@article{hao2026,
title = {ToolForge: A Data Synthesis Pipeline for Multi-Hop, Multi-Turn, and Self-Reflective Tool-Use Data},
author = {Chen, Hao and Zhou, Shunyuan and Hu, Zhexin and Chai, Jiajun and He, Hang and Yang, Haocheng and Wang, Xiaohan and Lin, Wei and Wang, Tianyu and Zhao, Zhuofeng and Yin, Guojun},
journal = {Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing},
year = {2026},
month = {Jan},
}
Chen, Hao et al. (2026). ToolForge: A Data Synthesis Pipeline for Multi-Hop, Multi-Turn, and Self-Reflective Tool-Use Data. Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing.
Chen, Hao, et al.. "ToolForge: A Data Synthesis Pipeline for Multi-Hop, Multi-Turn, and Self-Reflective Tool-Use Data." Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing, 2026.
Chen, Hao, et al.. "ToolForge: A Data Synthesis Pipeline for Multi-Hop, Multi-Turn, and Self-Reflective Tool-Use Data." Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing (2026).
Chen, Hao et al., 2026. ToolForge: A Data Synthesis Pipeline for Multi-Hop, Multi-Turn, and Self-Reflective Tool-Use Data. Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing.
TY - JOUR
TI - ToolForge: A Data Synthesis Pipeline for Multi-Hop, Multi-Turn, and Self-Reflective Tool-Use Data
AU - Chen, Hao
AU - Zhou, Shunyuan
AU - Hu, Zhexin
AU - Chai, Jiajun
AU - He, Hang
AU - Yang, Haocheng
AU - Wang, Xiaohan
AU - Lin, Wei
AU - Wang, Tianyu
AU - Zhao, Zhuofeng
AU - Yin, Guojun
PY - 2026
JO - Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing
ER -