--- title: "Who cites Self-Distillation Enables Continual — 62 citing papers" description: "62 papers of the Elamur Research library cite «Self-Distillation Enables Continual Learning», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/shenfeld-2026-self-distillation-enables-continual-learning/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/shenfeld-2026-self-distillation-enables-continual-learning/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Self-Distillation Enables Continual Learning](https://md.research.elamur.ai/free/en/papers/shenfeld-2026-self-distillation-enables-continual-learning/) / cited by # Who cites «Self-Distillation Enables Continual Learning» 62 papers of our library cite it (of the 149,439 whose bibliographies we read) · 14 with a page here, the most cited first · [← back to «Self-Distillation Enables Continual Learning»](https://md.research.elamur.ai/free/en/papers/shenfeld-2026-self-distillation-enables-continual-learning/) 1. [**Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models arXiv:2601.18734**Siyan Zhao, Zhihui Xie, Mengchen Liu, et al.*2026 · 97 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2026-self-distilled-reasoner-policy-self/) 2. [**Reinforcement Learning via Self-Distillation arXiv:2601.20802**Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.*2026 · 74 citations*](https://md.research.elamur.ai/free/en/papers/hubotter-2026-reinforcement-learning-self-distillation/) 3. [**Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe arXiv:2604.13016**Yaxuan Li, Yuxin Zuo, Bingxiang He, et al.*2026 · 58 citations*](https://md.research.elamur.ai/free/en/papers/li-2026-rethinking-policy-distillation-large-language/) 4. [**A Survey of On-Policy Distillation for Large Language Models arXiv:2604.00626**Mingyang Song, Mao Zheng*2026 · 41 citations*](https://md.research.elamur.ai/free/en/papers/song-2026-survey-policy-distillation-large-language/) 5. [**Self-Distilled RLVR arXiv:2604.03128**Chenxu Yang, Chuanyu Qin, Qingyi Si, et al.*2026 · 37 citations*](https://md.research.elamur.ai/free/en/papers/yang-2026-self-distilled-rlvr/) 6. [**On-Policy Context Distillation for Language Models arXiv:2602.12275**Tianzhu Ye, Li Dong, Xun Wu, et al.*2026 · 36 citations*](https://md.research.elamur.ai/free/en/papers/ye-2026-policy-context-distillation-language-models/) 7. [**Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy Distillation arXiv:2604.13010**Yecheng Wu, Song Han, Han Cai*2026 · 10 citations*](https://md.research.elamur.ai/free/en/papers/wu-2026-lightning-opd-efficient-post-training/) 8. [**KL for a KL: On-Policy Distillation with Control Variate Baseline arXiv:2605.07865**Minjae Oh, Sangjun Song, Gyubin Choi, et al.*2026 · 8 citations*](https://md.research.elamur.ai/free/en/papers/oh-2026-kl-kl-policy-distillation-control/) 9. [**Unmasking On-Policy Distillation: Where It Helps, Where It Hurts, and Why arXiv:2605.10889**Mohammadreza Armandpour, Fatih Ilhan, David Harrison, et al.*2026 · 7 citations*](https://md.research.elamur.ai/free/en/papers/armandpour-2026-unmasking-policy-distillation-where-helps/) 10. [**Asymmetric On-Policy Distillation: Bridging Exploitation and Imitation at the Token Level arXiv:2605.06387**Nan Jia, Haojin Yang, Xing Ma, et al.*2026 · 6 citations*](https://md.research.elamur.ai/free/en/papers/jia-2026-asymmetric-policy-distillation-bridging-exploitation/) 11. [**Uni-OPD: Unifying On-Policy Distillation with a Dual-Perspective Recipe arXiv:2605.03677**Wenjin Hou, Shangpin Peng, Weinong Wang, et al.*2026 · 6 citations*](https://md.research.elamur.ai/free/en/papers/hou-2026-uni-opd-unifying-policy-distillation/) 12. [**Self-Distilled Policy Gradient arXiv:2606.04036**Yifeng Liu, Shiyuan Zhang, Yifan Zhang, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/liu-2026-self-distilled-policy-gradient/) 13. **[Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment](https://md.research.elamur.ai/free/en/papers/yang-2026-which-reasoning-trajectories-teach-students/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuming Yang, Mingyoung Lai, Wanxu Zhao, et al.*2026 · 4 citations* 14. **[LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?](https://md.research.elamur.ai/free/en/papers/wang-2026-lightreasoner-can-small-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyuan Wang, Yankai Chen, Zhonghang Li, et al.*2026 · 1 citation* 48 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/shenfeld-2026-self-distillation-enables-continual-learning/) — Self-Distillation Enables Continual Learning