---
title: "Who cites Shuofei Qiao — 215 papers of our library"
description: "215 papers of the Elamur Research library cite the works of Shuofei Qiao, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/shuofei-qiao/cited-by/"
---
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# Who cites Shuofei Qiao

215 citations of their works from 215 papers of our library (of the 149,439 whose bibliographies we read) · 69 with a page here, the most cited first · [← Shuofei Qiao](https://md.research.elamur.ai/free/en/authors/shuofei-qiao/)

1. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
2. **[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*
3. [**A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity arXiv:2302.04023**Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, et al.*2023 · 882 citations*](https://md.research.elamur.ai/free/en/papers/bang-2023-multitask-multilingual-multimodal-evaluation-chatgpt/)
4. **[Towards Reasoning in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/huang-2023-reasoning-large-language-models-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jie Huang, Kevin Chen-Chuan Chang*2023 · 780 citations*
5. **[Large Language Models for Generative Information Extraction: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2023-large-language-models-generative-information/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Derong Xu, Wei Chen, Wenjun Peng, et al.*2023 · 406 citations*
6. [**Augmented Language Models: a Survey arXiv:2302.07842**Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.*2023 · 369 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-augmented-language-models-survey/)
7. **[Large Language Models are Better Reasoners with Self-Verification](https://md.research.elamur.ai/free/en/papers/weng-2023-large-language-models-are-better/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yixuan Weng, Minjun Zhu, Fei Xia, et al.*2023 · 304 citations*
8. **[Combating Misinformation in the Age of LLMs: Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/chen-2023-combating-misinformation-age-llms-opportunities/) [AI Magazine](https://md.research.elamur.ai/free/en/venues/ai-magazine/)**Canyu Chen, Kai Shu*2023 · 214 citations*
9. **[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*
10. [**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/)
11. **[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*
12. [**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/)
13. [**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/)
14. [**Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback arXiv:2305.10142**Yao Fu, Hao Peng, Tushar Khot, et al.*2023 · 132 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-improving-language-model-negotiation-self/)
15. **[Natural Language Reasoning, A Survey](https://md.research.elamur.ai/free/en/papers/yu-2023-natural-language-reasoning-survey/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Fei Yu, Hongbo Zhang, Prayag Tiwari, et al.*2023 · 130 citations*
16. [**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/)
17. [**Hallucination of Multimodal Large Language Models: A Survey arXiv:2404.18930**Zechen Bai, Pichao Wang, Tianjun Xiao, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-hallucination-multimodal-large-language-models/)
18. **[Answering Questions by Meta-Reasoning over Multiple Chains of Thought](https://md.research.elamur.ai/free/en/papers/yoran-2023-answering-questions-meta-reasoning-over/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ori Yoran, Tomer Wolfson, Ben Bogin, et al.*2023 · 99 citations*
19. [**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/)
20. [**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/)
21. [**Contrastive Decoding Improves Reasoning in Large Language Models arXiv:2309.09117**Sean O'Brien, Mike Lewis*2023 · 68 citations*](https://md.research.elamur.ai/free/en/papers/o-brien-2023-contrastive-decoding-improves-reasoning-large/)
22. **[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*
23. [**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/)
24. [**Beyond Accuracy: Evaluating the Reasoning Behavior of Large Language Models — A Survey arXiv:2404.01869**Philipp Mondorf, Barbara Plank*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/mondorf-2024-accuracy-evaluating-reasoning-behavior-large/)
25. **[MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks](https://md.research.elamur.ai/free/en/papers/zhang-2024-mlcopilot-unleashing-power-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Lei Zhang, Yuge Zhang, Kan Ren, et al.*2024 · 52 citations*
26. **[LightThinker: Thinking Step-by-Step Compression](https://md.research.elamur.ai/free/en/papers/zhang-2025-lightthinker-thinking-step-step-compression/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jintian Zhang, Yuqi Zhu, Mengshu Sun, et al.*2025 · 50 citations*
27. **[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*
28. [**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/)
29. **[WebAgent-R1: Training Web Agents via End-to-End Multi-Turn Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wei-2025-webagent-r1-training-web-agents/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhepei Wei, Wenlin Yao, Yao Liu, et al.*2025 · 36 citations*
30. [**Through the Lens of Core Competency: Survey on Evaluation of Large Language Models arXiv:2308.07902**Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-through-lens-core-competency-survey/)
31. [**BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models arXiv:2309.06085**Wei Qi Leong, Jian Gang Ngui, Yosephine Susanto, et al.*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/leong-2023-bhasa-holistic-southeast-asian-linguistic/)
32. [**LLMs and the Abstraction and Reasoning Corpus: Successes, Failures, and the Importance of Object-based Representations arXiv:2305.18354**Yudong Xu, Wenhao Li, Pashootan Vaezipoor, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-llms-abstraction-reasoning-corpus-successes/)
33. [**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/)
34. [**Logical Reasoning over Natural Language as Knowledge Representation: A Survey arXiv:2303.12023**Zonglin Yang, Xinya Du, Rui Mao, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-logical-reasoning-over-natural-language/)
35. [**CodeI/O: Condensing Reasoning Patterns via Code Input-Output Prediction arXiv:2502.07316**Junlong Li, Daya Guo, Dejian Yang, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-codei-o-condensing-reasoning/)
36. **[ConCISE: Confidence-guided Compression in Step-by-step Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/qiao-2025-concise-confidence-guided-compression-step/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ziqing Qiao, Yongheng Deng, Jiali Zeng, et al.*2025 · 19 citations*
37. **[Multilingual and Explainable Text Detoxification with Parallel Corpora](https://md.research.elamur.ai/free/en/papers/dementieva-2025-multilingual-explainable-text-detoxification-parallel/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Daryna Dementieva, Nikolay Babakov, Amit Ronen, et al.*2025 · 19 citations*
38. [**In-Context Principle Learning from Mistakes arXiv:2402.05403**Tianjun Zhang, Aman Madaan, Luyu Gao, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-context-principle-learning-mistakes/)
39. [**Timo: Towards Better Temporal Reasoning for Language Models arXiv:2406.14192**Zhaochen Su, Jun Zhang, Tong Zhu, et al.*2024 · 19 citations*](https://md.research.elamur.ai/free/en/papers/su-2024-timo-towards-better-temporal-reasoning/)
40. **[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*
41. [**Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs arXiv:2507.09477**Yangning Li, Weizhi Zhang, Yuyao Yang, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-towards-agentic-rag-deep-reasoning/)
42. [**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/)
43. **[FoE: Forest of Errors Makes the First Solution the Best in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/jiang-2026-foe-forest-errors-makes-first/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kehan Jiang, Haonan Dong, Zhaolu Kang, et al.*2026 · 15 citations*
44. [**A Survey on Latent Reasoning arXiv:2507.06203**Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-survey-latent-reasoning/)
45. **[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*
46. [**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/)
47. **[LazyEviction: Lagged KV Eviction with Attention Pattern Observation for Efficient Long Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2026-lazyeviction-lagged-kv-eviction-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoyue Zhang, Hualei Zhang, Xiaosong Ma, et al.*2026 · 8 citations*
48. **[Enhancing the Reasoning Capabilities of Small Language Models via Solution Guidance Fine-Tuning](https://md.research.elamur.ai/free/en/papers/bi-2025-enhancing-reasoning-capabilities-small-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jing Bi, Yuting Wu, Weiwei Xing, et al.*2025 · 8 citations*
49. **[Efficient Reasoning for LLMs through Speculative Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/wang-2026-efficient-reasoning-llms-through-speculative/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jikai Wang, Juntao Li, Jianye Hou, et al.*2026 · 6 citations*
50. **[Beyond “I Don't Know”: Evaluating LLM Self-Awareness in Discriminating Data and Model Uncertainty](https://md.research.elamur.ai/free/en/papers/ren-2026-beyond-i-don-t-know/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyi Ren, Ante Wang, Yunghwei Lai, et al.*2026 · 3 citations*
51. **[Scaling Laws for Code: A More Data-Hungry Regime](https://md.research.elamur.ai/free/en/papers/luo-2026-scaling-laws-code-more-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xianzhen Luo, Wenzhen Zheng, Qingfu Zhu, et al.*2026 · 3 citations*
52. **[Can We Predict Before Executing Machine Learning Agents?](https://md.research.elamur.ai/free/en/papers/zheng-2026-can-we-predict-before-executing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingsheng Zheng, Jintian Zhang, Yujie Luo, et al.*2026 · 2 citations*
53. **[MR-ALIGN: Meta-Reasoning Informed Factuality Alignment for Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/wang-2026-mr-align-meta-reasoning-informed/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinming Wang, Jian Xu, Bin Yu, et al.*2026 · 2 citations*
54. **[The Riddle of Reflection: Evaluating Reasoning and Self-Awareness in Multilingual LLMs Using Indian Riddles](https://md.research.elamur.ai/free/en/papers/m-2026-riddle-reflection-evaluating-reasoning-self/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Abhinav P M, Ojasva Saxena, Oswald C, et al.*2026 · 2 citations*
55. **[Conversational Assistants to Support Patients with Heart Failure: Comparing a Neurosymbolic Architecture with GPT](https://md.research.elamur.ai/free/en/papers/tayal-2026-conversational-assistants-support-patients-heart/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Anuja Tayal, Devika Salunke, Barbara Di Eugenio, et al.*2026 · 1 citation*
56. **[Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers](https://md.research.elamur.ai/free/en/papers/yang-2026-mid-think-training-free-intermediate/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Van Yang, Shouren Wang, Debargha Ganguly, et al.*2026 · 1 citation*
57. **[Not All Tokens Matter: Towards Efficient LLM Reasoning via Token Significance in Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/liu-2026-not-all-tokens-matter-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanbing Liu, Lang Cao, Yuanyi Ren, et al.*2026 · 1 citation*
58. **[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*
59. **[The Thin Line Between Comprehension and Persuasion in LLMs](https://md.research.elamur.ai/free/en/papers/wynter-2026-thin-line-between-comprehension-persuasion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adrian de Wynter, Tangming Yuan*2026 · 1 citation*
60. **[Vision-Language Introspection: Mitigating Overconfident Hallucinations in MLLMs via Interpretable Bi-Causal Steering](https://md.research.elamur.ai/free/en/papers/liu-2026-vision-language-introspection-mitigating-overconfident/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuliang Liu, Songbo Yang, Dong Fang, et al.*2026 · 1 citation*
61. **[Bayesian Social Deduction with Graph-Informed Language Models](https://md.research.elamur.ai/free/en/papers/rahimirad-2026-bayesian-social-deduction-graph-informed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shahab Rahimirad, Guven Gergerli, Lucia Romero, et al.*2026*
62. **[Concise Math Reasoning via Difficulty-Aware Distillation](https://md.research.elamur.ai/free/en/papers/wu-2026-concise-math-reasoning-difficulty-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yifan Wu, Jingze Shi, Bingheng Wu, et al.*2026*
63. **[Merlin's Whisper: Enabling Efficient Reasoning in Large Language Models via Black-box Persuasive Prompting](https://md.research.elamur.ai/free/en/papers/xia-2026-merlin-s-whisper-enabling-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Heming Xia, Cunxiao Du, Rui Li, et al.*2026*
64. **[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*
65. **[PACE: Predictive Adaptive Context Extraction for Long-Horizon LLM Agents](https://md.research.elamur.ai/free/en/papers/wei-2026-pace-predictive-adaptive-context-extraction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Wei, Xiao Peng, Tt, et al.*2026*
66. **[Pru-CoT: Towards Efficient Reasoning Distillation via Pruning Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/liu-2026-pru-cot-efficient-reasoning-distillation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Han Liu, Shuotian Ma, Hui Li, et al.*2026*
67. **[Thought-Action Graph Reasoning: Faithful and Efficient Reasoning of Large Language Models via Reusing Past Experience](https://md.research.elamur.ai/free/en/papers/qi-2026-thought-action-graph-reasoning-faithful/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhixiao Qi, Feng Huang, Yunqi Zhang, et al.*2026*
68. **[WebUncertainty: Dual-Level Uncertainty Driven Planning and Reasoning For Autonomous Web Agent](https://md.research.elamur.ai/free/en/papers/zhang-2026-webuncertainty-dual-level-uncertainty-driven/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lingfeng Zhang, Yongan Sun, Jinpeng Hu, et al.*2026*
69. **[ZoomR: Memory Efficient Reasoning through Multi-Granularity Key Value Retrieval](https://md.research.elamur.ai/free/en/papers/yang-2026-zoomr-memory-efficient-reasoning-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**David H. Yang, Yuxuan Zhu, Mohammad Mohammadi Amiri, et al.*2026*

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