---
title: "Who cites Zhenguo Li — page 2 — 1,100 papers of our library"
description: "1,100 papers of the Elamur Research library cite the works of Zhenguo Li, found in their bibliographies · page 2 of 3 · 101–200; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/zhenguo-li/cited-by/page/2/"
---
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# Who cites Zhenguo Li

1,233 citations of their works from 1,100 papers of our library (of the 149,439 whose bibliographies we read) · 284 with a page here, the most cited first · page 2 of 3 · 101–200 · [← Zhenguo Li](https://md.research.elamur.ai/free/en/authors/zhenguo-li/)

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101. **[MARIO: MAth Reasoning with code Interpreter Output - A Reproducible Pipeline](https://md.research.elamur.ai/free/en/papers/liao-2024-mario-math-reasoning-code-interpreter/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Minpeng Liao, Chengxi Li, Wei Luo, et al.*2024 · 64 citations*
102. [**Learning From Mistakes Makes LLM Better Reasoner arXiv:2310.20689**Shengnan An, Zexiong Ma, Zeqi Lin, et al.*2023 · 64 citations*](https://md.research.elamur.ai/free/en/papers/an-2023-learning-mistakes-makes-llm-better/)
103. **[PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models](https://md.research.elamur.ai/free/en/papers/song-2025-prmbench-fine-grained-challenging-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingyang Song, Zhaochen Su, Xiaoye Qu, et al.*2025 · 63 citations*
104. [**Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves arXiv:2311.04205**Yihe Deng, Weitong Zhang, Zixiang Chen, et al.*2023 · 62 citations*](https://md.research.elamur.ai/free/en/papers/deng-2023-rephrase-respond-let-large-language/)
105. [**The Generative AI Paradox: "What It Can Create, It May Not Understand" arXiv:2311.00059**Peter West, Ximing Lu, Nouha Dziri, et al.*2023 · 62 citations*](https://md.research.elamur.ai/free/en/papers/west-2023-generative-ai-paradox-create-may/)
106. **[Small Models Struggle to Learn from Strong Reasoners](https://md.research.elamur.ai/free/en/papers/li-2025-small-models-struggle-learn-strong/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuetai Li, Xiang Yue, Zhangchen Xu, et al.*2025 · 61 citations*
107. **[MAPO: Advancing Multilingual Reasoning through Multilingual-Alignment-as-Preference Optimization](https://md.research.elamur.ai/free/en/papers/she-2024-mapo-advancing-multilingual-reasoning-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuaijie She, Wei Zou, Shujian Huang, et al.*2024 · 59 citations*
108. [**Rho-1: Not All Tokens Are What You Need arXiv:2404.07965**Zhenghao Lin, Zhibin Gou, Yeyun Gong, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-rho-1-all-tokens-need/)
109. **[MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMs](https://md.research.elamur.ai/free/en/papers/lu-2024-mathgenie-generating-synthetic-data-question/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zimu Lu, Aojun Zhou, Houxing Ren, et al.*2024 · 58 citations*
110. [**LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning arXiv:2308.03303**Longteng Zhang, Lin Zhang, Shaohuai Shi, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-lora-fa-efficient-effective-low/)
111. **[Unintended Impacts of LLM Alignment on Global Representation](https://md.research.elamur.ai/free/en/papers/ryan-2024-unintended-impacts-llm-alignment-global/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael J Ryan, William Held, Diyi Yang*2024 · 57 citations*
112. **[OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AI](https://md.research.elamur.ai/free/en/papers/huang-2024-olympicarena-benchmarking-multi-discipline-cognitive/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhen Huang, Zengzhi Wang, Shijie Xia, et al.*2024 · 56 citations*
113. **[SciAgent: Tool-augmented Language Models for Scientific Reasoning](https://md.research.elamur.ai/free/en/papers/ma-2024-sciagent-tool-augmented-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yubo Ma, Zhibin Gou, Junheng Hao, et al.*2024 · 55 citations*
114. **[InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-4khd-pioneering/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 54 citations*
115. [**Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planning arXiv:2406.14283**Chaojie Wang, Yanchen Deng, Zhiyi Lyu, et al.*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-q-improving-multi-step-reasoning/)
116. [**FIMO: A Challenge Formal Dataset for Automated Theorem Proving arXiv:2309.04295**Chengwu Liu, Jianhao Shen, Huajian Xin, et al.*2023 · 53 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-fimo-challenge-formal-dataset-automated/)
117. [**CogVLM2: Visual Language Models for Image and Video Understanding arXiv:2408.16500**Wenyi Hong, Weihan Wang, Ming Ding, et al.*2024 · 52 citations*](https://md.research.elamur.ai/free/en/papers/hong-2024-cogvlm2-visual-language-models/)
118. **[JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ma-2024-janusflow-harmonizing-autoregression-rectified/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Yiyang Ma, Xingchao Liu, Xiaokang Chen, et al.*2024 · 52 citations*
119. [**Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies arXiv:2407.13623**Chaofan Tao, Qian Liu, Longxu Dou, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/tao-2024-scaling-laws-vocabulary-larger-models/)
120. [**Stable LM 2 1.6B Technical Report arXiv:2402.17834**Marco Bellagente, Jonathan Tow, Dakota Mahan, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/bellagente-2024-stable-lm-2-1-6b/)
121. [**MathChat: Converse to Tackle Challenging Math Problems with LLM Agents arXiv:2306.01337**Yiran Wu; Feiran Jia; Shaokun Zhang; Hangyu Li; Erkang Zhu; Yue Wang; Yin Tat Lee; Richard Peng; Qingyun Wu;, Chi Wang*2023 · 46 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-mathchat-converse-tackle-challenging-math/)
122. [**EuroLLM-9B: Technical Report arXiv:2506.04079**Pedro Henrique Martins, Joao Alves, Patrick Fernandes, et al.*2025 · 45 citations*](https://md.research.elamur.ai/free/en/papers/martins-2025-eurollm-9b-technical-report/)
123. **[Augmenting Math Word Problems via Iterative Question Composing](https://md.research.elamur.ai/free/en/papers/liu-2024-augmenting-math-word-problems-iterative/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Haoxiong Liu, Yifan Zhang, Yifan Luo, et al.*2024 · 44 citations*
124. [**NVLM: Open Frontier-Class Multimodal LLMs arXiv:2409.11402**Wenliang Dai, Nayeon Lee, Boxin Wang, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dai-2024-nvlm-open-frontier-class-multimodal/)
125. **[Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2025-towards-thinking-optimal-scaling-test/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wenkai Yang, Shuming Ma, Yankai Lin, et al.*2025 · 43 citations*
126. **[Improve Vision Language Model Chain-of-thought Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2025-improve-vision-language-model-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruohong Zhang, Bowen Zhang, Yanghao Li, et al.*2025 · 42 citations*
127. [**Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling arXiv:2502.06703**Runze Liu, Junqi Gao, Jian Zhao, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-1b-llm-surpass-405b-llm/)
128. **[MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scale](https://md.research.elamur.ai/free/en/papers/guo-2025-mammoth-vl-eliciting-multimodal-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiawei Guo, Tianyu Zheng, Yizhi Li, et al.*2025 · 40 citations*
129. [**InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output arXiv:2407.03320**Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-internlm-xcomposer-2-5/)
130. [**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/)
131. [**SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models arXiv:2504.11468**Hardy Chen, Haoqin Tu, Fali Wang, et al.*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-sft-rl-early-investigation-training/)
132. **[MasRouter: Learning to Route LLMs for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/yue-2025-masrouter-learning-route-llms-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanwei Yue, Guibin Zhang, Boyang Liu, et al.*2025 · 35 citations*
133. **[Vision-Language Models Can Self-Improve Reasoning via Reflection](https://md.research.elamur.ai/free/en/papers/cheng-2025-vision-language-models-can-self/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kanzhi Cheng, Li YanTao, Fangzhi Xu, et al.*2025 · 35 citations*
134. [**Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding arXiv:2405.08748**Zhimin Li, Jianwei Zhang, Qin Lin, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-hunyuan-dit-powerful-multi/)
135. [**On the Diversity of Synthetic Data and its Impact on Training Large Language Models arXiv:2410.15226**Hao Chen, Abdul Waheed, Xiang Li, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-diversity-synthetic-data-impact-training/)
136. **[mCoT: Multilingual Instruction Tuning for Reasoning Consistency in Language Models](https://md.research.elamur.ai/free/en/papers/lai-2024-mcot-multilingual-instruction-tuning-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huiyuan Lai, Malvina Nissim*2024 · 34 citations*
137. **[Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing](https://md.research.elamur.ai/free/en/papers/jiao-2024-learning-planning-based-reasoning-trajectories/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fangkai Jiao, Chengwei Qin, Zhengyuan Liu, et al.*2024 · 31 citations*
138. **[Knowledge Boundary of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/li-2025-knowledge-boundary-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Moxin Li, Yong Zhao, Wenxuan Zhang, et al.*2025 · 30 citations*
139. [**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/)
140. [**Language Models as Science Tutors arXiv:2402.11111**Alexis Chevalier, Jiayi Geng, Alexander Wettig, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/chevalier-2024-language-models-science-tutors/)
141. [**InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language Models arXiv:2503.06692**Yuchen Yan, Yongliang Shen, Yang Liu, et al.*2025 · 29 citations*](https://md.research.elamur.ai/free/en/papers/yan-2025-inftythink-breaking-length-limits-long/)
142. **[Towards Effective and Efficient Continual Pre-training of Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-effective-efficient-continual-pre-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jie Chen, Zhipeng Chen, Jiapeng Wang, et al.*2025 · 29 citations*
143. **[LangBridge: Multilingual Reasoning Without Multilingual Supervision](https://md.research.elamur.ai/free/en/papers/yoon-2024-langbridge-multilingual-reasoning-without-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dongkeun Yoon, Joel Jang, Sungdong Kim, et al.*2024 · 29 citations*
144. [**Baichuan-Omni-1.5 Technical Report arXiv:2501.15368**Yadong Li, Jun Liu, Tao Zhang, et al.*2025 · 28 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-baichuan-omni-1-5/)
145. **[Automatic Instruction Evolving for Large Language Models](https://md.research.elamur.ai/free/en/papers/zeng-2024-automatic-instruction-evolving-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weihao Zeng, Can Xu, Yingxiu Zhao, et al.*2024 · 28 citations*
146. [**Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning arXiv:2512.20848**NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.*2025 · 27 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-3-nano-open-efficient/)
147. [**Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling arXiv:2408.16737**Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2024-smaller-weaker-yet-better-training/)
148. [**DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning arXiv:2310.02954**Jing Xiong, Zixuan Li, Chuanyang Zheng, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-dq-lore-dual-queries-low/)
149. **[FuseChat: Knowledge Fusion of Chat Models](https://md.research.elamur.ai/free/en/papers/wan-2025-fusechat-knowledge-fusion-chat-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fanqi Wan, Longguang Zhong, Ziyi Yang, et al.*2025 · 25 citations*
150. **[Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space](https://md.research.elamur.ai/free/en/papers/zhang-2025-soft-thinking-unlocking-reasoning-potential/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhen Zhang, Xuehai He, Weixiang Yan, et al.*2025 · 25 citations*
151. [**HunyuanProver: A Scalable Data Synthesis Framework and Guided Tree Search for Automated Theorem Proving arXiv:2412.20735**Yang Li, Dong Du, Linfeng Song, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-hunyuanprover-scalable-data-synthesis/)
152. [**MiniCPM-V 4.5: Cooking Efficient MLLMs via Architecture, Data, and Training Recipe arXiv:2509.18154**Tianyu Yu, Zefan Wang, Chongyi Wang, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/yu-2025-minicpm-v-4-5/)
153. **[ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection](https://md.research.elamur.ai/free/en/papers/yan-2026-errorradar-benchmarking-complex-mathematical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Shen Wang, Jiahao Huo, et al.*2026 · 23 citations*
154. **[Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm Perspective](https://md.research.elamur.ai/free/en/papers/yu-2025-chain-reasoning-unified-mathematical-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiyao Yu, Yuxiang Zhang, Dongdong Zhang, et al.*2025 · 23 citations*
155. [**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/)
156. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
157. [**Step-Video-T2V Technical Report: The Practice, Challenges, and Future of Video Foundation Model arXiv:2502.10248**Guoqing Ma, Haoyang Huang, Kun Yan, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/ma-2025-step-video-t2v-technical/)
158. **[Jailbreak Large Vision-Language Models Through Multi-Modal Linkage](https://md.research.elamur.ai/free/en/papers/wang-2025-jailbreak-large-vision-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Wang, Xiaofei Zhou, Yichen Wang, et al.*2025 · 20 citations*
159. **[SLAM: Towards Efficient Multilingual Reasoning via Selective Language Alignment](https://md.research.elamur.ai/free/en/papers/fan-2025-slam-efficient-multilingual-reasoning-selective/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yuchun Fan, Yongyu Mu, YiLin Wang, et al.*2025 · 20 citations*
160. **[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*
161. **[MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought Verification](https://md.research.elamur.ai/free/en/papers/sun-2025-mm-verify-enhancing-multimodal-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linzhuang Sun, Hao Liang, Jingxuan Wei, et al.*2025 · 19 citations*
162. [**MA-LoT: Model-Collaboration Lean-based Long Chain-of-Thought Reasoning enhances Formal Theorem Proving arXiv:2503.03205**Ruida Wang, Rui Pan, Yuxin Li, et al.*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-ma-lot-model-collaboration-lean/)
163. [**FormalAlign: Automated Alignment Evaluation for Autoformalization arXiv:2410.10135**Jianqiao Lu, Yingjia Wan, Yinya Huang, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-formalalign-automated-alignment-evaluation-autoformalization/)
164. [**HunyuanImage 3.0 Technical Report arXiv:2509.23951**Tencent Hunyuan Foundation Model Team*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-hunyuan-hunyuanimage-3-0-technical/)
165. [**Language Matters: How Do Multilingual Input and Reasoning Paths Affect Large Reasoning Models? arXiv:2505.17407**Zhi Rui Tam, Cheng-Kuang Wu, Yu Ying Chiu, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/tam-2025-language-matters-multilingual-input-reasoning/)
166. **[STaR-SQL: Self-Taught Reasoner for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/he-2025-star-sql-self-taught-reasoner/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingqian He, Yongliang Shen, Wenqi Zhang, et al.*2025 · 17 citations*
167. **[Let the Expert Stick to His Last: Expert-Specialized Fine-Tuning for Sparse Architectural Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-let-expert-stick-his/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zihan Wang, Deli Chen, Damai Dai, et al.*2024 · 17 citations*
168. [**Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models arXiv:2308.00304**Jiaao Chen, Xiaoman Pan, Dian Yu, et al.*2023 · 17 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-skills-context-prompting-unlocking-compositionality/)
169. **[ATLAS: Autoformalizing Theorems through Lifting, Augmentation, and Synthesis of Data](https://md.research.elamur.ai/free/en/papers/liu-2025-atlas-autoformalizing-theorems-through-lifting/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoyang Liu, Kangjie Bao, Jiashuo Zhang, et al.*2025 · 16 citations*
170. **[Language Models Encode the Value of Numbers Linearly](https://md.research.elamur.ai/free/en/papers/zhu-2025-language-models-encode-value-numbers/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Fangwei Zhu, Damai Dai, Zhifang Sui*2025 · 15 citations*
171. [**Preference Optimization for Reasoning with Pseudo Feedback arXiv:2411.16345**Fangkai Jiao, Geyang Guo, Xingxing Zhang, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/jiao-2024-preference-optimization-reasoning-pseudo-feedback/)
172. [**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/)
173. [**Understanding Chain-of-Thought in LLMs through Information Theory arXiv:2411.11984**Jean-Francois Ton, Muhammad Faaiz Taufiq, Yang Liu*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/ton-2024-understanding-chain-thought-llms-through/)
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182. [**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/)
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185. [**REAL-Prover: Retrieval Augmented Lean Prover for Mathematical Reasoning arXiv:2505.20613**Ziju Shen, Naohao Huang, Fanyi Yang, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/shen-2025-real-prover-retrieval-augmented-lean/)
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193. [**Stable Code Technical Report arXiv:2404.01226**Nikhil Pinnaparaju, Reshinth Adithyan, Duy Phung, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/pinnaparaju-2024-stable-code-technical-report/)
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195. **[Exposing the Achilles' Heel: Evaluating LLMs Ability to Handle Mistakes in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/singh-2025-exposing-achilles-heel-evaluating-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joykirat Singh, Akshay Nambi, Vibhav Vineet*2025 · 8 citations*
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198. **[T2I-FactualBench: Benchmarking the Factuality of Text-to-Image Models with Knowledge-Intensive Concepts](https://md.research.elamur.ai/free/en/papers/huang-2025-t2i-factualbench-benchmarking-factuality-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwei Huang, Wanggui He, Quanyu Long, et al.*2025 · 8 citations*
199. [**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/)
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