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Author

Lijun Wu

OpenAlex ID: A5139745386
MinerU2.5: A Decoupled Vision-Language Model for Efficient High-Resolution Document Parsing
2026 · Junbo Niu, Zheng Liu, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting · 9
A Strategic Coordination Framework of Small LMs Matches Large LMs in Data Synthesis
2025 · Xin Gao, Qizhi Pei, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting · 2
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Tracing the Roots: A Multi-Agent Framework for Uncovering Data Lineage in Post-Training LLMs
2026 · Yu Li, Xiaoran Shang, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting
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REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at Once
2026 · Zhuoshi Pan, Qizhi Pei, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting
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R3: End-to-End Reasoning-based Planning for Multi-step Retrosynthesis via Reinforcement Learning
2026 · YiFei Wang, Qizhi Pei, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting
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Data Pollination: An Emergent Ecological Process Driving AI Population Evolution
2026 · Shufang Xie, Qizhi Pei, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting
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ChartVerse: Scaling Chart Reasoning via Reliable Programmatic Synthesis from Scratch
2026 · Zheng Liu, Honglin Lin, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting
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The Data Frontier for Large Language Models: Selection, Synthesis, and Tools
2026 · Lijun Wu, Wentao Zhang, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting
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Works count: 8
Citation count: 11
H-index: 2
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