---
title: "Who cites Xiangpeng Wei — page 3 — 772 papers of our library"
description: "772 papers of the Elamur Research library cite the works of Xiangpeng Wei, found in their bibliographies · page 3 of 3 · 201–275; the most cited first."
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---
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# Who cites Xiangpeng Wei

868 citations of their works from 772 papers of our library (of the 149,439 whose bibliographies we read) · 275 with a page here, the most cited first · page 3 of 3 · 201–275 · [← Xiangpeng Wei](https://md.research.elamur.ai/free/en/authors/xiangpeng-wei/)

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

201. **[Beyond the Context Window: Scaling Agentic RL via End-to-end Optimized Context Compression](https://md.research.elamur.ai/free/en/papers/lu-2026-beyond-context-window-scaling-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Miao Lu, Weiwei Sun, Weihua Du, et al.*2026*
202. **[Calibration-Aware Policy Optimization for Reasoning LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-calibration-aware-policy-optimization-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqi Wang, Xingzhou Lou, Meiqi Wu, et al.*2026*
203. **[ChemVLR: Prioritizing Reasoning in Perception for Chemical Vision-Language Understanding](https://md.research.elamur.ai/free/en/papers/zhao-2026-chemvlr-prioritizing-reasoning-perception-chemical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuanle Zhao, Xinyuan Cai, Xiang Cheng, et al.*2026*
204. **[CodeRM-NT: Reward Model for Code RL without Unit Tests](https://md.research.elamur.ai/free/en/papers/xia-2026-coderm-nt-reward-model-code/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiao Xia, Dan Zhang, Tianrui Sun*2026*
205. **[Complex-IF and Beyond: Expert Rubrics for RLVR](https://md.research.elamur.ai/free/en/papers/mehta-2026-complex-if-beyond-expert-rubrics/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Sushant Mehta, Liudas Panavas, Eleanor Fleming, et al.*2026*
206. [**Controllable Spoken Dialogue Generation: An LLM-Driven Grading System for K-12 Non-Native English Learners arXiv:2604.22542**Haidong Yuan, Haokun Zhao, Wanshi Xu, et al.*2026*](https://md.research.elamur.ai/free/en/papers/yuan-2026-controllable-spoken-dialogue-generation-llm/)
207. **[Crossing the Reward Bridge: Expanding Reinforcement Learning with Verifiable Rewards Across Diverse Domains](https://md.research.elamur.ai/free/en/papers/su-2026-crossing-reward-bridge-expanding-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Su, Dian Yu, Linfeng Song, et al.*2026*
208. **[Curing Miracle Steps in LLM Mathematical Reasoning with Rubric Rewards](https://md.research.elamur.ai/free/en/papers/yuan-2026-curing-miracle-steps-llm-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youliang Yuan, Qiuyang Mang, Jingbang Chen, et al.*2026*
209. **[Data Efficient RLVR via Off-Policy Influence Guidance](https://md.research.elamur.ai/free/en/papers/zhu-2026-data-efficient-rlvr-off-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Erle Zhu, Dazhi Jiang, Yuan Wang, et al.*2026*
210. **[DeepICD-R1: Medical Reasoning through Hierarchical Rewards and Unsupervised Distillation](https://md.research.elamur.ai/free/en/papers/rohr-2026-deepicd-r1-medical-reasoning-through/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Tom Röhr, Thomas Maximilian Josef Steffek, Roman Teucher, et al.*2026*
211. **[Don't Tell the Answer, Truly Guide the Reasoning During RL Rollouts](https://md.research.elamur.ai/free/en/papers/wang-2026-don-t-tell-answer-truly/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyi Wang, Jinyi Han, Zishang Jiang, et al.*2026*
212. **[EfficientTool: A Cost-Effective Aligning Framework for Tool-Conditioned Agents in SME Scenarios](https://md.research.elamur.ai/free/en/papers/mu-2026-efficienttool-cost-effective-aligning-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanqi Mu, Bingfeng Pi, Defei Xia, et al.*2026*
213. **[Entropy Scheduling in Reinforcement Learning for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-entropy-scheduling-reinforcement-learning-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingjin Wang, Howe Tissue, Lu Wang, et al.*2026*
214. **[Evo-PI: Aligning Medical Reasoning via Evolving Principle-Guided Supervision](https://md.research.elamur.ai/free/en/papers/zheng-2026-evo-pi-aligning-medical-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xianda Zheng, Huan Gao, Meng-Fen Chiang, et al.*2026*
215. **[Experience-driven Multi-turn Reinforcement Learning for GUI Agents](https://md.research.elamur.ai/free/en/papers/lu-2026-experience-driven-multi-turn-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxi Lu, Jiabo Ye, Fei Tang, et al.*2026*
216. **[Exploiting Tree Structure for Credit Assignment in Reinforcement Learning with Large Language Models](https://md.research.elamur.ai/free/en/papers/tran-2026-exploiting-tree-structure-credit-assignment/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hieu Tran, Zonghai Yao, Hong yu*2026*
217. **[Exploration-Exploitation Reshaping towards Efficient Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/shi-2026-exploration-exploitation-reshaping-efficient-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yufeng Shi, Weilin Luo, Yuxiang Zhang, et al.*2026*
218. **[FeedTrans: Enhance Machine Translation via Feedback](https://md.research.elamur.ai/free/en/papers/sun-2026-feedtrans-enhance-machine-translation-feedback/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zengkui Sun, Jiali Zeng, Jiaan Wang, et al.*2026*
219. **[From Isolated Scoring to Collaborative Ranking: A Comparison-Native Framework for LLM-Based Paper Evaluation](https://md.research.elamur.ai/free/en/papers/zheng-2026-isolated-scoring-collaborative-ranking-comparison/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pujun Zheng, Jiacheng Yao, Jinquan Zheng, et al.*2026*
220. **[From Short Video to Clickable Search: RLVR-Enabled Listwise Query Suggestion with Retrieval-Augmented Context](https://md.research.elamur.ai/free/en/papers/tian-2026-short-video-clickable-search-rlvr/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingkai Tian, Xuye, Long Meng, et al.*2026*
221. **[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*
222. **[Generalization in Graph Reasoning: A Systematic Comparison of LLM Training Approaches](https://md.research.elamur.ai/free/en/papers/shirai-2026-generalization-graph-reasoning-systematic-comparison/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Sola Shirai, Kavitha Srinivas, Julian Dolby, et al.*2026*
223. **[GeometryZero: Advancing Geometry Solving via Group Contrastive Policy Optimization](https://md.research.elamur.ai/free/en/papers/wang-2026-geometryzero-advancing-geometry-solving-group/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yikun Wang, Yibin Wang, Dianyi Wang, et al.*2026*
224. **[Good Reasoning Makes Good Demonstrations: Implicit Reasoning Quality Supervision via In-Context Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mei-2026-good-reasoning-makes-good-demonstrations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tiehua Mei, Minxuan Lv, Leiyu Pan, et al.*2026*
225. **[How Can Synthetic Data Improve Multilingual Language Model Pretraining? A Data Quality Perspective](https://md.research.elamur.ai/free/en/papers/zhu-2026-how-can-synthetic-data-improve/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tongyao Zhu, Qian Liu, Chang Ma, et al.*2026*
226. **[HTMR: Hybrid Token Masking Reinforcement Learning with Verifiable Rewards for Event Argument Extraction with Multi-Perspective Reasoning](https://md.research.elamur.ai/free/en/papers/luo-2026-htmr-hybrid-token-masking-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianwen Luo, Yongkang Jin, Yu Hong, et al.*2026*
227. **[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*
228. **[Improving Retrieval-Augmented Generation without Taxonomy-based Error Categorization](https://md.research.elamur.ai/free/en/papers/zhang-2026-improving-retrieval-augmented-generation-without/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gongbo Zhang, Yifan Peng, Chunhua Weng*2026*
229. **[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*
230. **[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*
231. **[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*
232. **[Lang2Act: Fine-Grained Visual Reasoning through Self-Emergent Linguistic Toolchains](https://md.research.elamur.ai/free/en/papers/xiong-2026-lang2act-fine-grained-visual-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuqi Xiong, Chunyi Peng, Zhipeng Xu, et al.*2026*
233. **[Language-Aware Token Boosting: LLM Language Confusion Reduction Without Tuning](https://md.research.elamur.ai/free/en/papers/ukarapol-2026-language-aware-token-boosting-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Trapoom Ukarapol, Pakhapoom Sarapat, Nut Chukamphaeng*2026*
234. **[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*
235. **[Learning from Mistakes: Negative Reasoning Samples Enhance Out-of-Domain Generalization](https://md.research.elamur.ai/free/en/papers/xueyun-2026-learning-mistakes-negative-reasoning-samples/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tian Xueyun, MingHua Ma, Bingbing Xu, et al.*2026*
236. **[LEPO: Latent Reasoning Policy Optimization for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-lepo-latent-reasoning-policy-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuyan Zhou, Jiarui Yu, Hande Dong, et al.*2026*
237. **[LoopCoder: Scaling Code Intelligence via Looped Language Models](https://md.research.elamur.ai/free/en/papers/yang-2026-loopcoder-scaling-code-intelligence-looped/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jian Yang, Wei Zhang, Shuyue Guo, et al.*2026*
238. **[LoRE: Enhancing Search Relevance with Progressive Chain-of-Thought and Preference Alignment](https://md.research.elamur.ai/free/en/papers/lu-2026-lore-enhancing-search-relevance-progressive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenji Lu, Zhuo Chen, Hui Zhao, et al.*2026*
239. **[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*
240. **[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*
241. **[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*
242. **[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*
243. **[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*
244. **[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*
245. **[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*
246. **[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*
247. **[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*
248. **[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*
249. **[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*
250. **[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*
251. **[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*
252. **[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*
253. **[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*
254. **[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*
255. **[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*
256. **[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*
257. **[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*
258. **[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*
259. **[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*
260. **[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*
261. **[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*
262. **[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*
263. **[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*
264. **[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*
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