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: "a large scale exploration of effective global features for a joint entity detection and tracking model"
  Abstract: Entity detection and tracking (EDT) is the task of identifying textual mentions of real-world entities in documents, extending the named entity detection and coreference resolution task by considering mentions other than names (pronouns, definite descriptions, etc.). Like NE tagging and coreference resolution, most solutions to the EDT task separate out the mention detection aspect from the coreference aspect. By doing so, these solutions are limited to using only local features for learning. In contrast, by modeling both aspects of the EDT task simultaneously, we are able to learn using highly complex, non-local features. We develop a new joint EDT model and explore the utility of many features, demonstrating their effectiveness on this task.

Connected through hyperedge HE-1 (induced by source paper "toward gender inclusive coreference resolution"):
  with members:
    - "equalizing gender biases in neural machine translation with word embeddings techniques"
    - "lipstick on a pig debiasing methods cover up systematic gender biases in word embeddings but do not remove them"
    - "counterfactual data augmentation for mitigating gender stereotypes in languages with rich morphology"
    - "mind the gap a balanced corpus of gendered ambiguous pronouns"
    - "assessing gender bias in machine translation a case study with google translate"
    - "examining gender and race bias in two hundred sentiment analysis systems"
    - "pronoun translation in english french machine translation an analysis of error types"
    - "gender bias in coreference resolution"

Connected through hyperedge HE-2 (induced by source paper "anaphora and coreference resolution a review"):
  with members:
    - "recent trends in deep learning based personality detection"
    - "solving hard coreference problems"
    - "sentiment and sarcasm classification with multitask learning"
    - "end to end neural coreference resolution"
    - "a mention ranking model for abstract anaphora resolution"
    - "evaluating discourse phenomena in neural machine translation"
    - "lexical features in coreference resolution to be used with caution"
    - "recent trends in deep learning based natural language processing"

Connected through hyperedge HE-3 (induced by source paper "neural coreference resolution with deep biaffine attention by joint mention detection and mention clustering"):
  with members:
    - "end to end neural coreference resolution"
    - "lexical features in coreference resolution to be used with caution"
    - "improving coreference resolution by learning entity level distributed representations"
    - "learning global features for coreference resolution"
    - "deep reinforcement learning for mention ranking coreference models"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-4 (induced by source paper "reinforcement learning for transition based mention detection"):
  with members:
    - "globally normalized transition based neural networks"
    - "neural architectures for named entity recognition"
    - "prioritized experience replay"
    - "introduction to the conll 2003 shared task language independent named entity recognition"

Connected through hyperedge HE-5 (induced by source paper "improving coreference resolution by learning entity level distributed representations"):
  with members:
    - "learning global features for coreference resolution"
    - "learning to search for dependencies"
    - "learning to search better than your teacher"
    - "efficient programmable learning to search"
    - "polyglot distributed word representations for multilingual nlp"
    - "distributed representations of words and phrases and their compositionality"
    - "improving neural networks by preventing co adaptation of feature detectors"
    - "narrowing the modeling gap a cluster ranking approach to coreference resolution"

Connected through hyperedge HE-6 (induced by source paper "big data and cross document coreference resolution current state and future opportunities"):
  with members:
    - "distantly labeling data for large scale cross document coreference"

Connected through hyperedge HE-7 (induced by source paper "narrowing the modeling gap a cluster ranking approach to coreference resolution"):
  with members:
    - "a survey of paraphrasing and textual entailment methods"

Connected through hyperedge HE-8 (induced by source paper "search based structured prediction"):
  with members:
    - "pegasus a policy search method for large mdps and pomdps"
    - "case factor diagrams for structured probabilistic modeling"
    - "bayesian query focused summarization"
    - "a noisy channel model for document compression"
    - "learning as search optimization approximate large margin methods for structured prediction"
    - "the use of classifiers in sequential inference"

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)