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: "the regretful agent heuristic aided navigation through progress estimation"
  Abstract: As deep learning continues to make progress for challenging perception tasks, there is increased interest in combining vision, language, and decision-making. Specifically, the Vision and Language Navigation (VLN) task involves navigating to a goal purely from language instructions and visual information without explicit knowledge of the goal. Recent successful approaches have made in-roads in achieving good success rates for this task but rely on beam search, which thoroughly explores a large number of trajectories and is unrealistic for applications such as robotics. In this paper, inspired by the intuition of viewing the problem as search on a navigation graph, we propose to use a progress monitor developed in prior work as a learnable heuristic for search. We then propose two modules incorporated into an end-to-end architecture: 1) A learned mechanism to perform backtracking, which decides whether to continue moving forward or roll back to a previous state (Regret Module) and 2) A mechanism to help the agent decide which direction to go next by showing directions that are visited and their associated progress estimate (Progress Marker). Combined, the proposed approach significantly outperforms current state-of-the-art methods using greedy action selection, with 5% absolute improvement on the test server in success rates, and more importantly 8% on success rates normalized by the path length. Our code is available 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"
    - "vision and dialog 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"
    - "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:
    - "vision and dialog navigation"
    - "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"

Connected through hyperedge HE-3 (induced by source paper "multi view learning for vision and language navigation"):
  with members:
    - "towards learning a generic agent for vision and language navigation via pre training"
    - "tactical rewind self correction via backtracking in vision and language navigation"
    - "vision language navigation with self supervised auxiliary reasoning tasks"
    - "self monitoring navigation agent via auxiliary 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"
    - "speaker follower models for vision and language navigation"

Connected through hyperedge HE-4 (induced by source paper "reverie remote embodied visual referring expression in real indoor environments"):
  with members:
    - "improving referring expression grounding with cross modal attention guided erasing"
    - "tactical rewind self correction via backtracking in vision and language navigation"
    - "reinforced cross modal matching and self supervised imitation learning for vision language navigation"
    - "talk the walk navigating new york city through grounded dialogue"
    - "touchdown natural language navigation and spatial reasoning in visual street environments"
    - "speaker follower models for vision and language navigation"
    - "vision based navigation with language based assistance via imitation learning with indirect intervention"
    - "mattnet modular attention network for referring expression comprehension"

Connected through hyperedge HE-5 (induced by source paper "talk2nav long range vision and language navigation with dual attention and spatial memory"):
  with members:
    - "tactical rewind self correction via backtracking in vision and language navigation"
    - "learning accurate comfortable and human like driving"
    - "learning to follow directions in street view"
    - "grounding human to vehicle advice for self driving vehicles"
    - "self monitoring navigation agent via auxiliary progress estimation"
    - "reinforced cross modal matching and self supervised imitation learning for vision language navigation"
    - "talk the walk navigating new york city through grounded dialogue"
    - "touchdown natural language navigation and spatial reasoning in visual street environments"

Connected through hyperedge HE-6 (induced by source paper "talk2nav long range vision and language navigation in cities"):
  with members:
    - "tactical rewind self correction via backtracking in vision and language navigation"
    - "language conditioned graph networks for relational reasoning"
    - "grounding human to vehicle advice for self driving vehicles"
    - "self monitoring navigation agent via auxiliary progress estimation"
    - "reinforced cross modal matching and self supervised imitation learning for vision language navigation"
    - "talk the walk navigating new york city through grounded dialogue"
    - "touchdown natural language navigation and spatial reasoning in visual street environments"
    - "visual memory for robust path following"

Connected through hyperedge HE-7 (induced by source paper "help anna visual navigation with natural multimodal assistance via retrospective curiosity encouraging imitation learning"):
  with members:
    - "vision and dialog navigation"
    - "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"
    - "qt opt scalable deep reinforcement learning for vision based robotic manipulation"

Connected through hyperedge HE-8 (induced by source paper "chasing ghosts instruction following as bayesian state tracking"):
  with members:
    - "tactical rewind self correction via backtracking in vision and language navigation"
    - "self monitoring navigation agent via auxiliary 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"
    - "differentiable particle filters end to end learning with algorithmic priors"
    - "semi parametric topological memory for navigation"
    - "speaker follower models for vision and language navigation"
    - "on evaluation of embodied navigation agents"

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.AI(Artificial Intelligence)