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portfolio
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publications
QG-SMS: Enhancing Test Item Analysis via Student Modeling and Simulation
Published in Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL), 2025
This paper develops a student modeling approach for question generation to enhance test item analysis through simulation.
Recommended citation: B. Nguyen, T. Du, M. Yu, L. Angrave, and M. Jiang. (2025). "QG-SMS: Enhancing Test Item Analysis via Student Modeling and Simulation." Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL).
Characterizing Language Use in a Collaborative Situated Game
Published in arXiv preprint arXiv:2512.03381, 2025
This paper analyzes situated language use and ad-hoc convention formation within a large-scale corpus collected from a virtual 3D environment.
Recommended citation: N. Tomlin, N. Zhou, E. Fleisig, L. Chen, T. Wright, L. Vinh, L.X. Ma, S. Eisape, T. Du, T. Zhang, A. Koller, A. Suhr. (2025). "Characterizing Language Use in a Collaborative Situated Game." arXiv preprint arXiv:2512.03381.
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Agent KB: A Hierarchical Memory Framework for Cross-Domain Agentic Problem Solving
Published in ICML 2025 Workshop on Collaborative and Federated Agentic Workflows, 2025
This paper introduces a hierarchical memory framework that enables agents to leverage cross-domain experience for improved problem-solving capabilities.
Recommended citation: X. Tang, T. Qin, T. Peng, Z. Zhou, D. Shao, T. Du, X. Wei, H. Zhu, G. Zhang, et al. (2025). "Agent KB: A Hierarchical Memory Framework for Cross-Domain Agentic Problem Solving." ICML 2025 Workshop on Collaborative and Federated Agentic Workflows.
ROCKET: Residual-Oriented Multi-Layer Alignment for Spatially-Aware Vision-Language-Action Models
Published in arXiv preprint arXiv:2602.17951, 2026
This paper introduces ROCKET, a novel multi-layer alignment framework that enhances spatial awareness in Vision-Language-Action models through residual-oriented techniques.
Recommended citation: G. Sun, T. Du, K. Feng, C. Luo, X. Ding, Z. Shen, Z. Wang, Y. He, A. Li. (2026). "ROCKET: Residual-Oriented Multi-Layer Alignment for Spatially-Aware Vision-Language-Action Models." arXiv preprint arXiv:2602.17951.
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Vision-Language-Action in Robotics: A Survey of Datasets, Benchmarks, and Data Engines
Published in Transactions on Machine Learning Research (TMLR), 2026
A comprehensive survey examining the data infrastructure supporting Vision-Language-Action models in robotics, analyzing datasets, benchmarks, and data engines.
Recommended citation: Z. Wang, B. Wang, H. Zhang, T. Du, T. Chen, G. Sun, Y. He, Z. Shen, W. Ye, A. Li. (2026). "Vision-Language-Action in Robotics: A Survey of Datasets, Benchmarks, and Data Engines." Transactions on Machine Learning Research (TMLR).
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talks
Talk 1 on Relevant Topic in Your Field
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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