human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "sequence to logic with copy and cache"):
  Abstract: Generating logical form equivalents of human language is a fresh way to employ neural architectures where long short-term memory effectively captures dependencies in both encoder and decoder units. #R##N#The logical form of the sequence usually preserves information from the natural language side in the form of similar tokens, and recently a copying mechanism has been proposed which increases the probability of outputting tokens from the source input through decoding. #R##N#In this paper we propose a caching mechanism as a more general form of the copying mechanism which also weighs all the words from the source vocabulary according to their relation to the current decoding context. #R##N#Our results confirm that the proposed method achieves improvements in sequence/token-level accuracy on sequence to logical form tasks. Further experiments on cross-domain adversarial attacks show substantial improvements when using the most influential examples of other domains for training.

Includes members:
  Member "seq2sql generating structured queries from natural language using reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scalable neural methods for reasoning with a symbolic knowledge base")
  Member "sqlnet generating structured queries from natural language without reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "schema2qa answering complex queries on the structured web with a neural model")
  Member "language to logical form with neural attention":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "unsupervised question decomposition for question answering")
  Member "data recombination for neural semantic parsing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exploring neural models for parsing natural language into first order logic")
  Member "sequence to sequence learning with neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")
  Member "learning to map sentences to logical form structured classification with probabilistic categorial grammars":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "break it down a question understanding benchmark")
  Member "learning dependency based compositional semantics":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "break it down a question understanding benchmark")

Question: Please tell me which class the source paper 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.LG(Machine Learning)