Yizhuo Zhang
Yizhuo Zhang has 2 papers in our library, in 2026, most of them on Language models & pretraining, Vision & language; often with Heng Wang, Kejuan Yang, Shangbin Feng.
OpenAlex · ORCID · h-index 14 · 100 works · 729 citations OpenAlex, 2026-10-14
Affiliations
🔬Institute of High Energy PhysicsBeijing ·
China2023–2026 · 43 papers🎓Zhengzhou UniversityZhengzhou ·
China2023–2026 · 42 papers🎓Liaoning Normal UniversityDalian ·
China2023–2026 · 41 papers🎓University of South ChinaHengyang ·
China2023–2026 · 41 papers🎓University of Science and Technology of ChinaHefei ·
China2023–2026 · 35 papers🎓Changzhou UniversityChangzhou ·
China2024–2026 · 3 papers🎓Jilin UniversityChangchun ·
China2025–2026 · 3 papers🎓Nankai UniversityTianjin ·
China2024–2026 · 2 papers🎓Henan Normal UniversityXinxiang ·
China2026 · 1 paper🎓North China Electric Power UniversityBeijing ·
China2026 · 1 paper
Fields, topics and concepts
📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksComputer Vision and Pattern Recognition · 2 worksLanguage and Linguistics · 2 works
🧭 Topics 2Research subjects and languages the work is about.Language models & pretraining · 2 worksVision & language · 1 work
Works by year
2020s
Papers
- Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment (2026)
Earlier work improved LLM graph reasoning by supervised fine-tuning (SFT) on synthetic graph puzzles. That helps with algorithmic problems, which classical algorithms already solve exactly, but it does not reliably carry over to real tasks with hidden graph structure. The authors test whether post-training alignment… - UNIVID: Unified Vision-Language Model for Video Moderation (2026)
Short-video platforms usually moderate content with a large collection of separate classifiers, one per policy.
Co-authors here
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
Updated
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