Papers by Huatao Li
Penetrative AI: Making LLMs Comprehend the Physical World (2024.findings-acl)
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| Challenge: | Recent advances in Large Language Models (LLMs) have demonstrated remarkable capabilities across a range of tasks. |
| Approach: | They explore how LLMs can be extended to interact with and reason about the physical world through IoT sensors and actuators, a concept that they call "Penetrative AI". |
| Outcome: | The proposed approach extends LLMs' capabilities to interact with and reason about the physical world through IoT sensors and actuators. |
TeachMaster: Generative Teaching via Code (2026.acl-industry)
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Yuheng Wang, Runde Yang, Lin Wu, Jie Zhang, Jingru Fan, Tianle Zhou, Ruoyu Fu, Huatao Li, Ruijie Shi, Siheng Chen, Weinan E, Chen Qian
| Challenge: | Existing methods for creating video content are limited by high costs and slow update cycles. |
| Approach: | They propose a paradigm shifting educators from manual creators to high-level directors who focus on pedagogical intents while agents handle execution. |
| Outcome: | The proposed framework reduces production costs to 0.3% of traditional course videos and provides a robust solution for scalable education. |