---
title: "Who cites Jiazhan Feng — page 3 — 795 papers of our library"
description: "795 papers of the Elamur Research library cite the works of Jiazhan Feng, found in their bibliographies · page 3 of 3 · 201–254; the most cited first."
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---
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# Who cites Jiazhan Feng

807 citations of their works from 795 papers of our library (of the 149,439 whose bibliographies we read) · 254 with a page here, the most cited first · page 3 of 3 · 201–254 · [← Jiazhan Feng](https://md.research.elamur.ai/free/en/authors/jiazhan-feng/)

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

201. **[CoVerRL: Breaking the Consensus Trap in Label-Free Reasoning via Generator-Verifier Co-Evolution](https://md.research.elamur.ai/free/en/papers/pan-2026-coverrl-breaking-consensus-trap-label/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Teng Pan, Yuchen Yan, Zixuan Wang, et al.*2026 · 1 citation*
202. **[Entropy Ratio Clipping as a Soft Global Constraint for Stable Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/su-2026-entropy-ratio-clipping-as-soft/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenpeng Su, Leiyu Pan, Minxuan Lv, et al.*2026 · 1 citation*
203. **[From Off-Policy to On-Policy: Enhancing GUI Agents via Bi-level Expert-to-Policy Assimilation](https://md.research.elamur.ai/free/en/papers/wang-2026-off-policy-policy-enhancing-gui/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zezhou Wang, Ziyun Zhang, Xiaoyi Zhang, et al.*2026 · 1 citation*
204. **[MatchTIR: Fine-Grained Supervision for Tool-Integrated Reasoning via Bipartite Matching](https://md.research.elamur.ai/free/en/papers/qu-2026-matchtir-fine-grained-supervision-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Changle Qu, Sunhao Dai, Hengyi Cai, et al.*2026 · 1 citation*
205. **[SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs](https://md.research.elamur.ai/free/en/papers/sun-2026-sepseq-training-free-framework-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Sun, Yu Liu, Lu Han, et al.*2026 · 1 citation*
206. **[Adversarial Yet Cooperative: Multi-Perspective Reasoning in Retrieved-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-adversarial-yet-cooperative-multi-perspective/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Can Xu, Lingyong Yan, Jiayi Wu, et al.*2026*
207. **[Agent-Dice: Disentangling Knowledge Updates via Geometric Consensus for Agent Continual Learning](https://md.research.elamur.ai/free/en/papers/wu-2026-agent-dice-disentangling-knowledge-updates/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheng Wu, Xingyu Lou, Xinbei Ma, et al.*2026*
208. **[AgentV-RL: Scaling Reward Modeling with Agentic Verifier](https://md.research.elamur.ai/free/en/papers/zhang-2026-agentv-rl-scaling-reward-modeling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiazheng Zhang, Ziche Fu, Zhiheng Xi, et al.*2026*
209. **[Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward Modeling](https://md.research.elamur.ai/free/en/papers/wang-2026-aligning-agents-planning-benchmark-trajectory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaxuan Wang, Yulan Hu, Wenjin Yang, et al.*2026*
210. **[ARM2: Adaptive Reasoning Model with Vision Understanding and Executable Code](https://md.research.elamur.ai/free/en/papers/xie-2026-arm2-adaptive-reasoning-model-vision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jian Xie, Zhendong Chu, Aoxiao Zhong, et al.*2026*
211. **[Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/phan-2026-beyond-reasoning-gains-mitigating-general/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hoang Phan, Xianjun Yang, Yuanshun Yao, et al.*2026*
212. **[Beyond Sample-Level Feedback: Using Reference-Level Feedback to Guide Data Synthesis](https://md.research.elamur.ai/free/en/papers/mehri-2026-beyond-sample-level-feedback-reference/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Shuhaib Mehri, Xiusi Chen, Heng Ji, et al.*2026*
213. **[Calibrated Progressive Distillation: Co-Designing Curriculum and Target Mixing for Knowledge Distillation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-calibrated-progressive-distillation-co-designing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mengxiang Zhang, Lingyuan Liu*2026*
214. **[CodeRise: Bootstrapping LLMs for Ultra Low-Resource Programming Languages via Progressive Self-Refinement Curriculum](https://md.research.elamur.ai/free/en/papers/wen-2026-coderise-bootstrapping-llms-ultra-low/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tengfei Wen, Xuanang Chen, Ben He, et al.*2026*
215. **[CompTab: A Comprehensive Benchmark for Real-World TableQA with Complex Reasoning and Irregular Tables](https://md.research.elamur.ai/free/en/papers/yang-2026-comptab-comprehensive-benchmark-real-world/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Yang, Wei Du, Jie Wang, et al.*2026*
216. **[DynamixSFT: Dynamic Mixture Optimization of Instruction Tuning Collections](https://md.research.elamur.ai/free/en/papers/shin-2026-dynamixsft-dynamic-mixture-optimization-instruction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haebin Shin, Lei Ji, Xiao Liu, et al.*2026*
217. **[GCIG: GraphRAG-based Cross-document Instruction Generation for Boosting LLM Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2026-gcig-graphrag-based-cross-document/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaoliang Xu, Huang Yuan, Junmei Wang, et al.*2026*
218. **[Generation of Instruction and Preference Dataset for Improving Japanese Instruction Following in LLMs](https://md.research.elamur.ai/free/en/papers/moriyama-2026-generation-instruction-preference-dataset-improving/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kei Moriyama, Takashi Kodama, Kouta Nakayama*2026*
219. **[GUI0: Self-Evolving Foundational GUI Agents in Super App Ecosystems](https://md.research.elamur.ai/free/en/papers/wang-2026-gui0-self-evolving-foundational-gui/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyi Wang, Wei Dai, Kyle Qiao, et al.*2026*
220. [**How Does "English (US)" Become the Default? Triangulating Structural Bias Towards American English Across the LLM Pipeline arXiv:2604.04204**Mir Tafseer Nayeem, Davood Rafiei*2026*](https://md.research.elamur.ai/free/en/papers/nayeem-2026-english-us-become-default-triangulating/)
221. **[HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs](https://md.research.elamur.ai/free/en/papers/peng-2026-hss-synth-humanities-social-sciences/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ru Peng, Tianyu Zhao, Xijun Gu, et al.*2026*
222. **[Inverting the Shield: Systematically Generating Safety Tests from Policy Specifications](https://md.research.elamur.ai/free/en/papers/lu-2026-inverting-shield-systematically-generating-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyue Lu, Xianglin Yang, Haijun Liu, et al.*2026*
223. **[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*
224. **[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*
225. **[Large-Scale Diverse Synthesis for Mid-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-large-scale-diverse-synthesis-mid/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuemiao Zhang, Chengying Tu, Can Ren, et al.*2026*
226. **[Learning from Evolving Training Dynamics: An Entropy-Maximizing Data Curation Strategy for LLM Supervised Post-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-learning-evolving-training-dynamics-entropy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengxiang Zhang, Lingyuan Liu*2026*
227. **[MAGNET: Towards Adaptive GUI Agents with Memory-Driven Knowledge Evolution](https://md.research.elamur.ai/free/en/papers/sun-2026-magnet-adaptive-gui-agents-memory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Libo Sun, Jiwen Zhang, Siyuan Wang, et al.*2026*
228. **[Mitigating Judgment Preference Bias in Large Language Models through Group-Based Polling](https://md.research.elamur.ai/free/en/papers/liu-2026-mitigating-judgment-preference-bias-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuliang Liu, Zhipeng Xu, Zhenghao Liu, et al.*2026*
229. **[Mixture-of-Minds: Multi-Agent Reinforcement Learning for Table Understanding](https://md.research.elamur.ai/free/en/papers/zhou-2026-mixture-minds-multi-agent-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhang Zhou, Mingrui Zhang, Ke Li, et al.*2026*
230. **[Multi-Constraint State Tracking with Negation: A Diagnostic Benchmark for LLM World Modeling](https://md.research.elamur.ai/free/en/papers/sar-2026-multi-constraint-state-tracking-negation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ayan Sar, Pranav Singh Puri, Sumit Aich, et al.*2026*
231. **[NaturalGAIA: A Verifiable Benchmark and Hierarchical Framework for Long-Horizon GUI Tasks](https://md.research.elamur.ai/free/en/papers/zheng-2026-naturalgaia-verifiable-benchmark-hierarchical-framework/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihan Zheng, Tianle Cui, Taoran Wang, et al.*2026*
232. **[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*
233. **[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*
234. **[PersonaTrace: Synthesizing Realistic Digital Footprints with LLM Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-personatrace-synthesizing-realistic-digital-footprints/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Minjia Wang, Yunfeng Wang, Xiao Ma, et al.*2026*
235. **[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*
236. **[PuzzleClone: A DSL-Powered Framework for Synthesizing Verifiable Data](https://md.research.elamur.ai/free/en/papers/xiong-2026-puzzleclone-dsl-powered-framework-synthesizing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Xiong, Yanwei Huang, Rongjunchen Zhang, et al.*2026*
237. **[QFinZero: A Unified Financial Toolchain for LLM-Based Trading Agents](https://md.research.elamur.ai/free/en/papers/luo-2026-qfinzero-unified-financial-toolchain-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haochen Luo, Yifan LI, Ho Tin Ko, et al.*2026*
238. **[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*
239. **[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*
240. **[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*
241. **[RV-Syn: Rational and Verifiable Mathematical Reasoning Data Synthesis based on Structured Function Library](https://md.research.elamur.ai/free/en/papers/wang-2026-rv-syn-rational-verifiable-mathematical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiapeng Wang, Jinhao Jiang, Zhiqiang Zhang, et al.*2026*
242. **[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*
243. **[SGA-MCTS: Decoupling Planning from Execution via Training-Free Atomic Experience Retrieval](https://md.research.elamur.ai/free/en/papers/xie-2026-sga-mcts-decoupling-planning-execution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xin Xie, Dongyun Xue, Wuguannan Yao, et al.*2026*
244. **[Suppressing Final Layer Hidden State Jumps in Transformer Pretraining](https://md.research.elamur.ai/free/en/papers/shibata-2026-suppressing-final-layer-hidden-state/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Keigo Shibata, Kazuki Yano, Ryosuke Takahashi, et al.*2026*
245. **[SynthAgent: Adapting Web Agents with Synthetic Supervision](https://md.research.elamur.ai/free/en/papers/wang-2026-synthagent-adapting-web-agents-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaoyang Wang, Yiming Liang, Xuchao Zhang, et al.*2026*
246. **[TARE: Lightweight Token-Aware Representation Editing for Fine-tuning Transformer-like Models](https://md.research.elamur.ai/free/en/papers/wang-2026-tare-lightweight-token-aware-representation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yulong Wang, Siyu Zhao*2026*
247. **[ToolCPT: Improving Tool Utilization in LLM Agents via Continuous Pre-training](https://md.research.elamur.ai/free/en/papers/yang-2026-toolcpt-improving-tool-utilization-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifan Yang, Jinghui Lu, Evadeng, et al.*2026*
248. **[Training Verifier to Assessing Complex Real-World Tool-Use Trajectories](https://md.research.elamur.ai/free/en/papers/sun-2026-training-verifier-assessing-complex-real/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Linzhuang Sun, Mingyang Chen, Hao Liang, et al.*2026*
249. **[TURTLEAI: Benchmarking Multimodal Models for Visual Programming in Turtle Graphics](https://md.research.elamur.ai/free/en/papers/wen-2026-turtleai-benchmarking-multimodal-models-visual/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chao Wen, Jacqueline Staub, Adish Singla*2026*
250. **[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*
251. **[Unveiling Inherent Visual Grounding in Multimodal LLMs for Text-Rich Images](https://md.research.elamur.ai/free/en/papers/zhou-2026-unveiling-inherent-visual-grounding-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shijie Zhou, Jihyung Kil, Ming Li, et al.*2026*
252. **[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*
253. **[We Are What We Repeatedly Do: Improving Long Context Instruction Following](https://md.research.elamur.ai/free/en/papers/robinette-2026-we-are-what-we-repeatedly/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Preston K Robinette, Andrew Hard, Swaroop Ramaswamy, et al.*2026*
254. **[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*

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