---
title: "Who cites Pei Chu — page 2 — 573 papers of our library"
description: "573 papers of the Elamur Research library cite the works of Pei Chu, found in their bibliographies · page 2 of 2 · 101–159; the most cited first."
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---
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# Who cites Pei Chu

595 citations of their works from 573 papers of our library (of the 149,439 whose bibliographies we read) · 159 with a page here, the most cited first · page 2 of 2 · 101–159 · [← Pei Chu](https://md.research.elamur.ai/free/en/authors/pei-chu/)

[← prev](https://md.research.elamur.ai/free/en/authors/pei-chu/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/pei-chu/cited-by/) **2**

101. **[V-MAGE: A Game Evaluation Framework for Assessing Vision-Centric Capabilities in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-v-mage-game-evaluation-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangxi Zheng, Linjie Li, Zhengyuan Yang, et al.*2026 · 2 citations*
102. [**Benchmarking Vision Language Models on German Factual Data arXiv:2504.11108**Rene Peinl, Vincent Tischler*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/peinl-2025-benchmarking-vision-language-models-german/)
103. **[AiraXiv: An AI-Driven Open-Access Platform for Human and AI Scientists](https://md.research.elamur.ai/free/en/papers/pan-2026-airaxiv-ai-driven-open-access/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junshu Pan, Panzhong Lu, Yixuan Weng, et al.*2026 · 1 citation*
104. **[CaTS-Bench: Can Language Models Describe Time Series?](https://md.research.elamur.ai/free/en/papers/zhou-2026-cats-bench-can-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Luca Zhou, Pratham Yashwante, Marshall Fisher, et al.*2026 · 1 citation*
105. **[CodeEvo: Interaction-Driven Synthesis of Code-centric Data through Hybrid and Iterative Feedback](https://md.research.elamur.ai/free/en/papers/sun-2026-codeevo-interaction-driven-synthesis-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiushi Sun, Jingyang Gong, Lei Li, et al.*2026 · 1 citation*
106. **[CoReTab: Improving Multimodal Table Understanding with Code-driven Reasoning](https://md.research.elamur.ai/free/en/papers/nguyen-2026-coretab-improving-multimodal-table-understanding/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Van-Quang Nguyen, Takayuki Okatani*2026 · 1 citation*
107. **[How to Set the Learning Rate for Large-Scale Pre-training?](https://md.research.elamur.ai/free/en/papers/zhou-2026-how-set-learning-rate-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yunhua Zhou, Shuhao Xing, Junhao Huang, et al.*2026 · 1 citation*
108. **[IF-RewardBench: Benchmarking Judge Models for Instruction-Following Evaluation](https://md.research.elamur.ai/free/en/papers/wen-2026-if-rewardbench-benchmarking-judge-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bosi Wen, Yilin Niu, Cunxiang Wang, et al.*2026 · 1 citation*
109. **[SharVeT: Similarity-aware Parameter Sharing with Vector-based Tuning for Efficient LLM Compression](https://md.research.elamur.ai/free/en/papers/yun-2026-sharvet-similarity-aware-parameter-sharing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jeongin Yun, Jaeri Lee, Jongjin Kim, et al.*2026 · 1 citation*
110. **[SPD-Faith Bench: Diagnosing and Improving Faithfulness in Chain-of-Thought for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/lv-2026-spd-faith-bench-diagnosing-improving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weijiang Lv, Yaoxuan Feng, Xiaobo Xia, et al.*2026 · 1 citation*
111. **[VisTW: Benchmarking Vision-Language Models for Taiwanese Mandarin in Taiwan](https://md.research.elamur.ai/free/en/papers/tam-2026-vistw-benchmarking-vision-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhi Rui Tam, Yung-Yu Shih, Yen-Wei Lee, et al.*2026 · 1 citation*
112. **[When Helpers Become Hazards: A Benchmark for Analyzing Multimodal LLM-Powered Safety in Daily Life](https://md.research.elamur.ai/free/en/papers/lou-2026-when-helpers-become-hazards-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyue Lou, Xu Jinan, Jingyi Yin, et al.*2026 · 1 citation*
113. [**Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving arXiv:2512.10739**Yuzhe Gu, Songyang Gao, Zijian Wu, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/gu-2025-intern-s1-mo-long/)
114. [**GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs? arXiv:2412.10056**Zhikai Lei, Tianyi Liang, Hanglei Hu, et al.*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/lei-2024-gaokao-eval-high-scores/)
115. [**A Cascade Reinforcement Learning Strategy for Efficiently Enhancing the Reasoning Ability of Multimodal Large Language Models (高效提升多模态大语言模型推理能力的级联强化学习策略) Acta Automatica Sinica (自动化学报)**Weiyun Wang (王玮赟), Hengjun Pu (蒲恒骏), Linglin Jing (景凌林), et al.*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-cascade-reinforcement-learning/)
116. **[A Scalable Multi-LLM Collaboration System with Retrieval-based Selection and Exploration-Exploitation-Driven Enhancement](https://md.research.elamur.ai/free/en/papers/tang-2026-scalable-multi-llm-collaboration-system/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shengji Tang, Jianjian Cao, Weihao Lin, et al.*2026*
117. **[Adapting Vision-Language Models for E-commerce Understanding at Scale](https://md.research.elamur.ai/free/en/papers/nulli-2026-adapting-vision-language-models-e/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Matteo Nulli, Vladimir Orshulevich, Tala Bazazo, et al.*2026*
118. **[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*
119. **[AICA-Bench: Holistically Examining the Capabilities of VLMs in Affective Image Content Analysis](https://md.research.elamur.ai/free/en/papers/she-2026-aica-bench-holistically-examining-capabilities/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dong She, Xianrong Yao, Liqun Chen, et al.*2026*
120. **[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*
121. **[Attention as Selector: Unlocking VLM Attention for Long Document Page Retrieval](https://md.research.elamur.ai/free/en/papers/zhu-2026-attention-as-selector-unlocking-vlm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minfeng Zhu, Linxin Bao, Wei Chen, et al.*2026*
122. **[Benchmarking Temporal Reasoning and Alignment Across Chinese Dynasties](https://md.research.elamur.ai/free/en/papers/wang-2026-benchmarking-temporal-reasoning-alignment-across/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zhenglin Wang, Jialong Wu, Pengfei Li, et al.*2026*
123. **[ContextCheck: Sentence-Level Faithfulness Verification with Context-Aware Disambiguation](https://md.research.elamur.ai/free/en/papers/yin-2026-contextcheck-sentence-level-faithfulness-verification/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yueqin Yin, Yaxi Li, Xin Liu, et al.*2026*
124. **[DaMo: Data Mixing Optimizer in Fine-tuning Multimodal LLMs for Mobile Phone Agents](https://md.research.elamur.ai/free/en/papers/shi-2026-damo-data-mixing-optimizer-fine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Shi, Jun Yang, Ni Yang, et al.*2026*
125. **[Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation](https://md.research.elamur.ai/free/en/papers/ye-2026-deep-reporter-deep-research-grounded/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangda Ye, Kuicai Dong, Xie Zhifei, et al.*2026*
126. **[Detecting AI-Generated Content on Social Media with Multi-modal Language Models](https://md.research.elamur.ai/free/en/papers/yang-2026-detecting-ai-generated-content-social/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenyang Yang, Shen Yan, Yibo Yang, et al.*2026*
127. **[Distilling Long-CoT Reasoning through Collaborative Step-wise Multi-Teacher Decoding](https://md.research.elamur.ai/free/en/papers/yun-2026-distilling-long-cot-reasoning-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taewon Yun, Jisu Shin, Jeonghwan Choi, et al.*2026*
128. **[EvaHan 2026 Ancient Books Multimodal OCR and Layout Analysis System Technical Report](https://md.research.elamur.ai/free/en/papers/zheng-2026-evahan-2026-ancient-books-multimodal/) [Workshop on Language Technologies for Historical and Ancient Languages @ LREC](https://md.research.elamur.ai/free/en/venues/lt4hala/)**Chenrui Zheng*2026*
129. **[Evaluating Discriminability of Vision-Language Models](https://md.research.elamur.ai/free/en/papers/muraoka-2026-evaluating-discriminability-vision-language-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Masayasu Muraoka, Naoaki Okazaki*2026*
130. **[Exploring Fine-Tuning for In-Context Retrieval and Efficient KV-Caching in Long-Context Language Models](https://md.research.elamur.ai/free/en/papers/molfese-2026-exploring-fine-tuning-context-retrieval/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Francesco Maria Molfese, Momchil Hardalov, Rexhina Blloshmi, et al.*2026*
131. **[Fico: Evaluating Vision-Language Models under Visual Fidelity and Compression at Scale](https://md.research.elamur.ai/free/en/papers/tu-2026-fico-evaluating-vision-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianhong Tu, Nicholas Crispino, Kyle Montgomery, et al.*2026*
132. **[Fixing Semantic Blind Spots in Anchor Tokens of dMLLMs](https://md.research.elamur.ai/free/en/papers/xu-2026-fixing-semantic-blind-spots-anchor/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ruixuan Xu, Jiexi Xu, Qiyan Zhao, et al.*2026*
133. **[Flow-Based Page Unique Semantic Mapping Architecture for Document Visual Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2026-flow-based-page-unique-semantic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haosen Wang, Jing Xiao, Chaochao Du, et al.*2026*
134. **[From Conversation to Evaluation: Benchmarking LLMs on Development Knowledge via SimpleDevQA](https://md.research.elamur.ai/free/en/papers/zhang-2026-conversation-evaluation-benchmarking-llms-development/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jing Zhang, Lianghong Guo, Yanlin Wang, et al.*2026*
135. **[From Detection to Understanding: Multi-Turn Reasoning for Video Misinformation Analysis](https://md.research.elamur.ai/free/en/papers/zeng-2026-detection-understanding-multi-turn-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhi Zeng, Jiaying Wu, Minnan Luo, et al.*2026*
136. **[From Words to Pixels: A Comprehensive Survey on Large Language Models in Visual Segmentation](https://md.research.elamur.ai/free/en/papers/wang-2026-words-pixels-comprehensive-survey-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yizhou Wang, Mang Tik Chiu, Lingzhi Zhang, et al.*2026*
137. **[GenProve: Learning to Generate Text with Fine-Grained Provenance](https://md.research.elamur.ai/free/en/papers/wei-2026-genprove-learning-generate-text-fine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingxuan Wei, Xingyue Wang, Yanghaoyu Liao, et al.*2026*
138. **[Hard to Read, Easy to Jailbreak: How Visual Degradation Bypasses MLLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/song-2026-hard-read-easy-jailbreak-how/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhixue Song, Boyan Han, Yiwei Wang, et al.*2026*
139. **[Market-Bench: Benchmarking Large Language Models on Economic and Trade Competition](https://md.research.elamur.ai/free/en/papers/zheng-2026-market-bench-benchmarking-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yushuo Zheng, Huiyu Duan, Zicheng Zhang, et al.*2026*
140. **[Memory-Driven Role-Playing: Evaluation and Enhancement of Persona Knowledge Utilization in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-memory-driven-role-playing-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Wang, Haoyang You, Yang Zhang, et al.*2026*
141. **[MirrorCAPTCHA: Wild CAPTCHA, Wild Distribution, Wild Web-based Platform Meet Multimodal LLM Agents](https://md.research.elamur.ai/free/en/papers/wu-2026-mirrorcaptcha-wild-captcha-wild-distribution/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangyu Wu, Yuwei Hu, Tianyu Cui, et al.*2026*
142. **[MONETA: Multimodal Industry Classification through Geographic Information with Multi Agent Systems](https://md.research.elamur.ai/free/en/papers/yuksel-2026-moneta-multimodal-industry-classification-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arda Yüksel, Gabriel Thiem, Susanne Walter, et al.*2026*
143. **[MSEarth: A Multimodal Benchmark for Earth Science Phenomenon Discovery with MLLMs](https://md.research.elamur.ai/free/en/papers/zhao-2026-msearth-multimodal-benchmark-earth-science/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangyu Zhao, Wanghan Xu, Bo Liu, et al.*2026*
144. **[MuSe: Multi-Stage Graph Reasoning via Vision-Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-muse-multi-stage-graph-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanyu Wang, Xu Chu, Zhijie Tan, et al.*2026*
145. **[M³-VQA: A Benchmark for Multimodal, Multi-Entity, Multi-Hop Visual Question Answering](https://md.research.elamur.ai/free/en/papers/ma-2026-m-3-vqa-benchmark-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiatong Ma, Longteng Guo, Yuchen Liu, et al.*2026*
146. **[OptiVerse: A Comprehensive Benchmark towards Optimization Problem Solving](https://md.research.elamur.ai/free/en/papers/zhang-2026-optiverse-comprehensive-benchmark-optimization-problem/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyu Zhang, Boxuan Zhang, Yuchen Wan, et al.*2026*
147. **[PaperScope: A Multi-Modal Multi-Document Benchmark for Agentic Deep Research Across Massive Scientific Papers](https://md.research.elamur.ai/free/en/papers/xiong-2026-paperscope-multi-modal-multi-document/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lei Xiong, Huaying Yuan, Zheng Liu, et al.*2026*
148. **[PlanE: Meta Planning of Data, Tuning, and Inference for Extractive-based LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-plane-meta-planning-data-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiacheng Wang, Weiyan Zhang, Guangya Yu*2026*
149. **[PodBench: A Comprehensive Benchmark for Instruction-Aware Audio-Oriented Podcast Script Generation](https://md.research.elamur.ai/free/en/papers/xu-2026-podbench-comprehensive-benchmark-instruction-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenning Xu, Mao Zheng, Mingyu Zheng, et al.*2026*
150. **[PRISM: Probing Reasoning, Instruction, and Source Memory in LLM Hallucinations](https://md.research.elamur.ai/free/en/papers/wu-2026-prism-probing-reasoning-instruction-source/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhe Wu, Guangyu Wang, Yuran Chen, et al.*2026*
151. **[RADAR: A Reasoning-Guided Attribution Framework for Explainable Visual Data Analysis](https://md.research.elamur.ai/free/en/papers/rani-2026-radar-reasoning-guided-attribution-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anku Rani, Aparna Garimella, Apoorv Saxena, et al.*2026*
152. **[RIPRAG: Hack a Black-box Retrieval-Augmented Generation Question-Answering System with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/xi-2026-riprag-hack-black-box-retrieval/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Meng Xi, Sihan Lv, Yechen Jin, et al.*2026*
153. **[RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-routemoa-dynamic-routing-without-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jize Wang, Han Wu, Zhiyuan You, et al.*2026*
154. **[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*
155. **[SDiaReward: Modeling and Benchmarking Spoken Dialogue Rewards with Modality and Colloquialness](https://md.research.elamur.ai/free/en/papers/lu-2026-sdiareward-modeling-benchmarking-spoken-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyu Lu, Yuhan Wang, Fan Zhuo, et al.*2026*
156. **[Simple-VGC: Enhancing Visual Grounding in Multimodal Reasoning via Adaptive Tool Composition](https://md.research.elamur.ai/free/en/papers/wang-2026-simple-vgc-enhancing-visual-grounding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ye Wang, Qianglong Chen, Siyuan Wang, et al.*2026*
157. **[ViX-Ray: A Vietnamese Chest X-Ray Dataset for Vision-Language Models](https://md.research.elamur.ai/free/en/papers/nguyen-2026-vix-ray-vietnamese-chest-x/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Duy Vu Minh Nguyen, Chinh Thanh Truong, Trần Hoàng Phúc, et al.*2026*
158. **[When Good OCR Is Not Enough: Benchmarking OCR Robustness for Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/sun-2026-when-good-ocr-is-not/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lin Sun, Wangdexian, Jingang Huang, et al.*2026*
159. **[WildReward: Learning Reward Models from In-the-Wild Human Interactions](https://md.research.elamur.ai/free/en/papers/peng-2026-wildreward-learning-reward-models-wild/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.*2026*

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