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: "iris a conversational agent for complex tasks"
  Abstract: Today's conversational agents are restricted to simple standalone commands. In this paper, we present Iris, an agent that draws on human conversational strategies to combine commands, allowing it to perform more complex tasks that it has not been explicitly designed to support: for example, composing one command to "plot a histogram" with another to first "log-transform the data". To enable this complexity, we introduce a domain specific language that transforms commands into automata that Iris can compose, sequence, and execute dynamically by interacting with a user through natural language, as well as a conversational type system that manages what kinds of commands can be combined. We have designed Iris to help users with data science tasks, a domain that requires support for command combination. In evaluation, we find that data scientists complete a predictive modeling task significantly faster (2.6 times speedup) with Iris than a modern non-conversational programming environment. Iris supports the same kinds of commands as today's agents, but empowers users to weave together these commands to accomplish complex goals.

Connected through hyperedge HE-1 (induced by source paper "flowsense a natural language interface for visual data exploration within a dataflow system"):
  with members:
    - "seq2sql generating structured queries from natural language using reinforcement learning"
    - "recent trends in deep learning based natural language processing"
    - "a brief survey of text mining classification clustering and extraction techniques"
    - "compositional semantic parsing on semi structured tables"

Connected through hyperedge HE-2 (induced by source paper "pumice a multi modal agent that learns concepts and conditionals from natural language and demonstrations"):
  with members:
    - "learning to mine aligned code and natural language pairs from stack overflow"
    - "a syntactic neural model for general purpose code generation"
    - "compositional semantic parsing on semi structured tables"

Connected through hyperedge HE-3 (induced by source paper "understanding chatbot mediated task management"):
  with members:
    - "calendar help designing a workflow based scheduling agent with humans in the loop"

Connected through hyperedge HE-4 (induced by source paper "dialectic enhancing text input fields with automatic feedback to improve social content writing quality"):
  with members:
    - "adversarial generation of natural language"
    - "rationalizing neural predictions"
    - "winning arguments interaction dynamics and persuasion strategies in good faith online discussions"
    - "inferring networks of substitutable and complementary products"
    - "can cascades be predicted"
    - "how to ask for a favor a case study on the success of altruistic requests"

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.HC(Human-Computer Interaction)