Tao Ji
Tao Ji has 2 papers in our library, in 2019–2025, most of them on Dependency parsing, Language models & pretraining; often with Caishuang Huang, Junjie Ye, Man Lan.
OpenAlex · ORCID · h-index 15 · 96 works · 816 citations OpenAlex, 2026-10-14
📄 2 works in our library · 🔗 Cited 143 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #6460
Affiliations
Fields, topics and concepts
📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksArts and Humanities · 1 workLanguage and Linguistics · 1 workEngineering · 1 workComputer Vision and Pattern Recognition · 1 workControl and Systems Engineering · 1 work
🧭 Topics 2Research subjects and languages the work is about.Dependency parsing · 1 workLanguage models & pretraining · 1 work
Works by year
2020s
2010s
Papers
- Graph-based Dependency Parsing with Graph Neural Networks (2019 · 94 citations)
Graph-based dependency parsers score every possible head–dependent pair and then decode a tree. Their accuracy depends heavily on how each word is represented. Earlier encoders, such as BiLSTMs and the biaffine parser of Dozat and Manning (2017), mostly capture first-order parent–child information. Ji, Wu and Lan add… - ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios (2025 · 35 citations)
Most benchmarks for tool use by large language models only check whether a model picks the expected API. That approach works only when correct answers can be fixed in advance, and it reveals little about the skills behind successful tool use. ToolEyes addresses both gaps. The authors define seven realistic scenarios…
All works
- Graph-based Dependency Parsing with Graph Neural NetworksAnnual Meeting of the Association for Computational Linguistics (ACL)Tao Ji, Yuanbin Wu, Man Lan2019 · 94 citations
- Secrets of RLHF in Large Language Models Part II: Reward Modeling ↗arXiv:2401.06080 · no summary yetBinghai Wang et al.2024 · 72 citations
- ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world ScenariosInternational Conference on Computational Linguistics (COLING)Junjie Ye, Guanyu Li, SongYang Gao, et al.2025 · 35 citations
- StepCoder: Improving Code Generation with Reinforcement Learning from Compiler Feedback ↗Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetShihan Dou et al.2024 · 32 citations
Co-authors here
- Caishuang Huang
- Junjie Ye
- Man Lan
- Qi Zhang
- Shihan Dou
- SongYang Gao
- Tao Gui
- Xiaoran Fan
- Xuanjing Huang
- Yilong Wu
- Yuanbin Wu
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×2: ACL 2019
- International Conference on Computational Linguistics (COLING): COLING 2025
Cited by
Updated
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