Yining Li
Yining Li has 4 papers in our library, in 2024–2026, most of them on Vision & language, Language models & pretraining, Legal AI; often with Songyang Zhang, Wenwei Zhang, Bin Wang.
OpenAlex · ORCID · h-index 35 · 161 works · 7,269 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 402 times in our library · 2 more in our library without a page yet · ⭐ Paper Stars ranking: #6100
Affiliations
Fields, topics and concepts
📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Computer Science · 4 worksComputer Vision and Pattern Recognition · 3 worksArts and Humanities · 2 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 2 worksSocial Sciences · 1 workLaw · 1 workPolitical Science and International Relations · 1 work
🧭 Topics 3Research subjects and languages the work is about.Vision & language · 2 worksLanguage models & pretraining · 1 workLegal AI · 1 work
Works by year
2020s
Papers
- InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model (2024 · 94 citations)
InternLM-XComposer2 is a vision-language model that both understands images and writes long documents mixing text and pictures. Its predecessor could only build such articles from a title. The new model accepts much richer inputs: outlines, detailed written requirements and reference images. - InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD (2024 · 54 citations)
Most large vision-language models (LVLMs) see images at low resolution, so they miss fine details in documents, charts, infographics and screenshots. - InternLM-Law: An Open Source Chinese Legal Large Language Model (2024 · 9 citations)
General-purpose LLMs often fail on Chinese legal questions, and earlier Chinese legal models were narrow, consultation-oriented, and built on older backbones. - RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents (2026)
Mixture-of-Agents (MoA) setups let several LLMs refine each other's answers over multiple layers. Because every model runs at every layer, this is expensive and slow. Sparse MoA adds an LLM judge to filter answers, but all models still have to generate before the judge sees them. Neither approach scales well to pools…
All works
- Dense Intrinsic Appearance Flow for Human Pose Transfer ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetYining Li, Chen Huang, Chen Change Loy2019 · 200 citations
- RTMO: Towards High-Performance One-Stage Real-Time Multi-Person Pose Estimation ↗arXiv:2312.07526 · no summary yetPeng Lu et al.2023 · 112 citations
- InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large ModelarXiv:2401.16420Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.2024 · 94 citations
- InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HDConference on Neural Information Processing Systems (NeurIPS)Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.2024 · 54 citations
- InternLM-Law: An Open Source Chinese Legal Large Language ModelarXiv:2406.14887Zhiwei Fei, Songyang Zhang, Xiaoyu Shen, et al.2024 · 9 citations
- RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Jize Wang, Han Wu, Zhiyuan You, et al.2026
Co-authors here
- Songyang Zhang ×4
- Wenwei Zhang ×3
- Bin Wang ×2
- Haodong Duan ×2
- Linke Ouyang ×2
- Maosong Cao ×2
- Pan Zhang ×2
- Xiaoyi Dong ×2
- Yuhang Cao ×2
- Yuhang Zang ×2
- Dacheng Tao
- Dahua Lin
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
- Conference on Neural Information Processing Systems (NeurIPS): NeurIPS 2024
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings
Cited by
Updated
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