---
title: "Who cites Torsten Hoefler — 825 papers of our library"
description: "825 papers of the Elamur Research library cite the works of Torsten Hoefler, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/torsten-hoefler/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/torsten-hoefler/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Torsten Hoefler](https://md.research.elamur.ai/free/en/authors/torsten-hoefler/) / cited by

# Who cites Torsten Hoefler

829 citations of their works from 825 papers of our library (of the 149,439 whose bibliographies we read) · 186 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Torsten Hoefler](https://md.research.elamur.ai/free/en/authors/torsten-hoefler/)

**1** [2](https://md.research.elamur.ai/free/en/authors/torsten-hoefler/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/torsten-hoefler/cited-by/page/2/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
2. [**Unleashing the potential of prompt engineering for large language models arXiv:2310.14735 · Patterns 6(6) 101,260 (2025)**Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.*2023 · 536 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-unleashing-potential-prompt-engineering-large/)
3. [**A Review of Large Language Models and Autonomous Agents in Chemistry arXiv:2407.01603**Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2024-review-large-language-models-autonomous/)
4. **[A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions](https://md.research.elamur.ai/free/en/papers/wu-2025-survey-llm-generated-text-detection/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Junchao Wu, Shu Yang, Runzhe Zhan, et al.*2025 · 277 citations*
5. [**Large Language Monkeys: Scaling Inference Compute with Repeated Sampling arXiv:2407.21787**Bradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.*2024 · 270 citations*](https://md.research.elamur.ai/free/en/papers/brown-2024-large-language-monkeys-scaling-inference/)
6. **[Large Language Models for Data Annotation and Synthesis: A Survey](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 262 citations*
7. [**ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep Learning SC 2021**Samyam Rajbhandari, Olatunji Ruwase, Jeff Rasley, et al.*2021 · 254 citations*](https://md.research.elamur.ai/free/en/papers/rajbhandari-2021-zero-infinity-breaking-gpu-memory/)
8. **[MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2024-medagents-large-language-models-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiangru Tang, Anni Zou, Zhuosheng Zhang, et al.*2024 · 246 citations*
9. **[ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search](https://md.research.elamur.ai/free/en/papers/zhang-2024-rest-mcts-llm-self-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Dan Zhang, Sining Zhoubian, Ziniu Hu, et al.*2024 · 200 citations*
10. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
11. [**Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs arXiv:2412.21187**Xingyu Chen, Jiahao Xu, Tian Liang, et al.*2024 · 192 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-think-that-much-2-3/)
12. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
13. **[VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks](https://md.research.elamur.ai/free/en/papers/koh-2024-visualwebarena-evaluating-multimodal-agents-realistic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jing Yu Koh, Robert Lo, Lawrence Jang, et al.*2024 · 184 citations*
14. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
15. [**Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution arXiv:2309.16797**Chrisantha Fernando, Dylan Banarse, Henryk Michalewski, et al.*2023 · 174 citations*](https://md.research.elamur.ai/free/en/papers/fernando-2023-promptbreeder-self-referential-self-improvement/)
16. [**Capabilities of Gemini Models in Medicine arXiv:2404.18416**Khaled Saab, Tao Tu, Wei-Hung Weng, et al.*2024 · 170 citations*](https://md.research.elamur.ai/free/en/papers/saab-2024-capabilities-gemini-models-medicine/)
17. [**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/)
18. **[ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMs](https://md.research.elamur.ai/free/en/papers/chen-2024-reconcile-round-table-conference-improves/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Justin Chen, Swarnadeep Saha, Mohit Bansal*2024 · 156 citations*
19. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning arXiv:2409.12183**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 138 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/)
20. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 130 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
21. **[Faithful Logical Reasoning via Symbolic Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/xu-2024-faithful-logical-reasoning-symbolic-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jundong Xu, Hao Fei, Liangming Pan, et al.*2024 · 129 citations*
22. [**Understanding the planning of LLM agents: A survey arXiv:2402.02716**Xu Huang, Weiwen Liu, Xiaolong Chen, et al.*2024 · 128 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-understanding-planning-llm-agents-survey/)
23. [**TravelPlanner: A Benchmark for Real-World Planning with Language Agents arXiv:2402.01622**Jian Xie, Kai Zhang, Jiangjie Chen, et al.*2024 · 125 citations*](https://md.research.elamur.ai/free/en/papers/xie-2024-travelplanner-benchmark-real-world-planning/)
24. [**Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future arXiv:2309.15402**Zheng Chu, Jingchang Chen, Qianglong Chen, et al.*2023 · 125 citations*](https://md.research.elamur.ai/free/en/papers/chu-2023-navigate-through-enigmatic-labyrinth-survey/)
25. [**Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models arXiv:2501.09686**Fengli Xu, Qianyue Hao, Zefang Zong, et al.*2025 · 120 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-towards-large-reasoning-models-survey/)
26. [**QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving MLSys 2025**Yujun Lin, Haotian Tang, Shang Yang, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-qserve-w4a8kv4-quantization-system-co/)
27. [**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/)
28. [**Efficient Large Language Models: A Survey arXiv:2312.03863**Zhongwei Wan, Xin Wang, Che Liu, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/wan-2023-efficient-large-language-models-survey/)
29. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations*
30. **[Rethinking the Bounds of LLM Reasoning: Are Multi-Agent Discussions the Key?](https://md.research.elamur.ai/free/en/papers/wang-2024-rethinking-bounds-llm-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qineng Wang, Zihao Wang, Ying Su, et al.*2024 · 107 citations*
31. **[Multi-Step Reasoning with Large Language Models, a Survey](https://md.research.elamur.ai/free/en/papers/plaat-2024-multi-step-reasoning-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aske Plaat, Annie Wong, Suzan Verberne, et al.*2024 · 106 citations*
32. [**Chain of Draft: Thinking Faster by Writing Less arXiv:2502.18600**Silei Xu, Wenhao Xie, Lingxiao Zhao, et al.*2025 · 98 citations*](https://md.research.elamur.ai/free/en/papers/xu-2025-chain-draft-thinking-faster-writing/)
33. [**GLM-5: from Vibe Coding to Agentic Engineering arXiv:2602.15763**Aohan Zeng, Xin Lv, Zhenyu Hou, et al.*2026 · 95 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-5-glm-5-vibe-coding/)
34. **[Boosting Language Models Reasoning with Chain-of-Knowledge Prompting](https://md.research.elamur.ai/free/en/papers/wang-2024-boosting-language-models-reasoning-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianing Wang, Qiushi Sun, Xiang Li, et al.*2024 · 94 citations*
35. [**Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models arXiv:2503.06749**Wenxuan Huang, Bohan Jia, Zijie Zhai, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/huang-2025-vision-r1-incentivizing-reasoning-capability/)
36. **[Data Interpreter: An LLM Agent for Data Science](https://md.research.elamur.ai/free/en/papers/hong-2025-data-interpreter-llm-agent-data/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sirui Hong, Yizhang Lin, Bang Liu, et al.*2025 · 91 citations*
37. [**Language Agents as Optimizable Graphs arXiv:2402.16823**Mingchen Zhuge, Wenyi Wang, Louis Kirsch, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/zhuge-2024-language-agents-optimizable-graphs/)
38. **[Roleplay-doh: Enabling Domain-Experts to Create LLM-simulated Patients via Eliciting and Adhering to Principles](https://md.research.elamur.ai/free/en/papers/louie-2024-roleplay-doh-enabling-domain-experts/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ryan Louie, Ananjan Nandi, William Fang, et al.*2024 · 90 citations*
39. **[Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs](https://md.research.elamur.ai/free/en/papers/jin-2024-graph-chain-thought-augmenting-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bowen Jin, Chulin Xie, Jiawei Zhang, et al.*2024 · 89 citations*
40. [**Retrieval-Augmented Generation with Graphs (GraphRAG) arXiv:2501.00309**Haoyu Han, Yu Wang, Harry Shomer, et al.*2025 · 87 citations*](https://md.research.elamur.ai/free/en/papers/han-2025-retrieval-augmented-generation-graphs-graphrag/)
41. [**Rethinking Interpretability in the Era of Large Language Models arXiv:2402.01761**Chandan Singh, Jeevana Priya Inala, Michel Galley, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-rethinking-interpretability-era-large-language/)
42. **[EfficientQAT: Efficient Quantization-Aware Training for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-efficientqat-efficient-quantization-aware-training/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengzhao Chen, Wenqi Shao, Peng Xu, et al.*2025 · 82 citations*
43. [**Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoning arXiv:2410.14211**Xingyu Tan, Xiaoyang Wang, Qing Liu, et al.*2024 · 80 citations*](https://md.research.elamur.ai/free/en/papers/tan-2024-paths-over-graph-knowledge-graph/)
44. **[Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing](https://md.research.elamur.ai/free/en/papers/tian-2024-toward-self-improvement-llms-imagination/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ye Tian, Baolin Peng, Linfeng Song, et al.*2024 · 80 citations*
45. [**A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? arXiv:2503.24235**Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-survey-test-time-scaling-large/)
46. **[Self-Contrast: Better Reflection Through Inconsistent Solving Perspectives](https://md.research.elamur.ai/free/en/papers/zhang-2024-self-contrast-better-reflection-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqi Zhang, Yongliang Shen, Linjuan Wu, et al.*2024 · 75 citations*
47. **[Training Language Models to Reason Efficiently](https://md.research.elamur.ai/free/en/papers/arora-2025-training-language-models-reason-efficiently/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Daman Arora, Andrea Zanette*2025 · 74 citations*
48. [**Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers arXiv:2408.06195**Zhenting Qi, Mingyuan Ma, Jiahang Xu, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/qi-2024-mutual-reasoning-makes-smaller-llms/)
49. [**Cumulative Reasoning with Large Language Models arXiv:2308.04371**Yifan Zhang, Jingqin Yang, Yang Yuan, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-cumulative-reasoning-large-language-models/)
50. [**Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation arXiv:2307.15337**Xuefei Ning, Zinan Lin, Zixuan Zhou, et al.*2023 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ning-2023-skeleton-thought-prompting-llms-efficient/)
51. [**Scaling Large Language Model-based Multi-Agent Collaboration arXiv:2406.07155**Chen Qian, Zihao Xie, YiFei Wang, et al.*2024 · 70 citations*](https://md.research.elamur.ai/free/en/papers/qian-2024-scaling-large-language-model/)
52. [**Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents arXiv:2408.07199**Pranav Putta, Edmund Mills, Naman Garg, et al.*2024 · 68 citations*](https://md.research.elamur.ai/free/en/papers/putta-2024-agent-q-advanced-reasoning-learning/)
53. [**Branch-Solve-Merge Improves Large Language Model Evaluation and Generation arXiv:2310.15123**Swarnadeep Saha, Omer Levy, Asli Celikyilmaz, et al.*2023 · 68 citations*](https://md.research.elamur.ai/free/en/papers/saha-2023-branch-solve-merge-improves-large/)
54. **[Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2024-buffer-thoughts-thought-augmented-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ling Yang, Zhaochen Yu, Tianjun Zhang, et al.*2024 · 67 citations*
55. **[Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering](https://md.research.elamur.ai/free/en/papers/shi-2024-generate-then-ground-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengliang Shi, Shuo Zhang, Weiwei Sun, et al.*2024 · 65 citations*
56. **[A Peek into Token Bias: Large Language Models Are Not Yet Genuine Reasoners](https://md.research.elamur.ai/free/en/papers/jiang-2024-peek-into-token-bias-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao, et al.*2024 · 64 citations*
57. [**Evaluation of OpenAI o1: Opportunities and Challenges of AGI arXiv:2409.18486**Tianyang Zhong, Zhengliang Liu, Yi Pan, et al.*2024 · 64 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-evaluation-openai-o1-opportunities-challenges/)
58. [**Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding arXiv:2401.12954**Mirac Suzgun, Adam Tauman Kalai*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/suzgun-2024-meta-prompting-enhancing-language-models/)
59. [**OS-Copilot: Towards Generalist Computer Agents with Self-Improvement arXiv:2402.07456**Zhiyong Wu, Chengcheng Han, Zichen Ding, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-os-copilot-towards-generalist-computer/)
60. [**Teaching Large Language Models to Reason with Reinforcement Learning arXiv:2403.04642**Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-teaching-large-language-models-reason/)
61. [**Tree Search for Language Model Agents arXiv:2407.01476**Jing Yu Koh, Stephen McAleer, Daniel Fried, et al.*2024 · 61 citations*](https://md.research.elamur.ai/free/en/papers/koh-2024-tree-search-language-model-agents/)
62. **[SoftCoT: Soft Chain-of-Thought for Efficient Reasoning with LLMs](https://md.research.elamur.ai/free/en/papers/xu-2025-softcot-soft-chain-thought-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yige Xu, Xu Guo, Zhiwei Zeng, et al.*2025 · 58 citations*
63. **[Can LLMs Learn from Previous Mistakes? Investigating LLMs' Errors to Boost for Reasoning](https://md.research.elamur.ai/free/en/papers/tong-2024-can-llms-learn-previous-mistakes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongqi Tong, Dawei Li, Sizhe Wang, et al.*2024 · 57 citations*
64. [**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/)
65. **[Agent-Pro: Learning to Evolve via Policy-Level Reflection and Optimization](https://md.research.elamur.ai/free/en/papers/zhang-2024-agent-pro-learning-evolve-policy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenqi Zhang, Ke Tang, Hai Wu, et al.*2024 · 52 citations*
66. **[Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching](https://md.research.elamur.ai/free/en/papers/aytes-2025-sketch-thought-efficient-llm-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Simon A. Aytes, Jinheon Baek, Sung Ju Hwang*2025 · 51 citations*
67. [**From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models arXiv:2406.16838**Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2024-decoding-meta-generation-inference-time/)
68. **[Puzzle Solving using Reasoning of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/giadikiaroglou-2024-puzzle-solving-reasoning-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Panagiotis Giadikiaroglou, Maria Lymperaiou, Giorgos Filandrianos, et al.*2024 · 48 citations*
69. [**RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation arXiv:2403.05313**Zihao Wang, Anji Liu, Haowei Lin, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-rat-retrieval-augmented-thoughts-elicit/)
70. [**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/)
71. **[Disentangling Memory and Reasoning Ability in Large Language Models](https://md.research.elamur.ai/free/en/papers/jin-2025-disentangling-memory-reasoning-ability-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingyu Jin, Weidi Luo, Sitao Cheng, et al.*2025 · 45 citations*
72. [**GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements arXiv:2402.10963**Alex Havrilla, Sharath Raparthy, Christoforus Nalmpantis, et al.*2024 · 45 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-glore-where-improve-llm-reasoning/)
73. [**Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning arXiv:2412.09078**Zhenni Bi, Kai Han, Chuanjian Liu, et al.*2024 · 43 citations*](https://md.research.elamur.ai/free/en/papers/bi-2024-forest-thought-scaling-test-time/)
74. **[MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL Generation](https://md.research.elamur.ai/free/en/papers/lee-2025-mcs-sql-leveraging-multiple-prompts/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Dongjun Lee, Choongwon Park, Jaehyuk Kim, et al.*2025 · 42 citations*
75. [**How FaR Are Large Language Models From Agents with Theory-of-Mind? arXiv:2310.03051**Pei Zhou, Aman Madaan, Srividya Pranavi Potharaju, et al.*2023 · 40 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-far-large-language-models-agents/)
76. **[Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning Corpus](https://md.research.elamur.ai/free/en/papers/lee-2024-reasoning-abilities-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/)**Seungpil Lee, Woochang Sim, Donghyeon Shin, et al.*2024 · 38 citations*
77. **[Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory](https://md.research.elamur.ai/free/en/papers/suzgun-2026-dynamic-cheatsheet-test-time-learning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mirac Suzgun, Mert Yuksekgonul, Federico Bianchi, et al.*2026 · 37 citations*
78. [**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/)
79. **[Is Sarcasm Detection A Step-by-Step Reasoning Process in Large Language Models?](https://md.research.elamur.ai/free/en/papers/yao-2024-sarcasm-detection-step-step-reasoning/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Ben Yao, Yazhou Zhang, Qiuchi Li, et al.*2024 · 33 citations*
80. [**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/)
81. [**One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support arXiv:2306.09237**Ronja Stern, Vishvaksenan Rasiah, Veton Matoshi, et al.*2023 · 29 citations*](https://md.research.elamur.ai/free/en/papers/stern-2023-one-law-many-languages-benchmarking/)
82. [**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/)
83. [**StateFlow: Enhancing LLM Task-Solving through State-Driven Workflows arXiv:2403.11322**Yiran Wu, Tianwei Yue, Shaokun Zhang, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-stateflow-enhancing-llm-task-solving/)
84. **[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*
85. [**MiniCPM4: Ultra-Efficient LLMs on End Devices arXiv:2506.07900**MiniCPM Team, Chaojun Xiao, Yuxuan Li, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/minicpm-team-2025-minicpm4-ultra-efficient-llms/)
86. **[“Give Me BF16 or Give Me Death”? Accuracy-Performance Trade-Offs in LLM Quantization](https://md.research.elamur.ai/free/en/papers/kurtic-2025-give-me-bf16-or-give/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eldar Kurtic, Alexandre Noll Marques, Shubhra Pandit, et al.*2025 · 21 citations*
87. [**Baichuan-M2: Scaling Medical Capability with Large Verifier System arXiv:2509.02208**Chengfeng Dou, Chong Liu, Fan Yang, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-m2-baichuan-m2-scaling-medical/)
88. **[A Survey of Post-Training Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/lai-2025-survey-post-training-scaling-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanyu Lai, Xiao Liu, Junjie Gao, et al.*2025 · 18 citations*
89. **[Large Language Models Can Solve Real-World Planning Rigorously with Formal Verification Tools](https://md.research.elamur.ai/free/en/papers/hao-2025-large-language-models-can-solve/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yilun Hao, Yongchao Chen, Yang Zhang, et al.*2025 · 18 citations*
90. **[The Role of Deductive and Inductive Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/cai-2025-role-deductive-inductive-reasoning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chengkun Cai, Xu Zhao, Haoliang Liu, et al.*2025 · 17 citations*
91. **[Aristotle: Mastering Logical Reasoning with A Logic-Complete Decompose-Search-Resolve Framework](https://md.research.elamur.ai/free/en/papers/xu-2025-aristotle-mastering-logical-reasoning-logic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jundong Xu, Hao Fei, Meng Luo, et al.*2025 · 16 citations*
92. [**Towards Reasoning Ability of Small Language Models arXiv:2502.11569**Gaurav Srivastava, Shuxiang Cao, Xuan Wang*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2025-towards-reasoning-ability-small-language/)
93. [**Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models arXiv:2411.02382**Guangzhi Xiong, Eric Xie, Amir Hassan Shariatmadari, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2024-improving-scientific-hypothesis-generation-knowledge/)
94. **[Self-Correcting RAG: Enhancing Faithfulness via MMKP Context Selection and NLI-Guided MCTS](https://md.research.elamur.ai/free/en/papers/xu-2026-self-correcting-rag-enhancing-faithfulness/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shijia Xu, Zhou Wu, Xiaolong Jia, et al.*2026 · 15 citations*
95. [**ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning arXiv:2501.06590**Xiangru Tang, Tianyu Hu, Muyang Ye, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/tang-2025-chemagent-self-updating-library-large/)
96. **[Reasoning about Uncertainty: Do Reasoning Models Know When They Don't Know?](https://md.research.elamur.ai/free/en/papers/mei-2026-reasoning-about-uncertainty-do-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiting Mei, Christina Zhang, Tenny Yin, et al.*2026 · 14 citations*
97. **[Meta-Reasoner: Dynamic Guidance for Optimized Inference-time Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/sui-2026-meta-reasoner-dynamic-guidance-optimized/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Sui, Yufei He, Tri Cao, et al.*2026 · 13 citations*
98. **[NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-Neurons](https://md.research.elamur.ai/free/en/papers/dong-2026-neureasoner-explainable-controllable-unified-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haonan Dong, Kehan Jiang, Haoran Ye, et al.*2026 · 13 citations*
99. **[Prompting Large Language Models to Tackle the Full Software Development Lifecycle: A Case Study](https://md.research.elamur.ai/free/en/papers/li-2025-prompting-large-language-models-tackle/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Bowen Li, Wenhan Wu, Ziwei Tang, et al.*2025 · 13 citations*
100. **[Parity-Aware Byte-Pair Encoding: Improving Cross-lingual Fairness in Tokenization](https://md.research.elamur.ai/free/en/papers/foroutan-2026-parity-aware-byte-pair-encoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Negar Foroutan, Clara Meister, Debjit Paul, et al.*2026 · 12 citations*

**1** [2](https://md.research.elamur.ai/free/en/authors/torsten-hoefler/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/torsten-hoefler/cited-by/page/2/)

- [← back to](https://md.research.elamur.ai/free/en/authors/torsten-hoefler/) — Torsten Hoefler