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: "learning assisted theorem proving with millions of lemmas"
  Abstract: Large formal mathematical libraries consist of millions of atomic inference steps that give rise to a corresponding number of proved statements (lemmas). Analogously to the informal mathematical practice, only a tiny fraction of such statements is named and re-used in later proofs by formal mathematicians. In this work, we suggest and implement criteria defining the estimated usefulness of the HOL Light lemmas for proving further theorems. We use these criteria to mine the large inference graph of the lemmas in the HOL Light and Flyspeck libraries, adding up to millions of the best lemmas to the pool of statements that can be re-used in later proofs. We show that in combination with learning-based relevance filtering, such methods significantly strengthen automated theorem proving of new conjectures over large formal mathematical libraries such as Flyspeck.

Connected through hyperedge HE-1 (induced by source paper "holist an environment for machine learning of higher order theorem proving"):
  with members:
    - "gamepad a learning environment for theorem proving"
    - "reinforcement learning of theorem proving"
    - "deep network guided proof search"
    - "holstep a machine learning dataset for higher order logic theorem proving"
    - "tactictoe learning to reason with hol4 tactics"
    - "premise selection for theorem proving by deep graph embedding"
    - "squad 100 000 questions for machine comprehension of text"
    - "wavenet a generative model for raw audio"

Connected through hyperedge HE-2 (induced by source paper "learning to reason in large theories without imitation"):
  with members:
    - "reinforcement learning of theorem proving"
    - "premise selection for theorem proving by deep graph embedding"
    - "deepmath deep sequence models for premise selection"
    - "wavenet a generative model for raw audio"
    - "holophrasm a neural automated theorem prover for higher order logic"
    - "adam a method for stochastic optimization"
    - "premise selection for mathematics by corpus analysis and kernel methods"
    - "playing atari with deep reinforcement learning"

Connected through hyperedge HE-3 (induced by source paper "proof mining with dependent types"):
  with members:
    - "goal translation for a hammer for coq extended abstract"
    - "sepia search for proofs using inferred automata"
    - "hipster integrating theory exploration in a proof assistant"
    - "mining state based models from proof corpora"
    - "recycling proof patterns in coq case studies"
    - "lemma mining over hol light"
    - "proof pattern recognition and lemma discovery in acl2"
    - "machine learning in proof general interfacing interfaces"

Connected through hyperedge HE-4 (induced by source paper "tactictoe learning to reason with hol4 tactics"):
  with members:
    - "internal guidance for satallax"
    - "sepia search for proofs using inferred automata"
    - "recycling proof patterns in coq case studies"
    - "blistr the blind strategymaker"
    - "machine learning in proof general interfacing interfaces"
    - "learning assisted automated reasoning with flyspeck"

Connected through hyperedge HE-5 (induced by source paper "certified connection tableaux proofs for hol light and tptp"):
  with members:
    - "premise selection and external provers for hol4"
    - "mizar 40 for mizar 40"
    - "machine learning of coq proof guidance first experiments"
    - "premise selection for mathematics by corpus analysis and kernel methods"
    - "hol y hammer online atp service for hol light"
    - "theorem proving in large formal mathematics as an emerging ai field"
    - "learning assisted automated reasoning with flyspeck"
    - "atp and presentation service for mizar formalizations"

Connected through hyperedge HE-6 (induced by source paper "developments in formal proofs"):
  with members:
    - "a formally verified proof of the central limit theorem"
    - "premise selection for mathematics by corpus analysis and kernel methods"
    - "hol y hammer online atp service for hol light"
    - "learning assisted automated reasoning with flyspeck"

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.AI(Artificial Intelligence)