---
title: "Who cites Yanghua Peng — page 3 — 775 papers of our library"
description: "775 papers of the Elamur Research library cite the works of Yanghua Peng, found in their bibliographies · page 3 of 3 · 201–251; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yanghua-peng/cited-by/page/3/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/yanghua-peng/cited-by/page/3/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Yanghua Peng](https://md.research.elamur.ai/free/en/authors/yanghua-peng/) / [cited by](https://md.research.elamur.ai/free/en/authors/yanghua-peng/cited-by/) / page 3

# Who cites Yanghua Peng

817 citations of their works from 775 papers of our library (of the 149,439 whose bibliographies we read) · 251 with a page here, the most cited first · page 3 of 3 · 201–251 · [← Yanghua Peng](https://md.research.elamur.ai/free/en/authors/yanghua-peng/)

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

201. **[Generalizable LLM Learning of Graph Synthetic Data with Post-training Alignment](https://md.research.elamur.ai/free/en/papers/zhang-2026-generalizable-llm-learning-graph-synthetic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yizhuo Zhang, Heng Wang, Shangbin Feng, et al.*2026*
202. **[ICDAGENT: Empowering Agentic Large Language Models for Explainable Medical Coding](https://md.research.elamur.ai/free/en/papers/yin-2026-icdagent-empowering-agentic-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyi Yin, Yuanpu Cao, Ting Wang, et al.*2026*
203. **[ImpRIF: Stronger Implicit Reasoning Leads to Better Complex Instruction Following](https://md.research.elamur.ai/free/en/papers/yang-2026-imprif-stronger-implicit-reasoning-leads/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuancheng Yang, Lin Yang, Xu Wang, et al.*2026*
204. **[Improved Policy Optimization for Mixture-of-Experts Models: Importance Sampling and Rewarding from an Expert-Centric Perspective](https://md.research.elamur.ai/free/en/papers/qian-2026-improved-policy-optimization-mixture-experts/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yining Qian, Jinpeng Li, Fei Mi, et al.*2026*
205. **[Internalizing Multi-Agent Reasoning for Accurate and Efficient LLM-based Recommendation](https://md.research.elamur.ai/free/en/papers/wu-2026-internalizing-multi-agent-reasoning-accurate/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yang Wu, Haoze Wang, Qian Li, et al.*2026*
206. **[JanusMM: A Benchmark for Self-Deprecation Understanding in Real-World Multimodal Conversations](https://md.research.elamur.ai/free/en/papers/xu-2026-janusmm-benchmark-self-deprecation-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyi Xu, Bingguang Hao, Yongyi Xiong, et al.*2026*
207. **[Joint Optimization of Training Data and Policy in RLHF](https://md.research.elamur.ai/free/en/papers/yu-2026-joint-optimization-training-data-policy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuohao Yu, Jiali Zeng, Weizheng Gu, et al.*2026*
208. **[Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains](https://md.research.elamur.ai/free/en/papers/yuan-2026-knowledge-verification-exploring-rlvr-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhonghang Yuan, Zhefan Wang, Fang Hu, et al.*2026*
209. **[Learning from Cognition: Enhancing RL Efficiency for LLM Reasoning via Hierarchical Metacognitive Decomposition and Refinement](https://md.research.elamur.ai/free/en/papers/sun-2026-learning-cognition-enhancing-rl-efficiency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zexu Sun, Yongcheng Zeng, Erxue Min, et al.*2026*
210. **[Leveraging Outline-Optimized Generative Interactions and Critique for Self-Refining Outlines with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-leveraging-outline-optimized-generative-interactions/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hengwei Liu, Haoyuan Ma, Qingqing Lyu, et al.*2026*
211. **[MathSight: A Benchmark Exploring Have Vision-Language Models Really Seen in University-Level Mathematical Reasoning?](https://md.research.elamur.ai/free/en/papers/wang-2026-mathsight-benchmark-exploring-have-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuandong Wang, Yao Cui, Yuxin Zhao, et al.*2026*
212. **[MDocRAG-RL: Empowering Multi-Modal Document RAG via Complex Visual Reasoning with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-mdocrag-rl-empowering-multi-modal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhongyu Wang*2026*
213. **[Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding](https://md.research.elamur.ai/free/en/papers/wang-2026-measure-twice-click-once-co/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenkai Wang, Xiyun Li, Hongcan Guo, et al.*2026*
214. **[MemBuilder: Reinforcing LLMs for Long-Term Memory Construction via Attributed Dense Rewards](https://md.research.elamur.ai/free/en/papers/shen-2026-membuilder-reinforcing-llms-long-term/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyu Shen, Ziming Wu, Fuming Lai, et al.*2026*
215. **[MemSearcher: Iterative Memory Integration for Search Agent via End-to-End Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yuan-2026-memsearcher-iterative-memory-integration-search/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qianhao Yuan, Jie Lou, Zichao Li, et al.*2026*
216. **[Mitigating Context Interference for Reliable and Efficient Search Agents](https://md.research.elamur.ai/free/en/papers/xue-2026-mitigating-context-interference-reliable-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boyang Xue, Bin Wu, Shuofei Qiao, et al.*2026*
217. **[Mitigating Selection Bias in Large Language Models via Permutation-Aware GRPO](https://md.research.elamur.ai/free/en/papers/zheng-2026-mitigating-selection-bias-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinquan Zheng, Jia Yuan, Jiacheng Yao, et al.*2026*
218. **[MVP: Enhancing Video Large Language Models via Self-supervised Masked Video Prediction](https://md.research.elamur.ai/free/en/papers/sun-2026-mvp-enhancing-video-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaokun Sun, Zezhong Wu, Zewen Ding, et al.*2026*
219. **[OS-Symphony: A Holistic Framework for Robust and Generalist Computer-Using Agents](https://md.research.elamur.ai/free/en/papers/yang-2026-os-symphony-holistic-framework-robust/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bowen Yang, Kaiming Jin, Zhenyu Wu, et al.*2026*
220. **[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*
221. **[Pause or Fabricate? Training Language Models for Grounded Reasoning](https://md.research.elamur.ai/free/en/papers/qiu-2026-pause-or-fabricate-training-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiwen Qiu, Linjuan Wu, Yizhou Liu, et al.*2026*
222. **[PEGRL: Improving Machine Translation by Post-Editing Guided Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/shen-2026-pegrl-improving-machine-translation-post/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yunzhi Shen, Hao Zhou, Xin Huang, et al.*2026*
223. **[PlotGen-Bench: Evaluating VLMs on Generating Visualization Code from Diverse Plots across Multiple Libraries](https://md.research.elamur.ai/free/en/papers/zhao-2026-plotgen-bench-evaluating-vlms-generating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yi Zhao, Zhen Yang, Shuaiqi Duan, et al.*2026*
224. **[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*
225. **[PRIME: A Process-Outcome Alignment Benchmark for Verifiable Reasoning in Mathematics and Engineering](https://md.research.elamur.ai/free/en/papers/wang-2026-prime-process-outcome-alignment-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangfeng Wang, Hangyu Guo, Yanlin Lai, et al.*2026*
226. **[Reflective RAG: Self-Evaluation Driven Strategy Optimization in Agentic Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wu-2026-reflective-rag-self-evaluation-driven/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haiyan Wu, Chenchen Wang, Chaoqun Sun, et al.*2026*
227. **[ReflectRM: Boosting Generative Reward Models via Self-Reflection within a Unified Judgment Framework](https://md.research.elamur.ai/free/en/papers/qin-2026-reflectrm-boosting-generative-reward-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kai Qin, Liangxin Liu, Yu Liang, et al.*2026*
228. **[Reliable Use of Lemmas via Eligibility Reasoning and Section-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/xu-2026-reliable-use-lemmas-eligibility-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhikun Xu, Xiaodong Yu, Ben Zhou, et al.*2026*
229. **[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*
230. **[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*
231. **[ROMA: Real-time Omni-Multimodal Assistant with Interactive Streaming Understanding](https://md.research.elamur.ai/free/en/papers/xueyun-2026-roma-real-time-omni-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tian Xueyun, Wei Li, Bingbing Xu, et al.*2026*
232. **[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*
233. **[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*
234. **[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*
235. **[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*
236. **[Stabilizing Efficient Reasoning with Step-Level Advantage Selection](https://md.research.elamur.ai/free/en/papers/wang-2026-stabilizing-efficient-reasoning-step-level/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Han Wang, Xiaodong Yu, Jialian Wu, et al.*2026*
237. **[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*
238. **[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*
239. **[Text-Guided Multi-Scale Frequency Representation Adaptation](https://md.research.elamur.ai/free/en/papers/yan-2026-text-guided-multi-scale-frequency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weicai Yan, Xinhua Ma, Wang Lin, et al.*2026*
240. **[TPS-Bench: Evaluating AI Agents' Tool Planning & Scheduling Abilities in Compounding Tasks](https://md.research.elamur.ai/free/en/papers/xu-2026-tps-bench-evaluating-ai-agents/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanwen Xu, Xuyao Huang, Yuzhe Liu, et al.*2026*
241. **[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*
242. **[TVWorld: Foundations for Remote-Control TV Agents](https://md.research.elamur.ai/free/en/papers/ma-2026-tvworld-foundations-remote-control-tv/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhantao Ma, Quanfeng Lu, Shuai Zhong, et al.*2026*
243. **[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*
244. **[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*
245. **[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*
246. **[Verifying the Subjective: Structured Multilingual Rewards for Low-Resource Alignment](https://md.research.elamur.ai/free/en/papers/sha-2026-verifying-subjective-structured-multilingual-rewards/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiu Sha, Mengxiao Zhu*2026*
247. **[VL-Calibration: Decoupled Confidence Calibration for Large Vision-Language Models Reasoning](https://md.research.elamur.ai/free/en/papers/xiao-2026-vl-calibration-decoupled-confidence-calibration/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenyi Xiao, Xinchi XU, Leilei Gan*2026*
248. **[When LLMs Read Tables Carelessly: Measuring and Reducing Data Referencing Errors](https://md.research.elamur.ai/free/en/papers/yang-2026-when-llms-read-tables-carelessly/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuqing Yang, Qi Zhu, Zhen Han, et al.*2026*
249. **[Why Does Reinforcement Learning Generalize? A Feature-Level Mechanistic Study of Post-Training in Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-why-does-reinforcement-learning-generalize/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dan Shi, Zhuowen Han, Simon Ostermann, et al.*2026*
250. **[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*
251. **[Survey on Key Technologies for Large Language Model Pre-training Systems (大语言模型预训练系统关键技术综述)](https://md.research.elamur.ai/free/en/papers/gao-2025-key-technologies-large/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yanjie Gao (高彦杰), Yueguo Chen (陈跃国)*2025*

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

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

- [← back to](https://md.research.elamur.ai/free/en/authors/yanghua-peng/) — Yanghua Peng