---
title: "Who cites Banghua Zhu — page 2 — 753 papers of our library"
description: "753 papers of the Elamur Research library cite the works of Banghua Zhu, found in their bibliographies · page 2 of 2 · 101–200; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/banghua-zhu/cited-by/page/2/"
---
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# Who cites Banghua Zhu

822 citations of their works from 753 papers of our library (of the 149,439 whose bibliographies we read) · 200 with a page here, the most cited first · page 2 of 2 · 101–200 · [← Banghua Zhu](https://md.research.elamur.ai/free/en/authors/banghua-zhu/)

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

101. **[SciArena: An Open Evaluation Platform for Non-Verifiable Scientific Literature-Grounded Tasks](https://md.research.elamur.ai/free/en/papers/zhao-2025-sciarena-open-evaluation-platform-non/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yilun Zhao, Kaiyan Zhang, Tiansheng Hu, et al.*2025 · 11 citations*
102. [**Yi-Lightning Technical Report arXiv:2412.01253**Alan Wake, Bei Chen, C.X. Lv, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/wake-2024-yi-lightning-technical-report/)
103. **[An Empirical Study of LLM-as-a-Judge: How Design Choices Impact Evaluation Reliability](https://md.research.elamur.ai/free/en/papers/yamauchi-2026-empirical-study-llm-as-judge/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Yusuke Yamauchi, Taro Yano, Masafumi Oyamada*2026 · 10 citations*
104. **[Beyond the Surface: Measuring Self-Preference in LLM Judgments](https://md.research.elamur.ai/free/en/papers/chen-2025-beyond-surface-measuring-self-preference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhi-Yuan Chen, Hao Wang, Xinyu Zhang, et al.*2025 · 10 citations*
105. [**Could Thinking Multilingually Empower LLM Reasoning? arXiv:2504.11833**Changjiang Gao, Xu Huang, Wenhao Zhu, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/gao-2025-could-thinking-multilingually-empower-llm/)
106. [**Hunyuan-TurboS: Advancing Large Language Models through Mamba-Transformer Synergy and Adaptive Chain-of-Thought arXiv:2505.15431**Tencent Hunyuan Team, Ao Liu, Botong Zhou, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-hunyuan-hunyuan-turbos-advancing-large/)
107. **[Too Late to Train, Too Early To Use? A Study on Necessity and Viability of Low-Resource Bengali LLMs](https://md.research.elamur.ai/free/en/papers/mahfuz-2025-too-late-train-too-early/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tamzeed Mahfuz, Satak Kumar Dey, Ruwad Naswan, et al.*2025 · 10 citations*
108. **[AdvancedIF: Rubric-Based Benchmarking and Reinforcement Learning for Advancing LLM Instruction Following](https://md.research.elamur.ai/free/en/papers/he-2026-advancedif-rubric-based-benchmarking-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yun He, Wenzhe Li, Hejia Zhang, et al.*2026 · 9 citations*
109. **[RubricHub: A Comprehensive and Highly Discriminative Rubric Dataset via Automated Coarse-to-Fine Generation](https://md.research.elamur.ai/free/en/papers/li-2026-rubrichub-comprehensive-highly-discriminative-rubric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sunzhu Li, Jiale Zhao, Huimin Ren, et al.*2026 · 9 citations*
110. **[WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback](https://md.research.elamur.ai/free/en/papers/shi-2026-wildfeedback-aligning-llms-situ-user/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taiwei Shi, Zhuoer Wang, Longqi Yang, et al.*2026 · 9 citations*
111. **[ChatBench: From Static Benchmarks to Human-AI Evaluation](https://md.research.elamur.ai/free/en/papers/chang-2025-chatbench-static-benchmarks-human-ai/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Serina Chang, Ashton Anderson, Jake M. Hofman*2025 · 9 citations*
112. **[Genius: A Generalizable and Purely Unsupervised Self-Training Framework For Advanced Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2025-genius-generalizable-purely-unsupervised-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangzhi Xu, Hang Yan, Chang Ma, et al.*2025 · 8 citations*
113. **[Selective Preference Optimization via Token-Level Reward Function Estimation](https://md.research.elamur.ai/free/en/papers/yang-2025-selective-preference-optimization-token-level/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kailai Yang, Zhiwei Liu, Qianqian Xie, et al.*2025 · 8 citations*
114. **[MetaScale: Test-Time Scaling with Evolving Meta-Thoughts](https://md.research.elamur.ai/free/en/papers/liu-2026-metascale-test-time-scaling-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qin Liu, Wenxuan Zhou, Nan Xu, et al.*2026 · 7 citations*
115. **[UltraIF: Advancing Instruction Following from the Wild](https://md.research.elamur.ai/free/en/papers/an-2025-ultraif-advancing-instruction-following-wild/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kaikai An, Li Sheng, Ganqu Cui, et al.*2025 · 7 citations*
116. **[Sentient Agent as a Judge: Evaluating Higher-Order Social Cognition in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-sentient-agent-as-judge-evaluating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bang Zhang, Ruotian Ma, Qingxuan Jiang, et al.*2026 · 6 citations*
117. [**rStar2-Agent: Agentic Reasoning Technical Report arXiv:2508.20722**Ning Shang, Yifei Liu, Yi Zhu, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/shang-2025-rstar2-agent-agentic-reasoning/)
118. **[When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs](https://md.research.elamur.ai/free/en/papers/khairi-2025-when-life-gives-you-samples/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ammar Khairi, Daniel D'souza, Ye Shen, et al.*2025 · 6 citations*
119. [**mR3: Multilingual Rubric-Agnostic Reward Reasoning Models arXiv:2510.01146**David Anugraha, Shou-Yi Hung, Zilu Tang, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/anugraha-2025-mr3-multilingual-rubric-agnostic-reward/)
120. [**Baichuan Alignment Technical Report arXiv:2410.14940**Mingan Lin, Fan Yang, Yanjun Shen, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-baichuan-alignment-technical-report/)
121. [**Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUs arXiv:2503.05139**Ling Team; Binwei Zeng; Chao Huang; Chao Zhang; Changxin Tian; Cong Chen; Dingnan Jin; Feng Yu; Feng Zhu; Feng Yuan; Fakang Wang; Gangshan Wang; Guangyao Zhai; Haitao Zhang; Huizhong Li; Jun Zhou; Jia Liu; Junpeng Fang; Junjie Ou; Jun Hu; Ji Luo; Ji Zhang; Jian Liu; Jian Sha; Jianxue Qian; Jiewei Wu; Junping Zhao; Jianguo Li; Jubao Feng; Jingchao Di; Junming Xu; Jinghua Yao; Kuan Xu; Kewei Du; Longfei Li; Lei Liang; Lu Yu; Li Tang; Lin Ju; Peng Xu; Qing Cui; Song Liu; Shicheng Li; Shun Song; Song Yan; Tengwei Cai; Tianyi Chen; Ting Guo; Ting Huang; Tao Feng; Tao Wu; Wei Wu; Xiaolu Zhang; Xueming Yang; Xin Zhao; Xiaobo Hu; Xin Lin; Yao Zhao; Yilong Wang; Yongzhen Guo; Yuanyuan Wang; Yue Yang; Yang Cao; Yuhao Fu; Yi Xiong; Yanzhe Li; Zhe Li; Zhiqiang Zhang; Ziqi Liu; Zhaoxin Huan; Zujie Wen; Zhenhang Sun; Zhuoxuan Du;, Zhengyu He*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/ling-team-2025-every-flop-counts-scaling/)
122. [**GemmAr: Enhancing LLMs Through Arabic Instruction-Tuning arXiv:2407.02147**Hasna Chouikhi, Manel Aloui, Cyrine Ben Hammou, et al.*2024 · 4 citations*](https://md.research.elamur.ai/free/en/papers/chouikhi-2024-gemmar-enhancing-llms-through-arabic/)
123. **[How Long Reasoning Chains Influence LLMs' Judgment of Answer Factuality](https://md.research.elamur.ai/free/en/papers/tu-2026-how-long-reasoning-chains-influence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minzhu Tu, Shiyu Ni, Keping Bi*2026 · 3 citations*
124. **[J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization](https://md.research.elamur.ai/free/en/papers/xu-2026-j4r-learning-judge-equivalent-initial/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Austin Xu, Yilun Zhou, Xuan-Phi Nguyen, et al.*2026 · 3 citations*
125. **[LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-llmeval-fair-large-scale-longitudinal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ming Zhang, Yujiong Shen, Jingyi Deng, et al.*2026 · 3 citations*
126. **[Outcome Accuracy is Not Enough: Aligning the Reasoning Process of Reward Models](https://md.research.elamur.ai/free/en/papers/wang-2026-outcome-accuracy-is-not-enough/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Binghai Wang, Yantao Liu, Yuxuan Liu, et al.*2026 · 3 citations*
127. **[RubricBench: Aligning Model-Generated Rubrics with Human Standards](https://md.research.elamur.ai/free/en/papers/zhou-2026-rubricbench-aligning-model-generated-rubrics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyi Zhou, Qiyuan Zhang, Yufei Wang, et al.*2026 · 3 citations*
128. **[My LLM might Mimic AAE - But When Should It?](https://md.research.elamur.ai/free/en/papers/sandoval-2025-my-llm-might-mimic-aae/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sandra Camille Sandoval, Christabel Acquaye, Kwesi Adu Cobbina, et al.*2025 · 3 citations*
129. **[AMIYA Shared Task: Arabic Modeling In Your Accent at VarDial 2026](https://md.research.elamur.ai/free/en/papers/robinson-2026-amiya-shared-task-arabic-modeling/) [Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)](https://md.research.elamur.ai/free/en/venues/vardial/)**Nathaniel R. Robinson, Shahd Abdelmoneim, Anjali Kantharuban, et al.*2026 · 2 citations*
130. **[EvoRoute: Experience-Driven Self-Routing LLM Agent Systems](https://md.research.elamur.ai/free/en/papers/zhang-2026-evoroute-experience-driven-self-routing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guibin Zhang, Haiyang Yu, Kaiming Yang, et al.*2026 · 2 citations*
131. **[Hard2Verify: A Step-Level Verification Benchmark for Open-Ended Frontier Math](https://md.research.elamur.ai/free/en/papers/pandit-2026-hard2verify-step-level-verification-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shrey Pandit, Austin Xu, Xuan-Phi Nguyen, et al.*2026 · 2 citations*
132. **[Paragraph Segmentation Revisited: Towards a Standard Task for Structuring Speech](https://md.research.elamur.ai/free/en/papers/retkowski-2026-paragraph-segmentation-revisited-standard-task/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Fabian Retkowski, Alexander Waibel*2026 · 2 citations*
133. **[Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption](https://md.research.elamur.ai/free/en/papers/liu-2026-position-llm-watermarking-should-align/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yepeng Liu, Xuandong Zhao, Dawn Song, et al.*2026 · 2 citations*
134. [**STEP3-VL-10B Technical Report arXiv:2601.09668**Ailin Huang, Chengyuan Yao, Chunrui Han, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/huang-2026-step3-vl-10b-technical/)
135. **[T-pro 2.0: An Efficient Russian Hybrid-Reasoning Model and Playground](https://md.research.elamur.ai/free/en/papers/stoianov-2026-t-pro-2-0-efficient/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Dmitrii Stoianov, Danil Taranets, Olga Tsymboi, et al.*2026 · 2 citations*
136. **[Tracking the evolution of LLM capabilities for Belarusian with OpenAI Evals](https://md.research.elamur.ai/free/en/papers/poritski-2026-tracking-evolution-llm-capabilities-belarusian/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Vladislav Poritski, Oksana Volchek, Maksim Aparovich, et al.*2026 · 2 citations*
137. [**WASIL: In-the-Wild Arabic Spoken Interactions with LLMs arXiv:2605.16364**Zien Sheikh Ali, Hamdy Mubarak, Soon-Gyo Jung, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/ali-2026-wasil-wild-arabic-spoken-interactions/)
138. [**Methodology of Adapting Large English Language Models for Specific Cultural Contexts arXiv:2406.18192**Wenjing Zhang, Siqi Xiao, Xuejiao Lei, et al.*2024 · 2 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-methodology-adapting-large-english-language/)
139. **[Adaptive Data Flywheel: Applying MAPE Control Loops to AI Agent Improvement](https://md.research.elamur.ai/free/en/papers/shukla-2026-adaptive-data-flywheel-applying-mape/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Aaditya Shukla, Sidney Knowles, Meenakshi Madugula, et al.*2026 · 1 citation*
140. **[Anti-Length Shift: Dynamic Outlier Truncation for Training Efficient Reasoning Models](https://md.research.elamur.ai/free/en/papers/wu-2026-anti-length-shift-dynamic-outlier/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Wu, Liyi Chen, Congxi Xiao, et al.*2026 · 1 citation*
141. **[Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future](https://md.research.elamur.ai/free/en/papers/wu-2026-can-ai-be-good-peer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sihong Wu, Owen Jiang, Yilun Zhao, et al.*2026 · 1 citation*
142. **[Can Models Help Us Create Better Models? Evaluating LLMs as Data Scientists](https://md.research.elamur.ai/free/en/papers/pietruszka-2026-can-models-help-us-create/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Michał Pietruszka, Łukasz Borchmann, Aleksander Jędrosz, et al.*2026 · 1 citation*
143. **[Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language Models](https://md.research.elamur.ai/free/en/papers/yin-2026-decentralized-arena-democratic-scalable-automatic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanbin Yin, Kun Zhou, Zhen Wang, et al.*2026 · 1 citation*
144. **[Frankentext: Stitching random text fragments into long-form narratives](https://md.research.elamur.ai/free/en/papers/pham-2026-frankentext-stitching-random-text-fragments/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chau Minh Pham, Jenna Russell, Dzung Pham, et al.*2026 · 1 citation*
145. **[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*
146. **[IGenBench: Benchmarking the Reliability of Text-to-Infographic Generation](https://md.research.elamur.ai/free/en/papers/tang-2026-igenbench-benchmarking-reliability-text-infographic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yinghao Tang, Xueding Liu, Boyuan Zhang, et al.*2026 · 1 citation*
147. **[Measuring Human Contribution in AI-Assisted Content Generation](https://md.research.elamur.ai/free/en/papers/xie-2026-measuring-human-contribution-ai-assisted/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yueqi Xie, Tao Qi, Jingwei Yi, et al.*2026 · 1 citation*
148. **[Multi-modal, Multi-task, Multi-criteria Automatic Evaluation with Vision Language Models](https://md.research.elamur.ai/free/en/papers/oi-2026-multi-modal-multi-task-multi/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Masanari Oi, Masahiro Kaneko, Naoaki Okazaki, et al.*2026 · 1 citation*
149. **[P-Check: Advancing Personalized Reward Model via Learning to Generate Dynamic Checklist](https://md.research.elamur.ai/free/en/papers/seo-2026-p-check-advancing-personalized-reward/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kwangwook Seo, Dongha Lee*2026 · 1 citation*
150. **[SCAN: Structured Capability Assessment and Navigation for LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-scan-structured-capability-assessment-navigation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zongqi Wang, Tianle Gu, Chen Gong, et al.*2026 · 1 citation*
151. **[SPARD: Self-Paced Curriculum for RL Alignment via Integrating Reward Dynamics and Data Utility](https://md.research.elamur.ai/free/en/papers/zhi-2026-spard-self-paced-curriculum-rl/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuyang Zhi, Peilun Zhou, Chengqiang Lu, et al.*2026 · 1 citation*
152. **[The Mighty ToRR: A Benchmark for Table Reasoning and Robustness in LLMs](https://md.research.elamur.ai/free/en/papers/tahan-2026-mighty-torr-benchmark-table-reasoning/) [Workshop on Structured Understanding, Retrieval, and Generation in the LLM Era](https://md.research.elamur.ai/free/en/venues/surgellm/)**Shir Ashury-Tahan, Yifan Mai, Rajmohan C, et al.*2026 · 1 citation*
153. **[X-NLP at SemEval-2026 Task 12: Prompting LLMs for Abductive Event Reasoning](https://md.research.elamur.ai/free/en/papers/mattie-2026-x-nlp-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Caelen Mattie, Patrick Bowen, Milton King*2026 · 1 citation*
154. [**A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战) Acta Automatica Sinica (自动化学报)**Anda Tang (唐岸达), Zhouchen Lin (林宙辰)*2026*](https://md.research.elamur.ai/free/en/papers/tang-2026-parameter-efficient-fine/)
155. **[Adaptive Prompt Optimization for Open-Ended Tasks: Uncertainty Preference as a Secondary Signal](https://md.research.elamur.ai/free/en/papers/zhang-2026-adaptive-prompt-optimization-open-ended/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuyang Zhang, Zhixuan Liu, Zhichen Dong, et al.*2026*
156. **[AI Safety Lost in Translation: Evaluating the Effectiveness of English-Italian Cross-Lingual LLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/wu-2026-ai-safety-lost-translation-evaluating/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Alessio Wu, Martim Brandao*2026*
157. **[AlphaContext: An Evolutionary Tree-based Psychometric Context Generator for Creativity Assessment](https://md.research.elamur.ai/free/en/papers/wang-2026-alphacontext-evolutionary-tree-based-psychometric/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixuan Wang, Yue Huang, Hong Qian, et al.*2026*
158. **[Analysing Differences in Persuasive Language in LLM-Generated Text: Uncovering Stereotypical Gender Patterns](https://md.research.elamur.ai/free/en/papers/pauli-2026-analysing-differences-persuasive-language-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Amalie Brogaard Pauli, Maria Barrett, Max Müller-Eberstein, et al.*2026*
159. **[At Your Own PACE: A Causal Framework for Evaluating EQ in LLMs](https://md.research.elamur.ai/free/en/papers/lyu-2026-your-own-pace-causal-framework/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lei Lyu, Shengling Wang, Ke Chao, et al.*2026*
160. **[Attribution-Based Analysis and Optimization of Modular Agentic Workflows](https://md.research.elamur.ai/free/en/papers/yang-2026-attribution-based-analysis-optimization-modular/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingxuan Yang, Bo Huang, Siyuan Qi, et al.*2026*
161. **[Automatic Evaluation of Open-Domain Real Conversations: Combining Encoder-Based, Dialogue-Based Features and Large Language Models Ratings](https://md.research.elamur.ai/free/en/papers/lopez-2026-automatic-evaluation-open-domain-real/) [International Workshop on Spoken Dialogue System Technology](https://md.research.elamur.ai/free/en/venues/iwsds/)**Cristina Conforto-López, Marcos Estecha-Garitagoitia, Mario Rodriguez-Cantelar, et al.*2026*
162. **[AutoTaskEval: Towards Domain-Specific and Fine-Grained Evaluation for LLMs](https://md.research.elamur.ai/free/en/papers/lyu-2026-autotaskeval-domain-specific-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingqing Lyu, Linjuan Wu, Yongliang Shen, et al.*2026*
163. **[Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-length-scaling-synergizing-breadth/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qiyuan Zhang, Yufei Wang, Tianhe Wu, et al.*2026*
164. **[Beyond Ranking: Fine-Grained Diagnostics and Self-Improvement for MLLMs](https://md.research.elamur.ai/free/en/papers/xu-2026-beyond-ranking-fine-grained-diagnostics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingze Xu, Zijing Zhao, Qiming Peng, et al.*2026*
165. **[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*
166. **[Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty Estimation](https://md.research.elamur.ai/free/en/papers/radharapu-2026-calibrating-llm-judges-linear-probes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bhaktipriya Radharapu, Eshika Saxena, Kenneth Li, et al.*2026*
167. **[Can AI Revise Research Papers with Human Review Feedback? An Empirical Study and Benchmark](https://md.research.elamur.ai/free/en/papers/luo-2026-can-ai-revise-research-papers/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihan Luo, Hong Huang, Jianxun Lian, et al.*2026*
168. **[ClinAlign: Scaling Healthcare Alignment from Clinician Preference](https://md.research.elamur.ai/free/en/papers/lyu-2026-clinalign-scaling-healthcare-alignment-clinician/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shiwei Lyu, Xidong Wang, Hao Zhu, et al.*2026*
169. **[COIG-P: A High-Quality and Large-Scale Chinese Preference Dataset for Alignment with Human Values](https://md.research.elamur.ai/free/en/papers/wu-2026-coig-p-high-quality-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Siwei Wu, JinCheng Ren, Xeron Du, et al.*2026*
170. **[Confident, Calibrated, or Complicit: Safety Alignment and Ideological Bias in LLM Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/selvaganapathy-2026-confident-calibrated-or-complicit-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sanjeevan Selvaganapathy, Mehwish Nasim*2026*
171. **[DynamicFocalPO: Adaptive Focusing Strategy for Preference Optimization](https://md.research.elamur.ai/free/en/papers/zhou-2026-dynamicfocalpo-adaptive-focusing-strategy-preference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shu Zhou, Junan Chen, Rui Ling, et al.*2026*
172. **[Evaluating Cost-Efficiency of LLMs in a RAG Setup on Polish Wikipedia: Quality vs. Energy Consumption](https://md.research.elamur.ai/free/en/papers/smits-2026-evaluating-cost-efficiency-llms-rag/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Patrycja Smits, Tomasz Walkowiak*2026*
173. **[ExpressivityBench: Can LLMs Communicate Implicitly?](https://md.research.elamur.ai/free/en/papers/tint-2026-expressivitybench-can-llms-communicate-implicitly/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Joshua Tint, Som Sagar, Aditya Taparia, et al.*2026*
174. **[Feedback-Aware Prompt Optimization Framework for Generating Job Postings](https://md.research.elamur.ai/free/en/papers/maharjan-2026-feedback-aware-prompt-optimization-framework/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Suraj Maharjan, Ainur Yessenalina, Srinivasan H. Sengamedu*2026*
175. **[Fin-STAR: Structure-as-Semantics to Resolve Implicitness in Financial Retrieval](https://md.research.elamur.ai/free/en/papers/zou-2026-fin-star-structure-as-semantics/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yu Zou, Yan Chen, Lida He, et al.*2026*
176. **[Mediocrity is the key for LLM as a Judge Anchor Selection](https://md.research.elamur.ai/free/en/papers/yehiya-2026-mediocrity-is-key-llm-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shachar Don-Yehiya, Asaf Yehudai, Leshem Choshen, et al.*2026*
177. **[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*
178. **[Model Directions, Not Words: Mechanistic Topic Models Using Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/zheng-2026-model-directions-not-words-mechanistic/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Carolina Zheng, Nicolas Beltran-Velez, Sweta Karlekar, et al.*2026*
179. **[MTR-Suite: A Framework for Evaluating and Synthesizing Conversational Retrieval Benchmarks](https://md.research.elamur.ai/free/en/papers/ruan-2026-mtr-suite-framework-evaluating-synthesizing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junhao Ruan, Abudukeyumu Abudula, Bei Li, et al.*2026*
180. **[Position: Scores Without Context? Rethinking the Role of Evaluation in the Era of LLMs](https://md.research.elamur.ai/free/en/papers/zhou-2026-position-scores-without-context-rethinking/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Jiawei Zhou*2026*
181. **[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*
182. **[PRISM: Probabilistic Reward Model with Inherent Structural Modeling](https://md.research.elamur.ai/free/en/papers/zhou-2026-prism-probabilistic-reward-model-inherent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhang Zhou, Yixin Cao, Yuchen Ni, et al.*2026*
183. **[Probing the Plasticity and Correlation of LLM Value Systems: LLM Value Rankings are Not Stable](https://md.research.elamur.ai/free/en/papers/tang-2026-probing-plasticity-correlation-llm-value/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenheng Tang, Qihua Pan, Jingya Shen, et al.*2026*
184. **[QUARTZ: Quantile-Aware Routing and Queueing for TTFT SLOs in LLM Serving](https://md.research.elamur.ai/free/en/papers/liu-2026-quartz-quantile-aware-routing-queueing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhipeng Liu, Yifan Zheng, Fanqi Kong, et al.*2026*
185. **[R ESEARCH QA: Evaluating Scholarly Question Answering at Scale Across 75 Fields with Survey-Mined Questions and Rubrics](https://md.research.elamur.ai/free/en/papers/yifei-2026-r-esearch-qa-evaluating-scholarly/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Li S. Yifei, Allen Chang, Chaitanya Malaviya, et al.*2026*
186. **[ReasonRec: A Reasoning-Augmented Multimodal Agent for Unified Recommendation](https://md.research.elamur.ai/free/en/papers/zhang-2026-reasonrec-reasoning-augmented-multimodal-agent/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yihua Zhang, Mingfu Liang, Jiyan Yang, et al.*2026*
187. **[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*
188. **[Revisiting Self-Play Preference Optimization: On the Role of Prompt Difficulty](https://md.research.elamur.ai/free/en/papers/xiao-2026-revisiting-self-play-preference-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yao Xiao, Jung-jae Kim, Roy Ka-Wei Lee, et al.*2026*
189. **[Reward Modeling for Scientific Writing Evaluation](https://md.research.elamur.ai/free/en/papers/sahinuc-2026-reward-modeling-scientific-writing-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Furkan Şahinuç, Subhabrata Dutta, Iryna Gurevych*2026*
190. **[Route to Rome Attack: Directing LLM Routers to Expensive Models via Adversarial Suffix Optimization](https://md.research.elamur.ai/free/en/papers/tang-2026-route-rome-attack-directing-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haochun Tang, Yuliang Yan, Jiahua Lu, et al.*2026*
191. **[Russian Generative Spelling, Punctuation and Capitalization Correction](https://md.research.elamur.ai/free/en/papers/martynov-2026-russian-generative-spelling-punctuation-capitalization/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Nikita Martynov, Danil Astafurov, Ulyana Isaeva, et al.*2026*
192. **[Self-Guided Alignment: Adaptive Preference Sensing for Multi-Objective Generation](https://md.research.elamur.ai/free/en/papers/wang-2026-self-guided-alignment-adaptive-preference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ning Wang, Zhanyang Liu, Taotao Zhou, et al.*2026*
193. **[SEMIROUTER: Sparse-Data Enhanced Routing for Adaptive Multi-LLM System](https://md.research.elamur.ai/free/en/papers/wang-2026-semirouter-sparse-data-enhanced-routing/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zijie Wang, Xinyu Yan, Che Wang, et al.*2026*
194. **[Show or Tell? Modeling the evolution of request-making in Human-LLM conversations](https://md.research.elamur.ai/free/en/papers/zhu-2026-show-or-tell-modeling-evolution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shengqi Zhu, Jeffrey Rzeszotarski, David Mimno*2026*
195. **[Synthetic Instruction Generation for Low-Resource Nordic Languages: Viability and Limitations in LLM Instruction-Tuning](https://md.research.elamur.ai/free/en/papers/stenlund-2026-synthetic-instruction-generation-low-resource/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mathias Stenlund, Annika Simonsen, Lars Bungum, et al.*2026*
196. **[Telling Speculative Stories to Help Humans Imagine the Harms of Healthcare AI](https://md.research.elamur.ai/free/en/papers/zhao-2026-telling-speculative-stories-help-humans/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingmeng Zhao, Tongnian Wang, Dan Schumacher, et al.*2026*
197. **[Toying with Style: Can GenAI Mimic a Literary Translator's Voice?](https://md.research.elamur.ai/free/en/papers/sopot-2026-toying-style-can-genai-mimic/) [Workshop on Style in GenAI-Translated Content (StyGenAI)](https://md.research.elamur.ai/free/en/venues/stygenai/)**Beniamin Sopot, Dorothy Kenny*2026*
198. **[WebCoderBench: Benchmarking Web Application Generation with Comprehensive and Interpretable Evaluation Metrics](https://md.research.elamur.ai/free/en/papers/liu-2026-webcoderbench-benchmarking-web-application-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenxu Liu, Yingjie Fu, Wei Yang, et al.*2026*
199. **[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*
200. **[TounsiBench: Benchmarking Large Language Models for Tunisian Arabic](https://md.research.elamur.ai/free/en/papers/hassine-2025-tounsibench-benchmarking-large-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Souha Ben Hassine, Asma Arrak, Marouene Addhoum, et al.*2025*

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