most citedClassMind: Scaling Classroom Observation and Instructional Feedback with Multimodal AI

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.HC20251 cited

ClassMind: Scaling Classroom Observation and Instructional Feedback with Multimodal AI

Ao Qu, Yuxi Wen, Jiayi Zhang +6

Classroom observation -- one of the most effective methods for teacher development -- remains limited due to high costs and a shortage of expert coaches. We present ClassMind, an A…

cs.CL2025

MEM1: Learning to Synergize Memory and Reasoning for Efficient Long-Horizon Agents

Zijian Zhou, Ao Qu, Zhaoxuan Wu +6

Modern language agents must operate over long-horizon, multi-turn interactions, where they retrieve external information, adapt to observations, and answer interdependent queries.…

cs.LG2025

From Street Views to Urban Science: Discovering Road Safety Factors with Multimodal Large Language Models

Yihong Tang, Ao Qu, Xujing Yu +4

Urban and transportation research has long sought to uncover statistically meaningful relationships between key variables and societal outcomes such as road safety, to generate act…

cs.CY2025

Simulating Society Requires Simulating Thought

Chance Jiajie Li, Jiayi Wu, Zhenze Mo +10

Simulating society with large language models (LLMs), we argue, requires more than generating plausible behavior; it demands cognitively grounded reasoning that is structured, revi…

cs.CL2025

Reimagining Urban Science: Scaling Causal Inference with Large Language Models

Yutong Xia, Ao Qu, Yunhan Zheng +8

Urban causal research is essential for understanding the complex, dynamic processes that shape cities and for informing evidence-based policies. However, current practices are ofte…