Mina Rhee

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Total Citations

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About

Mina Rhee is a researcher in artificial intelligence and robotics, specializing in natural language understanding for human-robot interaction. Her work focuses on bridging the gap between how humans communicate and how robots interpret commands in complex, real-world environments. Rhee’s key contribution lies in developing methods for grounding natural language instructions into semantic goal representations, enabling robots to abstract and generalize commands beyond rote execution. Her most-cited paper, "Grounding natural language instructions to semantic goal representations for abstraction and generalization" (2018, 19 citations), introduces a framework that allows robots to understand both action-oriented and goal-oriented instructions, a critical step toward more adaptable autonomous systems. In her earlier work, "A Tale of Two DRAGGNs: A Hybrid Approach for Interpreting Action-Oriented and Goal-Oriented Instructions" (2017), she proposed a hybrid model that distinguishes between commands specifying explicit actions versus target states, addressing a fundamental challenge in robotic instruction following. Though her citation counts are modest, Rhee’s research is foundational for creating robots that can operate alongside humans in unpredictable settings, making her a promising voice in the field of interactive AI.