🔗 Who cites «VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning»

36 papers of our library cite it (of the 149,439 whose bibliographies we read) · 17 with a page here, the most cited first · ← back to «VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning»

1. InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and EfficiencyarXiv:2508.18265Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.2025 · 179 citations
2. Beyond Distillation: Pushing the Limits of Medical LLM Reasoning with Minimalist Rule-Based RLarXiv:2505.17952Che Liu, Haozhe Wang, Jiazhen Pan, et al.2025 · 10 citations
3. Skywork R1V2: Multimodal Hybrid Reinforcement Learning for ReasoningarXiv:2504.16656Peiyu Wang, Yichen Wei, Yi Peng, et al.2025 · 10 citations
4. Infinity-Parser: Layout-Aware Reinforcement Learning with High-quality Document Parsing DatasetFindings of the Association for Computational LinguisticsBaode Wang, Biao Wu, Weizhen Li, et al.2026 · 4 citations
5. Forest Before Trees: Latent Superposition for Efficient Visual ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Yubo Wang, Juntian Zhang, Yichen Wu, et al.2026 · 3 citations
6. AdaTooler-V: Adaptive Tool-Use for Images and VideosFindings of the Association for Computational LinguisticsChaoyang Wang, Kaituo Feng, Dongyang Chen, et al.2026 · 2 citations
7. Visually-Guided Policy Optimization for Multimodal ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Zengbin Wang, Feng Xiong, Liang Lin, et al.2026 · 1 citation
8. A Survey of Multimodal Mathematical Reasoning: From Perception, Alignment to ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Tianyu Yang, Sihong Wu, Yilun Zhao, et al.2026
9. Benchmarking Deflection and Hallucination in Large Vision-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Nicholas Moratelli, Christopher Davis, Leonardo F. R. Ribeiro, et al.2026
10. Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning ModelsFindings of the Association for Computational LinguisticsHoang Phan, Xianjun Yang, Yuanshun Yao, et al.2026
11. Does RLVR Extend Reasoning Boundaries? Investigating Capability Expansion in Vision-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Minghe Shen, Zhuo Zhi, Chonghan Liu, et al.2026
12. DORA: A Dual-Objective Reinforcement Learning Framework for Effective and Efficient Multimodal Agentic SearchAnnual Meeting of the Association for Computational Linguistics (ACL)Guangming Qin, Yuhao Deng, Yukun Zhao, et al.2026
13. Journey Before Destination: On the importance of Visual Faithfulness in Slow ThinkingConference of the European Chapter of the Association for Computational Linguistics (EACL)Rheeya Uppaal, Phu Mon Htut, Min Bai, et al.2026
14. MDocRAG-RL: Empowering Multi-Modal Document RAG via Complex Visual Reasoning with Reinforcement LearningFindings of the Association for Computational LinguisticsZhongyu Wang2026
15. MedKInstruct: A Multimodal Knowledge Graph Based Framework for Multi-Hop and Hard-Negative Instruction Data Synthesis in MedVQAFindings of the Association for Computational LinguisticsYinan Wu, Jihang Jin, Xuhao Bao, et al.2026
16. Multimodal LLMs Do Not Compose Skills Optimally across ModalitiesLanguage Resources and Evaluation Conference (LREC)Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune2026
17. VL-Calibration: Decoupled Confidence Calibration for Large Vision-Language Models ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Wenyi Xiao, Xinchi XU, Leilei Gan2026

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