---
title: "Who cites Qiying Yu — page 3 — 654 papers of our library"
description: "654 papers of the Elamur Research library cite the works of Qiying Yu, found in their bibliographies · page 3 of 3 · 201–233; the most cited first."
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---
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# Who cites Qiying Yu

719 citations of their works from 654 papers of our library (of the 149,439 whose bibliographies we read) · 233 with a page here, the most cited first · page 3 of 3 · 201–233 · [← Qiying Yu](https://md.research.elamur.ai/free/en/authors/qiying-yu/)

[← prev](https://md.research.elamur.ai/free/en/authors/qiying-yu/cited-by/page/2/) [1](https://md.research.elamur.ai/free/en/authors/qiying-yu/cited-by/) [2](https://md.research.elamur.ai/free/en/authors/qiying-yu/cited-by/page/2/) **3**

201. **[N-GRPO: Embedding-Level Neighbor Mixing for Enhanced Policy Optimization](https://md.research.elamur.ai/free/en/papers/zhu-2026-n-grpo-embedding-level-neighbor/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xukun Zhu, Hang Yu, Peng Di, et al.*2026*
202. **[On the Editability of Delta Parameters in Post-Trained Models](https://md.research.elamur.ai/free/en/papers/tang-2026-editability-delta-parameters-post-trained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiaoyu Tang, Le Yu, Bowen Yu, et al.*2026*
203. **[PARIF: Pushing the Pareto Frontier of Instruction Following and Reasoning with Curriculum Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mu-2026-parif-pushing-pareto-frontier-instruction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rongchuan Mu, Zexin Wang, Qianyu Wang, et al.*2026*
204. **[Plug-and-Play Data Module for Code RL: Adaptive Ambiguity Replay](https://md.research.elamur.ai/free/en/papers/zhang-2026-plug-play-data-module-code/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianqing Zhang, Wei Xia, Zhezheng Hao, et al.*2026*
205. **[Policy-Guided Stepwise Action Planning for Controllable LLM Reasoning](https://md.research.elamur.ai/free/en/papers/zhou-2026-policy-guided-stepwise-action-planning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianpeng Zhou, Qisheng Hu, Jiahai Wang, et al.*2026*
206. **[Preference Optimization for Review Question Generation Improves Writing Quality](https://md.research.elamur.ai/free/en/papers/sharma-2026-preference-optimization-review-question-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Karun Sharma, Vidushee Vats, Shengzhi LI, et al.*2026*
207. **[RADO: Reasoning Audit-Driven Optimization for Rigorous Reasoning in High-Stakes Domains](https://md.research.elamur.ai/free/en/papers/tan-2026-rado-reasoning-audit-driven-optimization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhijie Tan, Xu Chu, Guanyu Wang, et al.*2026*
208. **[Reasoning-Aware AIGC Detection via Alignment and Reinforcement](https://md.research.elamur.ai/free/en/papers/wang-2026-reasoning-aware-aigc-detection-alignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhao Wang, Max Xiong, Jianxun Lian, et al.*2026*
209. **[Reflect, Rewrite, Repeat: How Simple Arithmetic Enables Advanced Reasoning in Small Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-reflect-rewrite-repeat-how-simple/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mengdie Flora Wang, Haochen Xie, Mun Young Kim, et al.*2026*
210. **[RepoDistill: Distilling Repository Knowledge through Compression-Aware Budget Allocation and Policy Optimization](https://md.research.elamur.ai/free/en/papers/yin-2026-repodistill-distilling-repository-knowledge-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xin Yin, Zixiang Ding, Yiang Zhang, et al.*2026*
211. **[Revisiting Entropy Regularization: Adaptive Coefficient Unlocks Its Potential for LLM Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/zhang-2026-revisiting-entropy-regularization-adaptive-coefficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaoyun Zhang, Xiaojian Yuan, Di Huang, et al.*2026*
212. **[RIFT: Repurposing Negative Samples via Reward-Informed Fine-Tuning](https://md.research.elamur.ai/free/en/papers/liu-2026-rift-repurposing-negative-samples-reward/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zehua Liu, Shuqi Liu, Tao Zhong, et al.*2026*
213. **[RiT: Rubrics-in-Thinking Reinforcement Learning for Improved Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/tian-2026-rit-rubrics-thinking-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaobin Tian, Shuai Yuan, Muyun Ding, et al.*2026*
214. **[R³: End-to-End Reasoning-based Planning for Multi-step Retrosynthesis via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-r-3-end-end-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YiFei Wang, Qizhi Pei, Jiangtao Feng, et al.*2026*
215. **[ScaleBox: Enabling High-Fidelity and Scalable Code Verification for Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-scalebox-enabling-high-fidelity-scalable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiasheng Zheng, Xin Zheng, Boxi Cao, et al.*2026*
216. **[Shorten After You're Right: Lazy Length Penalties for Reasoning RL](https://md.research.elamur.ai/free/en/papers/yuan-2026-shorten-after-you-re-right/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Danlong Yuan, Tian Xie, Shaohan Huang, et al.*2026*
217. **[Simplify-Pro: A Two-level and Progressive LLM-based Framework for Auto Long Text Simplification](https://md.research.elamur.ai/free/en/papers/zhou-2026-simplify-pro-two-level-progressive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peng Zhou, Guangxin Li, Xiaoying Huang, et al.*2026*
218. **[STAPO: Selective Trajectory-Aware Policy Optimization for LLM Agent Training](https://md.research.elamur.ai/free/en/papers/qi-2026-stapo-selective-trajectory-aware-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiuyi Qi, Tian Liang, Mutian Bao, et al.*2026*
219. **[Tailored Primitive Initialization is the Secret Key to Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yao-2026-tailored-primitive-initialization-is-secret/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yihang Yao, Guangtao Zeng, Raina Wu, et al.*2026*
220. **[Targeted Exploration via Unified Entropy Control for Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-targeted-exploration-unified-entropy-control/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chen Wang, Lai Wei, Yanzhi Zhang, et al.*2026*
221. **[TARo: Token-level Adaptive Routing for LLM Test-time Alignment](https://md.research.elamur.ai/free/en/papers/rai-2026-taro-token-level-adaptive-routing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Arushi Rai, Qiang Zhang, Hanqing Zeng, et al.*2026*
222. **[Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation](https://md.research.elamur.ai/free/en/papers/mule-2026-teaching-language-models-forecast-research/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Srujan P Mule, Aniketh Garikaparthi, Manasi Patwardhan*2026*
223. **[The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAG](https://md.research.elamur.ai/free/en/papers/zhou-2026-retrieval-bottleneck-scaling-laws-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shu Zhou, Jinman Leng, Yufei Song, et al.*2026*
224. **[TRAC: Teacher-Guided Token Reward with Adaptive Calibration for Robust Policy Optimization](https://md.research.elamur.ai/free/en/papers/wu-2026-trac-teacher-guided-token-reward/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sitong Wu, Haoru Tan, Xichen Zhang, et al.*2026*
225. **[Translation with Thought: Difficulty-Adaptive Reasoning via Reinforcement Learning for Multi-Domain Machine Translation](https://md.research.elamur.ai/free/en/papers/ye-2026-translation-thought-difficulty-adaptive-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongshi Ye, Biao Fu, Chongxuan Huang, et al.*2026*
226. **[Understanding and Mitigating Spurious Signal Amplification in Test-Time Reinforcement Learning for Math Reasoning](https://md.research.elamur.ai/free/en/papers/yu-2026-understanding-mitigating-spurious-signal-amplification/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yongcan Yu, Lingxiao He, Jian Liang, et al.*2026*
227. **[Understanding and Preventing Entropy Collapse in RLVR with On-Policy Entropy Flow Optimization](https://md.research.elamur.ai/free/en/papers/xu-2026-understanding-preventing-entropy-collapse-rlvr/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Huimin Xu, Shuai Zhao, Xiaobao Wu, et al.*2026*
228. **[V-RoLoRA: RLVR-Driven MoE Routing for Steerable Pluralistic Alignment](https://md.research.elamur.ai/free/en/papers/wang-2026-v-rolora-rlvr-driven-moe/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jing Wang, Yaomin Wu, Yinglin Wang, et al.*2026*
229. **[Verifier-Free RL for LLMs via Intrinsic Gradient-Norm Reward](https://md.research.elamur.ai/free/en/papers/wen-2026-verifier-free-rl-llms-intrinsic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuexiang Wen, Hang Yu, Linchao Zhu, et al.*2026*
230. **[When Efficiency Becomes a Vulnerability: Computational Cost Attacks on WebAgents](https://md.research.elamur.ai/free/en/papers/ning-2026-when-efficiency-becomes-vulnerability-computational/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liang-Bo Ning, Yuchen Zhu, Heqing Huang, et al.*2026*
231. **[When to Trust Tools? Adaptive Tool Trust Calibration For Tool-Integrated Math Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2026-when-trust-tools-adaptive-tool/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ruotao Xu, Yixin Ji, Yu Luo, et al.*2026*
232. **[WildSci: Advancing Scientific Reasoning from In-the-Wild Literature](https://md.research.elamur.ai/free/en/papers/liu-2026-wildsci-advancing-scientific-reasoning-wild/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengxiao Liu, Deepak Nathani, Zekun Li, et al.*2026*
233. **[Generating Questions Under Discussion with Reinforcement Learning using Ranking and Scoring for Reward and Evaluation](https://md.research.elamur.ai/free/en/papers/han-2025-generating-questions-under-discussion-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kelvin Han, Claire Gardent*2025*

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421 more citing papers of our library have no page here yet.

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