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: "shifting the baseline single modality performance on visual navigation qa"
  Abstract: We demonstrate the surprising strength of unimodal baselines in multimodal domains, and make concrete recommendations for best practices in future research. Where existing work often compares against random or majority class baselines, we argue that unimodal approaches better capture and reflect dataset biases and therefore provide an important comparison when assessing the performance of multimodal techniques. We present unimodal ablations on three recent datasets in visual navigation and QA, seeing an up to 29% absolute gain in performance over published baselines.

Connected through hyperedge HE-1 (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-2 (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"
    - "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-3 (induced by source paper "audio visual embodied navigation"):
  with members:
    - "two body problem collaborative visual task completion"
    - "embodied question answering in photorealistic environments with point cloud perception"
    - "do autonomous agents benefit from hearing"
    - "the replica dataset a digital replica of indoor spaces"
    - "benchmarking classic and learned navigation in complex 3d environments"
    - "co separating sounds of visual objects"
    - "splitnet sim2sim and task2task transfer for embodied visual navigation"
    - "interactive gibson benchmark for interactive navigation in cluttered environments"

Connected through hyperedge HE-4 (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"
    - "the regretful agent heuristic aided navigation through progress estimation"

Connected through hyperedge HE-5 (induced by source paper "what makes training multi modal classification networks hard"):
  with members:
    - "epic fusion audio visual temporal binding for egocentric action recognition"
    - "baidu uts submission to the epic kitchens action recognition challenge 2019"
    - "scaling egocentric vision the epic kitchens dataset"
    - "hypothesis only baselines in natural language inference"
    - "efficient low rank multimodal fusion with modality specific factors"
    - "a comparison of five multiple instance learning pooling functions for sound event detection with weak labeling"
    - "slowfast networks for video recognition"
    - "the sound of pixels"

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"
    - "vision and dialog navigation"
    - "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"

Connected through hyperedge HE-7 (induced by source paper "perceive transform and act multi modal attention networks for vision and language navigation"):
  with members:
    - "embodied vision and language navigation with dynamic convolutional filters"
    - "rerere remote embodied referring expressions in real indoor environments"
    - "embodied visual recognition"
    - "from language to goals inverse reinforcement learning for vision based instruction following"
    - "polysemous visual semantic embedding for cross modal retrieval"
    - "effective and general evaluation for instruction conditioned navigation using dynamic time warping"
    - "situational fusion of visual representation for visual navigation"
    - "stay on the path instruction fidelity in vision and language navigation"

Connected through hyperedge HE-8 (induced by source paper "embodied question answering in photorealistic environments with point cloud perception"):
  with members:
    - "splatnet sparse lattice networks for point cloud processing"
    - "blindfold baselines for embodied qa"
    - "building generalizable agents with a realistic and rich 3d environment"
    - "neural modular control for embodied question answering"
    - "minos multimodal indoor simulator for navigation in complex environments"
    - "escape from cells deep kd networks for the recognition of 3d point cloud models"
    - "home a household multimodal environment"
    - "attention is all you need"

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)