---
title: "Who cites Jian Luan — 173 papers of our library"
description: "173 papers of the Elamur Research library cite the works of Jian Luan, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/jian-luan/cited-by/"
---
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# Who cites Jian Luan

173 citations of their works from 173 papers of our library (of the 149,439 whose bibliographies we read) · 65 with a page here, the most cited first · [← Jian Luan](https://md.research.elamur.ai/free/en/authors/jian-luan/)

1. **[A Survey on Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,648 citations*
2. [**DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models arXiv:2402.03300**Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.*2024 · 2,115 citations*](https://md.research.elamur.ai/free/en/papers/shao-2024-deepseekmath-pushing-limits-mathematical-reasoning/)
3. **[OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems](https://md.research.elamur.ai/free/en/papers/he-2024-olympiadbench-challenging-benchmark-promoting-agi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaoqun He, Renjie Luo, Yuzhuo Bai, et al.*2024 · 456 citations*
4. [**Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement arXiv:2409.12122**An Yang, Beichen Zhang, Binyuan Hui, et al.*2024 · 417 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-qwen2-5-math-technical-report/)
5. [**Kimi K2: Open Agentic Intelligence arXiv:2507.20534**Kimi Team, Yifan Bai, Yiping Bao, et al.*2025 · 347 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k2-open-agentic/)
6. **[Large Language Models for Mathematical Reasoning: Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/ahn-2024-large-language-models-mathematical-reasoning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Janice Ahn, Rishu Verma, Renze Lou, et al.*2024 · 280 citations*
7. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
8. **[Tool Learning with Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/qu-2024-tool-learning-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Changle Qu, Sunhao Dai, Xiaochi Wei, et al.*2024 · 195 citations*
9. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
10. **[The Lessons of Developing Process Reward Models in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2025-lessons-developing-process-reward-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenru Zhang, Chujie Zheng, Yangzhen Wu, et al.*2025 · 161 citations*
11. [**Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models arXiv:2503.16419**Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/sui-2025-stop-overthinking-survey-efficient-reasoning/)
12. [**DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence arXiv:2606.19348**DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.*2026 · 122 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2026-deepseek-v4-highly-efficient/)
13. [**From Persona to Personalization: A Survey on Role-Playing Language Agents arXiv:2404.18231**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/)
14. [**A Survey on Efficient Inference for Large Language Models arXiv:2404.14294**Zixuan Zhou, Xuefei Ning, Ke Hong, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-survey-efficient-inference-large-language/)
15. **[GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers](https://md.research.elamur.ai/free/en/papers/li-2024-gsm-plus-comprehensive-benchmark-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qintong Li, Leyang Cui, Xueliang Zhao, et al.*2024 · 108 citations*
16. **[R-Judge: Benchmarking Safety Risk Awareness for LLM Agents](https://md.research.elamur.ai/free/en/papers/yuan-2024-r-judge-benchmarking-safety-risk/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tongxin Yuan, Zhiwei He, Lingzhong Dong, et al.*2024 · 106 citations*
17. **[Retrieval-Augmented Generation for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/wu-2024-retrieval-augmented-generation-natural-language/) [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/)**Shangyu Wu, Ying Xiong, Yufei Cui, et al.*2024 · 86 citations*
18. [**DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning arXiv:2504.11456**Zhiwei He, Tian Liang, Jiahao Xu, et al.*2025 · 78 citations*](https://md.research.elamur.ai/free/en/papers/he-2025-deepmath-103k-large-scale-challenging/)
19. [**Dynamic Early Exit in Reasoning Models arXiv:2504.15895**Chenxu Yang, Qingyi Si, Yongjie Duan, et al.*2025 · 74 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-dynamic-early-exit-reasoning-models/)
20. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/)
21. **[In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agents](https://md.research.elamur.ai/free/en/papers/tan-2025-prospect-retrospect-reflective-memory-management/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Tan, Jun Yan, I-Hung Hsu, et al.*2025 · 46 citations*
22. [**Efficient Reasoning Models: A Survey arXiv:2504.10903**Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-efficient-reasoning-models-survey/)
23. [**ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline arXiv:2404.02893**Yifan Xu, Xiao Liu, Xinghan Liu, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-chatglm-math-improving-math/)
24. [**Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent arXiv:2411.02265**Xingwu Sun, Yanfeng Chen, Yiqing Huang, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-hunyuan-large-open-source/)
25. [**Baichuan-M1: Pushing the Medical Capability of Large Language Models arXiv:2502.12671**Bingning Wang, Haizhou Zhao, Huozhi Zhou, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-baichuan-m1-pushing-medical/)
26. **[Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance](https://md.research.elamur.ai/free/en/papers/pecher-2025-comparing-specialised-small-general-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Branislav Pecher, Ivan Srba, Maria Bielikova*2025 · 24 citations*
27. **[Personalized Generation In Large Model Era: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2025-personalized-generation-large-model-era/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiyan Xu, Jinghao Zhang, Alireza Salemi, et al.*2025 · 24 citations*
28. [**Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical Reasoning arXiv:2407.00782**Zimu Lu, Aojun Zhou, Ke Wang, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-step-controlled-dpo-leveraging-stepwise/)
29. **[Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs](https://md.research.elamur.ai/free/en/papers/yang-2025-code-think-think-code-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Dayu Yang, Tianyang Liu, Daoan Zhang, et al.*2025 · 19 citations*
30. **[OS Agents: A Survey on MLLM-based Agents for Computer, Phone and Browser Use](https://md.research.elamur.ai/free/en/papers/hu-2025-os-agents-survey-mllm-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueyu Hu, Tao Xiong, Biao Yi, et al.*2025 · 17 citations*
31. [**Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models arXiv:2503.24377**Rui Wang, Hongru Wang, Boyang Xue, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-harnessing-reasoning-economy-survey-efficient/)
32. **[FBS: Modeling Native Parallel Reading inside a Transformer](https://md.research.elamur.ai/free/en/papers/wang-2026-fbs-modeling-native-parallel-reading/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tongxi Wang*2026 · 14 citations*
33. [**Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models — The Story Goes On arXiv:2407.08348**Liang Zeng, Liangjun Zhong, Liang Zhao, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-skywork-math-data-scaling-laws/)
34. [**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/)
35. [**Implicit Reasoning in Large Language Models: A Comprehensive Survey arXiv:2509.02350**Jindong Li, Yali Fu, Li Fan, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-implicit-reasoning-large-language-models/)
36. **[H-MEM: Hierarchical Memory for High-Efficiency Long-Term Reasoning in LLM Agents](https://md.research.elamur.ai/free/en/papers/sun-2026-h-mem-hierarchical-memory-high/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Haoran Sun, Shaoning Zeng, Bob Zhang*2026 · 8 citations*
37. **[FastMCTS: A Simple Sampling Strategy for Data Synthesis](https://md.research.elamur.ai/free/en/papers/li-2025-fastmcts-simple-sampling-strategy-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiji Li, Kai Lv, Yunfan Shao, et al.*2025 · 8 citations*
38. [**SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models arXiv:2408.15565**Dian Yu, Baolin Peng, Ye Tian, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/yu-2024-siam-self-improving-code-assisted/)
39. **[To Distill or Not to Distill? On the Robustness of Robust Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/waheed-2024-distill-or-not-distill-robustness/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Abdul Waheed, Karima Kadaoui, Muhammad Abdul-Mageed*2024 · 8 citations*
40. **[Context Reasoner: Incentivizing Reasoning Capability for Contextualized Privacy and Safety Compliance via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/hu-2025-context-reasoner-incentivizing-reasoning-capability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenbin Hu, Haoran Li, Huihao Jing, et al.*2025 · 7 citations*
41. [**Pangu Ultra: Pushing the Limits of Dense Large Language Models on Ascend NPUs arXiv:2504.07866**Yichun Yin, Wenyong Huang, Kaikai Song, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/yin-2025-pangu-ultra-pushing-limits/)
42. **[ARCQuant: Boosting NVFP4 Quantization with Augmented Residual Channels for LLMs](https://md.research.elamur.ai/free/en/papers/meng-2026-arcquant-boosting-nvfp4-quantization-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoqian Meng, Yilun Luo, Yafei Zhao, et al.*2026 · 5 citations*
43. **[Preference-Aware Memory Update for Long-Term LLM Agents](https://md.research.elamur.ai/free/en/papers/sun-2026-preference-aware-memory-update-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoran Sun, Zekun Zhang, Shaoning Zeng*2026 · 4 citations*
44. [**Pangu Pro MoE: Mixture of Grouped Experts for Efficient Sparsity arXiv:2505.21411**Yehui Tang, Xiaosong Li, Fangcheng Liu, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/tang-2025-pangu-pro-moe-mixture/)
45. **[Jailbreaking Attacks vs. Content Safety Filters: How Far Are We in the LLM Safety Arms Race?](https://md.research.elamur.ai/free/en/papers/xin-2026-jailbreaking-attacks-vs-content-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Xin, Dingfan Chen, Linyi Yang, et al.*2026 · 3 citations*
46. **[Through a Compressed Lens: Investigating The Impact of Quantization on Factual Knowledge Recall](https://md.research.elamur.ai/free/en/papers/wang-2026-through-compressed-lens-investigating-impact/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Qianli Wang, Mingyang Wang, Nils Feldhus, et al.*2026 · 2 citations*
47. **[From Signal Degradation to Computation Collapse: Uncovering the Two Failure Modes of LLM Quantization](https://md.research.elamur.ai/free/en/papers/zhou-2026-signal-degradation-computation-collapse-uncovering/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenxi Zhou, Pengfei Cao, Jiang Li, et al.*2026 · 1 citation*
48. [**Hunyuan-A13B Technical Report arXiv:2609.27284**Tencent Hunyuan Team, Ao Liu, Botong Zhou, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/team-2026-hunyuan-hunyuan-a13b-technical-report/)
49. **[PAC-BENCH: Evaluating Multi-Agent Collaboration under Privacy Constraints](https://md.research.elamur.ai/free/en/papers/park-2026-pac-bench-evaluating-multi-agent/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Minjun Park, Donghyun Kim, Hyeonjong Ju, et al.*2026 · 1 citation*
50. **[Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-render-thought-rendering-textual-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifan Wang, Shiyu Li, Peiming Li, et al.*2026 · 1 citation*
51. **[T²-RAGBench: Text-and-Table Benchmark for Evaluating Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/strich-2026-t-2-ragbench-text-table/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Jan Strich, Enes Kutay Isgorur, Maximilian Trescher, et al.*2026 · 1 citation*
52. **[Attention Under Attack: Analog Noise Effects and Mechanistic Vulnerabilities in Transformer Models](https://md.research.elamur.ai/free/en/papers/rahman-2026-attention-under-attack-analog-noise/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mafizur Rahman, Lijun Qian*2026*
53. **[Beyond Accuracy: Alignment and Error Detection across Languages in the Bi-GSM8K Math-Teaching Benchmark](https://md.research.elamur.ai/free/en/papers/park-2026-beyond-accuracy-alignment-error-detection/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jieun Park, KyungTae Lim, Joon-ho Lim*2026*
54. **[CogBench: Benchmarking Cognitive Alignment of Large Language Models in Educational Question Answering](https://md.research.elamur.ai/free/en/papers/lu-2026-cogbench-benchmarking-cognitive-alignment-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tong Lu, Zhichun Wang, Yuanhao Sun, et al.*2026*
55. **[Does Chain-of-Thought Reasoning Help Mobile GUI Agents? An Empirical Study](https://md.research.elamur.ai/free/en/papers/zhang-2026-does-chain-thought-reasoning-help/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Li Zhang, Longxi Gao, Mengwei Xu*2026*
56. **[Evaluating Small Language Models for English-to-Portuguese Translation: Impact of Model Scale and Quantization](https://md.research.elamur.ai/free/en/papers/tamiosso-2026-evaluating-small-language-models-english/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Gustavo Lopes Tamiosso, Rafael Oleques Nunes, Dennis Giovani Balreira*2026*
57. **[Failure Modes in Multi-Hop QA: The Weakest Link Effect and the Recognition Bottleneck](https://md.research.elamur.ai/free/en/papers/zhang-2026-failure-modes-multi-hop-qa/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Meiru Zhang, Zaiqiao Meng, Nigel Collier*2026*
58. **[How to Make LMs Strong Node Classifiers?](https://md.research.elamur.ai/free/en/papers/xu-2026-how-make-lms-strong-node/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhe Xu, Kaveh Hassani, Si Zhang, et al.*2026*
59. **[Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory](https://md.research.elamur.ai/free/en/papers/xu-2026-learning-how-what-memorize-cognition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Derong Xu, Shuochen Liu, Pengfei Luo, et al.*2026*
60. **[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*
61. **[MENTOR: Mitigating Identity Drift in Dynamic Role-Playing via Dual-Chain Structured Memory](https://md.research.elamur.ai/free/en/papers/zhuoning-2026-mentor-mitigating-identity-drift-dynamic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhu Zhuoning, Xingyu Gao, Hailong Shi*2026*
62. **[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*
63. **[Parallel Test-Time Scaling for Latent Reasoning Models](https://md.research.elamur.ai/free/en/papers/you-2026-parallel-test-time-scaling-latent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Runyang You, Yongqi Li, Meng Liu, et al.*2026*
64. **[Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow](https://md.research.elamur.ai/free/en/papers/zhong-2026-parallelism-generation-order-masked-diffusion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangyang Zhong, Yanmei Gu, Zhengqing Zang, et al.*2026*
65. **[TriEx: A Game-based Tri-View Framework for Explaining Internal Reasoning in Multi-Agent LLMs](https://md.research.elamur.ai/free/en/papers/wang-2026-triex-game-based-tri-view/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyi Wang, Chen Zhang, Wenjun Peng, et al.*2026*

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