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 "mathqa towards interpretable math word problem solving with operation based formalisms"):
  Abstract: We introduce a large-scale dataset of math word problems and an interpretable neural math problem solver that learns to map problems to operation programs. Due to annotation challenges, current datasets in this domain have been either relatively small in scale or did not offer precise operational annotations over diverse problem types. We introduce a new representation language to model precise operation programs corresponding to each math problem that aim to improve both the performance and the interpretability of the learned models. Using this representation language, our new dataset, MathQA, significantly enhances the AQuA dataset with fully-specified operational programs. We additionally introduce a neural sequence-to-program model enhanced with automatic problem categorization. Our experiments show improvements over competitive baselines in our MathQA as well as the AQuA dataset. The results are still significantly lower than human performance indicating that the dataset poses new challenges for future research. Our dataset is available at: https://math-qa.github.io/math-QA/

Includes members:
  Member "a meaning based statistical english math word problem solver":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "text2math end to end parsing text into math expressions")
  Member "mapping to declarative knowledge for word problem solving":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "text2math end to end parsing text into math expressions")
  Member "learning structured natural language representations for semantic parsing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "exploring neural models for parsing natural language into first order logic")
  Member "program induction by rationale generation learning to solve and explain algebraic word problems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "drop a reading comprehension benchmark requiring discrete reasoning over paragraphs")
  Member "neural generation of regular expressions from natural language with minimal domain knowledge":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "don t paraphrase detect rapid and effective data collection for semantic parsing")
  Member "annotating derivations a new evaluation strategy and dataset for algebra word problems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "analysing mathematical reasoning abilities of neural models")
  Member "adam a method for stochastic optimization":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "learning to map sentences to logical form structured classification with probabilistic categorial grammars":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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.CL(Computation and Language)