test time training for out of distribution generalization"
    - "lxmert learning cross modality encoder representations from transformers"
    - "fusion of detected objects in text for visual question answering"
    - "scene graph generation with external knowledge and image reconstruction"
    - "discovery of useful questions as auxiliary tasks"
    - "self supervised generalisation with meta auxiliary learning"
    - "vilbert pretraining task agnostic visiolinguistic representations for vision and language tasks"
    - "albert a lite bert for self supervised learning of language representations"

Connected through hyperedge HE-5 (induced by source paper "help anna visual navigation with natural multimodal assistance via retrospective curiosity encouraging imitation learning"):
  with members:
    - "rerere remote embodied referring expressions in real indoor environments"
    - "embodied question answering in photorealistic environments with point cloud perception"
    - "from video game to real robot the transfer between action spaces"
    - "learning to speak and act in a fantasy text adventure game"
    - "self monitoring navigation agent via auxiliary progress estimation"
    - "neural text generation with unlikelihood training"
    - "the regretful agent heuristic aided navigation through progress estimation"
    - "qt opt scalable deep reinforcement learning for vision based robotic manipulation"

Connected through hyperedge HE-6 (induced by source paper "alfred a benchmark for interpreting grounded instructions for everyday tasks"):
  with members:
    - "what should i do now marrying reinforcement learning and symbolic planning"
    - "tactical rewind self correction via backtracking in vision and language navigation"
    - "embodied question answering in photorealistic environments with point cloud perception"
    - "multi target embodied question answering"
    - "the regretful agent heuristic aided navigation through progress estimation"
    - "6 dof graspnet variational grasp generation for object manipulation"
    - "learning to navigate unseen environments back translation with environmental dropout"
    - "interactive visual grounding of referring expressions for human robot interaction"

Connected through hyperedge HE-7 (induced by source paper "just ask an interactive learning framework for vision and language navigation"):
  with members:
    - "tactical rewind self correction via backtracking in vision and language navigation"
    - "self monitoring navigation agent via auxiliary progress estimation"
    - "improving grounded natural language understanding through human robot dialog"
    - "habitat a platform for embodied ai research"
    - "the regretful agent heuristic aided navigation through progress estimation"
    - "learning to navigate unseen environments back translation with environmental dropout"
    - "reinforced cross modal matching and self supervised imitation learning for vision language navigation"
    - "touchdown natural language navigation and spatial reasoning in visual street environments"

Connected through hyperedge HE-8 (induced by source paper "valan vision and language agent navigation"):
  with members:
    - "seed rl scalable and efficient deep rl with accelerated central inference"
    - "effective and general evaluation for instruction conditioned navigation using dynamic time warping"
    - "stay on the path instruction fidelity in vision and language navigation"
    - "transferable representation learning in vision and language navigation"
    - "dopamine a research framework for deep reinforcement learning"
    - "impala scalable distributed deep rl with importance weighted actor learner architectures"
    - "reinforced cross modal matching and self supervised imitation learning for vision language navigation"
    - "touchdown natural language navigation and spatial reasoning in visual street environments"

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)