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: "towards assistive feeding with a general purpose mobile manipulator"
  Abstract: General-purpose mobile manipulators have the potential to serve as a versatile form of assistive technology. However, their complexity creates challenges, including the risk of being too difficult to use. We present a proof-of-concept robotic system for assistive feeding that consists of a Willow Garage PR2, a high-level web-based interface, and specialized autonomous behaviors for scooping and feeding yogurt. As a step towards use by people with disabilities, we evaluated our system with 5 able-bodied participants. All 5 successfully ate yogurt using the system and reported high rates of success for the system's autonomous behaviors. Also, Henry Evans, a person with severe quadriplegia, operated the system remotely to feed an able-bodied person. In general, people who operated the system reported that it was easy to use, including Henry. The feeding system also incorporates corrective actions designed to be triggered either autonomously or by the user. In an offline evaluation using data collected with the feeding system, a new version of our multimodal anomaly detection system outperformed prior versions.

Connected through hyperedge HE-1 (induced by source paper "adaptive robot assisted feeding an online learning framework for acquiring previously unseen food items"):
  with members:
    - "robot assisted feeding generalizing skewering strategies across food items on a realistic plate"
    - "towards robotic feeding role of haptics in fork based food manipulation"
    - "practical contextual bandits with regression oracles"
    - "focal loss for dense object detection"
    - "bandit based model selection for deformable object manipulation"
    - "taming the monster a fast and simple algorithm for contextual bandits"
    - "exploration in interactive personalized music recommendation a reinforcement learning approach"
    - "a contextual bandit approach to personalized news article recommendation"

Connected through hyperedge HE-2 (induced by source paper "robot assisted feeding generalizing skewering strategies across food items on a realistic plate"):
  with members:
    - "towards robotic feeding role of haptics in fork based food manipulation"
    - "toward active robot assisted feeding with a general purpose mobile manipulator design evaluation and lessons learned"
    - "mask r cnn"
    - "densely connected convolutional networks"
    - "a baseline for detecting misclassified and out of distribution examples in neural networks"
    - "an empirical study and analysis of generalized zero shot learning for object recognition in the wild"
    - "supersizing self supervision learning to grasp from 50k tries and 700 robot hours"
    - "real time grasp detection using convolutional neural networks"

Connected through hyperedge HE-3 (induced by source paper "learning from failures in robot assisted feeding using online learning to develop manipulation strategies for bite acquisition"):
  with members:
    - "robot assisted feeding generalizing skewering strategies across food items on a realistic plate"
    - "towards robotic feeding role of haptics in fork based food manipulation"
    - "practical contextual bandits with regression oracles"
    - "focal loss for dense object detection"
    - "bandit based model selection for deformable object manipulation"
    - "taming the monster a fast and simple algorithm for contextual bandits"
    - "exploration in interactive personalized music recommendation a reinforcement learning approach"
    - "a contextual bandit approach to personalized news article recommendation"

Connected through hyperedge HE-4 (induced by source paper "toward active robot assisted feeding with a general purpose mobile manipulator design evaluation and lessons learned"):
  with members:
    - "in home and remote use of robotic body surrogates by people with profound motor deficits"
    - "shared autonomy via hindsight optimization for teleoperation and teaming"
    - "a multimodal anomaly detector for robot assisted feeding using an lstm based variational autoencoder"
    - "tracking human pose during robot assisted dressing using single axis capacitive proximity sensing"
    - "reaching in clutter with whole arm tactile sensing"

Connected through hyperedge HE-5 (induced by source paper "acting thoughts towards a mobile robotic service assistant for users with limited communication skills"):
  with members:
    - "eegnet a compact convolutional neural network for eeg based brain computer interfaces"
    - "deep learning with convolutional neural networks for eeg decoding and visualization"
    - "very deep multilingual convolutional neural networks for lvcsr"
    - "deep residual learning for image recognition"
    - "fast and accurate deep network learning by exponential linear units elus"
    - "learning representations from eeg with deep recurrent convolutional neural networks"
    - "the fast downward planning system"

Connected through hyperedge HE-6 (induced by source paper "a multimodal anomaly detector for robot assisted feeding using an lstm based variational autoencoder"):
  with members:
    - "recurrent neural radio anomaly detection"
    - "lstm based encoder decoder for multi sensor anomaly detection"
    - "generating sentences from a continuous space"
    - "denoising criterion for variational auto encoding framework"
    - "learning phrase representations using rnn encoder decoder for statistical machine translation"
    - "reaching in clutter with whole arm tactile sensing"

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.RO(Robotics)