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: "robust multilingual named entity recognition with shallow semi supervised features"
  Abstract: We present a multilingual Named Entity Recognition approach based on a robust and general set of features across languages and datasets. Our system combines shallow local information with clustering semi-supervised features induced on large amounts of unlabeled text. Understanding via empirical experimentation how to effectively combine various types of clustering features allows us to seamlessly export our system to other datasets and languages. The result is a simple but highly competitive system which obtains state of the art results across five languages and twelve datasets. The results are reported on standard shared task evaluation data such as CoNLL for English, Spanish and Dutch. Furthermore, and despite the lack of linguistically motivated features, we also report best results for languages such as Basque and German. In addition, we demonstrate that our method also obtains very competitive results even when the amount of supervised data is cut by half, alleviating the dependency on manually annotated data. Finally, the results show that our emphasis on clustering features is crucial to develop robust out-of-domain models. The system and models are freely available to facilitate its use and guarantee the reproducibility of results.

Connected through hyperedge HE-1 (induced by source paper "humpty dumpty controlling word meanings via corpus poisoning"):
  with members:
    - "towards a robust deep neural network in text domain a survey"
    - "universal adversarial triggers for attacking and analyzing nlp"
    - "cross lingual alignment of contextual word embeddings with applications to zero shot dependency parsing"
    - "understanding the origins of bias in word embeddings"
    - "adversarial attacks on node embeddings via graph poisoning"
    - "black box generation of adversarial text sequences to evade deep learning classifiers"
    - "deep text classification can be fooled"
    - "towards understanding linear word analogies"

Connected through hyperedge HE-2 (induced by source paper "a survey on recent advances in named entity recognition from deep learning models"):
  with members:
    - "neuroner an easy to use program for named entity recognition based on neural networks"
    - "end to end recurrent neural network models for vietnamese named entity recognition word level vs character level"
    - "transfer learning for sequence tagging with hierarchical recurrent networks"
    - "an investigation of recurrent neural architectures for drug name recognition"
    - "end to end sequence labeling via bi directional lstm cnns crf"
    - "multilingual part of speech tagging with bidirectional long short term memory models and auxiliary loss"
    - "multi task cross lingual sequence tagging from scratch"
    - "neural architectures for named entity recognition"

Connected through hyperedge HE-3 (induced by source paper "sentiment tagging with partial labels using modular architectures"):
  with members:
    - "semeval 2013 task 2 sentiment analysis in twitter"
    - "mattnet modular attention network for referring expression comprehension"
    - "learning to parse and translate improves neural machine translation"
    - "learning to reason end to end module networks for visual question answering"
    - "multitask learning with low level auxiliary tasks for encoder decoder based speech recognition"
    - "empower sequence labeling with task aware neural language model"
    - "end to end sequence labeling via bi directional lstm cnns crf"
    - "learning to compose neural networks for question answering"

Connected through hyperedge HE-4 (induced by source paper "language independent sequence labelling for opinion target extraction"):
  with members:
    - "aspect based relational sentiment analysis using a stacked neural network architecture"
    - "elixa a modular and flexible absa platform"
    - "unsupervised word and dependency path embeddings for aspect term extraction"
    - "distributed representations of words and phrases and their compositionality"
    - "thumbs up sentiment classification using machine learning techniques"
    - "introduction to the conll 2002 shared task language independent named entity recognition"

Connected through hyperedge HE-5 (induced by source paper "multi lingual dialogue act recognition with deep learning methods"):
  with members:
    - "linear transformations for cross lingual semantic textual similarity"
    - "iso standard domain independent dialogue act tagging for conversational agents"
    - "sequential short text classification with recurrent and convolutional neural networks"
    - "convolutional neural networks for sentence classification"
    - "efficient estimation of word representations in vector space"

Connected through hyperedge HE-6 (induced by source paper "question aware sentence gating networks for question and answering"):
  with members:
    - "phase conductor on multi layered attentions for machine comprehension"
    - "reinforced mnemonic reader for machine comprehension"
    - "memen multi layer embedding with memory networks for machine comprehension"
    - "supervised learning of universal sentence representations from natural language inference data"
    - "fusionnet fusing via fully aware attention with application to machine comprehension"
    - "recurrent neural network based sentence encoder with gated attention for natural language inference"
    - "learning to compose task specific tree structures"
    - "text understanding with the attention sum reader network"

Connected through hyperedge HE-7 (induced by source paper "sequence labeling a practical approach"):
  with members:
    - "neural models for sequence chunking"
    - "fast and accurate entity recognition with iterated dilated convolutions"
    - "semi supervised sequence tagging with bidirectional language models"
    - "end to end sequence labeling via bi directional lstm cnns crf"
    - "multi task cross lingual sequence tagging from scratch"
    - "neural architectures for named entity recognition"
    - "multilingual language processing from bytes"
    - "finding function in form compositional character models for open vocabulary word representation"

Connected through hyperedge HE-8 (induced by source paper "w2vlda almost unsupervised system for aspect based sentiment analysis"):
  with members:
    - "improving topic models with latent feature word representations"
    - "ultradense word embeddings by orthogonal transformation"
    - "automatic labelling of topics with neural embeddings"
    - "topic modeling over short texts by incorporating word embeddings"
    - "efficient estimation of word representations in vector space"
    - "measuring praise and criticism inference of semantic orientation from association"

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)