--- title: "Who cites Skywork-R1V3 Technical Report — 6 citing papers" description: "6 papers of the Elamur Research library cite «Skywork-R1V3 Technical Report», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/shen-2025-skywork-r1v3-technical-report/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/shen-2025-skywork-r1v3-technical-report/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Skywork-R1V3 Technical Report](https://md.research.elamur.ai/free/en/papers/shen-2025-skywork-r1v3-technical-report/) / cited by # Who cites «Skywork-R1V3 Technical Report» 6 papers of our library cite it (of the 149,439 whose bibliographies we read) · 3 with a page here, the most cited first · [← back to «Skywork-R1V3 Technical Report»](https://md.research.elamur.ai/free/en/papers/shen-2025-skywork-r1v3-technical-report/) 1. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency arXiv:2508.18265**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/) 2. [**Step-Audio-R1 Technical Report arXiv:2511.15848**Fei Tian, Xiangyu Tony Zhang, Yuxin Zhang, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/tian-2025-step-audio-r1-technical/) 3. [**A Cascade Reinforcement Learning Strategy for Efficiently Enhancing the Reasoning Ability of Multimodal Large Language Models (高效提升多模态大语言模型推理能力的级联强化学习策略) Acta Automatica Sinica (自动化学报)**Weiyun Wang (王玮赟), Hengjun Pu (蒲恒骏), Linglin Jing (景凌林), et al.*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-cascade-reinforcement-learning/) 3 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/shen-2025-skywork-r1v3-technical-report/) — Skywork-R1V3 Technical Report