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: "diachronic word embeddings reveal statistical laws of semantic change"
  Abstract: Understanding how words change their meanings over time is key to models of language and cultural evolution, but historical data on meaning is scarce, making theories hard to develop and test. Word embeddings show promise as a diachronic tool, but have not been carefully evaluated. We develop a robust methodology for quantifying semantic change by evaluating word embeddings (PPMI, SVD, word2vec) against known historical changes. We then use this methodology to reveal statistical laws of semantic evolution. Using six historical corpora spanning four languages and two centuries, we propose two quantitative laws of semantic change: (i) the law of conformity---the rate of semantic change scales with an inverse power-law of word frequency; (ii) the law of innovation---independent of frequency, words that are more polysemous have higher rates of semantic change.

Connected through hyperedge HE-1 (induced by source paper "a framework for the computational linguistic analysis of dehumanization"):
  with members:
    - "social bias frames reasoning about social and power implications of language"
    - "mitigating gender bias in natural language processing literature review"
    - "talkdown a corpus for condescension detection in context"
    - "automatically neutralizing subjective bias in text"
    - "black is to criminal as caucasian is to police detecting and removing multiclass bias in word embeddings"
    - "contextual affective analysis a case study of people portrayals in online metoo stories"
    - "entity centric contextual affective analysis"
    - "examining gender and race bias in two hundred sentiment analysis systems"

Connected through hyperedge HE-2 (induced by source paper "understanding the downstream instability of word embeddings"):
  with members:
    - "on the downstream performance of compressed word embeddings"
    - "the influence of down sampling strategies on svd word embedding stability"
    - "allennlp a deep semantic natural language processing platform"
    - "deep contextualized word representations"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "factors influencing the surprising instability of word embeddings"
    - "on the dimensionality of word embedding"
    - "attention is all you need"

Connected through hyperedge HE-3 (induced by source paper "neural embeddings of scholarly periodicals reveal complex disciplinary organizations"):
  with members:
    - "the geometry of culture analyzing the meanings of class through word embeddings"
    - "the preeminence of ethnic diversity in scientific collaboration"
    - "semaxis a lightweight framework to characterize domain specific word semantics beyond sentiment"
    - "a style based generator architecture for generative adversarial networks"
    - "word embeddings quantify 100 years of gender and ethnic stereotypes"
    - "semantics derived automatically from language corpora contain human like biases"
    - "node2vec scalable feature learning for networks"
    - "man is to computer programmer as woman is to homemaker debiasing word embeddings"

Connected through hyperedge HE-4 (induced by source paper "where new words are born distributional semantic analysis of neologisms and their semantic neighborhoods"):
  with members:
    - "survey of computational approaches to diachronic conceptual change"
    - "making fetch happen the influence of social and linguistic context on nonstandard word growth and decline"
    - "the road to success assessing the fate of linguistic innovations in online communities"
    - "word embeddings quantify 100 years of gender and ethnic stereotypes"
    - "diachronic word embeddings and semantic shifts a survey"
    - "problems with evaluation of word embeddings using word similarity tasks"
    - "statistically significant detection of linguistic change"
    - "improving zero shot learning by mitigating the hubness problem"

Connected through hyperedge HE-5 (induced by source paper "shared task lexical semantic change detection in german"):
  with members:
    - "time out temporal referencing for robust modeling of lexical semantic change"
    - "a wind of change detecting and evaluating lexical semantic change across times and domains"
    - "survey of computational approaches to diachronic conceptual change"
    - "fasttext zip compressing text classification models"
    - "word translation without parallel data"
    - "sparse overcomplete word vector representations"
    - "statistically significant detection of linguistic change"
    - "temporal analysis of language through neural language models"

Connected through hyperedge HE-6 (induced by source paper "simulating lexical semantic change from sense annotated data"):
  with members:
    - "gasc genre aware semantic change for ancient greek"
    - "a wind of change detecting and evaluating lexical semantic change across times and domains"
    - "challenges in detecting evolutionary forces in language change using diachronic corpora"
    - "dialectometric analysis of language variation in twitter"
    - "german in flux detecting metaphoric change via word entropy"
    - "cultural shift or linguistic drift comparing two computational measures of semantic change"
    - "statistically significant detection of linguistic change"

Connected through hyperedge HE-7 (induced by source paper "semantic drift in multilingual representations"):
  with members:
    - "a survey of cross lingual word embedding models"
    - "what do language representations really represent"
    - "blackbox meets blackbox representational similarity and stability analysis of neural language models and brains"
    - "filtering and mining parallel data in a joint multilingual space"
    - "xnli evaluating cross lingual sentence representations"
    - "massively multilingual sentence embeddings for zero shot cross lingual transfer and beyond"
    - "multimodal grounding for language processing"
    - "glue a multi task benchmark and analysis platform for natural language understanding"

Connected through hyperedge HE-8 (induced by source paper "language in our time an empirical analysis of hashtags"):
  with members:
    - "network embedding as matrix factorization unifying deepwalk line pte and node2vec"
    - "tagvisor a privacy advisor for sharing hashtags"
    - "hierarchical graph representation learning with differentiable pooling"
    - "you are your metadata identification and obfuscation of social media users using metadata information"
    - "analyzing the digital traces of political manipulation the 2016 russian interference twitter campaign"
    - "ml leaks model and data independent membership inference attacks and defenses on machine learning models"
    - "twitter for sparking a movement reddit for sharing the moment metoo through the lens of social media"
    - "is saki delicious the food perception gap on instagram and its relation to health"

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)