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About

Heng Ji is a leading researcher in artificial intelligence, with a focus on advancing large language models (LLMs), multimedia learning, and AI-driven biomedical applications. Her work has significantly shaped how LLM agents interact with the world: her highly cited 2024 paper on "Executable Code Actions Elicit Better LLM Agents" (9 citations) introduced a paradigm shift by replacing rigid JSON-based action generation with executable code, enabling agents to more flexibly invoke tools and control robots for real-world tasks. In multimedia AI, Ji’s 2023 study on "Multimedia Generative Script Learning for Task Planning" (5 citations) pioneered the integration of visual historical states into goal-oriented script generation, enhancing robots’ ability to perform complex, stereotypical activities. Demonstrating her interdisciplinary impact, Ji’s 2025 work on "Artificial intelligence unlocks the future of oral organoid research" (4 citations) applies AI to overcome critical bottlenecks in organoid construction and data analysis, bridging computational methods with clinical translation. With a career marked by high-impact, cross-domain contributions, Heng Ji continues to push the boundaries of AI from foundational agent architectures to transformative biomedical tools.