---
title: "Who cites Andrea Zanette — 185 papers of our library"
description: "185 papers of the Elamur Research library cite the works of Andrea Zanette, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/andrea-zanette/cited-by/"
---
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# Who cites Andrea Zanette

194 citations of their works from 185 papers of our library (of the 149,439 whose bibliographies we read) · 85 with a page here, the most cited first · [← Andrea Zanette](https://md.research.elamur.ai/free/en/authors/andrea-zanette/)

1. [**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/)
2. **[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*
3. [**SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training arXiv:2501.17161**Tianzhe Chu, Yuexiang Zhai, Jihan Yang, et al.*2025 · 160 citations*](https://md.research.elamur.ai/free/en/papers/chu-2025-sft-memorizes-rl-generalizes-comparative/)
4. [**Training Language Models to Self-Correct via Reinforcement Learning arXiv:2409.12917**Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2024-training-language-models-self-correct/)
5. [**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/)
6. [**L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning arXiv:2503.04697**Pranjal Aggarwal, Sean Welleck*2025 · 125 citations*](https://md.research.elamur.ai/free/en/papers/aggarwal-2025-l1-controlling-long-reasoning-model/)
7. [**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/)
8. **[A Survey of Reinforcement Learning from Human Feedback](https://md.research.elamur.ai/free/en/papers/kaufmann-2023-survey-reinforcement-learning-human-feedback/) [Transactions on Machine Learning Research](https://md.research.elamur.ai/free/en/venues/transactions-on-machine-learning-research/)**Timo Kaufmann, Paul Weng, Viktor Bengs, et al.*2023 · 92 citations*
9. **[Recursive Introspection: Teaching Language Model Agents How to Self-Improve](https://md.research.elamur.ai/free/en/papers/qu-2024-recursive-introspection-teaching-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxiao Qu, Tianjun Zhang, Naman Garg, et al.*2024 · 75 citations*
10. [**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/)
11. [**RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning arXiv:2504.20073**Zihan Wang, Kangrui Wang, Qineng Wang, et al.*2025 · 71 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-ragen-understanding-self-evolution-llm/)
12. **[Group-in-Group Policy Optimization for LLM Agent Training](https://md.research.elamur.ai/free/en/papers/feng-2025-group-group-policy-optimization-llm/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lang Feng, Zhenghai Xue, Tingcong Liu, et al.*2025 · 69 citations*
13. [**Kevin: Multi-Turn RL for Generating CUDA Kernels arXiv 2025**Carlo Baronio, Pietro Marsella, Ben Pan, et al.*2025 · 69 citations*](https://md.research.elamur.ai/free/en/papers/baronio-2025-kevin-multi-turn-rl-generating/)
14. [**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/)
15. [**Thoughts Are All Over the Place: On the Underthinking of o1-Like LLMs arXiv:2501.18585**Yue Wang; Qiuzhi Liu; Jiahao Xu; Tian Liang; Xingyu Chen; Zhiwei He; Linfeng Song; Dian Yu; Juntao Li; Zhuosheng Zhang; Rui Wang; Zhaopeng Tu; Haitao Mi;, Dong Yu*2025 · 60 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-thoughts-all-over-place-underthinking/)
16. [**Reasoning Models Can Be Effective Without Thinking arXiv:2504.09858**Wenjie Ma, Jingxuan He, Charlie Snell, et al.*2025 · 58 citations*](https://md.research.elamur.ai/free/en/papers/ma-2025-reasoning-models-effective-thinking/)
17. [**DAST: Difficulty-Adaptive Slow-Thinking for Large Reasoning Models arXiv:2503.04472**Yi Shen, Jian Zhang, Jieyun Huang, et al.*2025 · 57 citations*](https://md.research.elamur.ai/free/en/papers/shen-2025-dast-difficulty-adaptive-slow-thinking/)
18. [**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/)
19. [**Spurious Rewards: Rethinking Training Signals in RLVR arXiv:2506.10947**Rulin Shao, Shuyue Stella Li, Rui Xin, et al.*2025 · 53 citations*](https://md.research.elamur.ai/free/en/papers/shao-2025-spurious-rewards-rethinking-training-signals/)
20. **[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*
21. [**RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning arXiv:2410.02089**Jonas Gehring, Kunhao Zheng, Jade Copet, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/gehring-2024-rlef-grounding-code-llms-execution/)
22. **[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*
23. [**Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-Thought arXiv:2501.04682**Violet Xiang, Charlie Snell, Kanishk Gandhi, et al.*2025 · 47 citations*](https://md.research.elamur.ai/free/en/papers/xiang-2025-towards-system-2-reasoning-llms/)
24. **[AdaptThink: Reasoning Models Can Learn When to Think](https://md.research.elamur.ai/free/en/papers/zhang-2025-adaptthink-reasoning-models-can-learn/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiajie Zhang, Nianyi Lin, Lei Hou, et al.*2025 · 44 citations*
25. [**Learning to Reason without External Rewards arXiv:2505.19590**Xuandong Zhao, Zhewei Kang, Aosong Feng, et al.*2025 · 44 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2025-learning-reason-external-rewards/)
26. **[Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?](https://md.research.elamur.ai/free/en/papers/zeng-2025-revisiting-test-time-scaling-o1/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.*2025 · 38 citations*
27. [**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/)
28. [**A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence arXiv:2507.21046**Huan-ang Gao, Jiayi Geng, Wenyue Hua, et al.*2025 · 36 citations*](https://md.research.elamur.ai/free/en/papers/gao-2025-survey-self-evolving-agents-where/)
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. [**AgentGym: Evolving Large Language Model-based Agents across Diverse Environments arXiv:2406.04151**Zhiheng Xi, Yiwen Ding, Wenxiang Chen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/xi-2024-agentgym-evolving-large-language-model/)
31. [**Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective arXiv:2412.14135**Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-scaling-search-learning-roadmap-reproduce/)
32. [**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/)
33. [**Scaling Test-Time Compute Without Verification or RL is Suboptimal arXiv:2502.12118**Amrith Setlur, Nived Rajaraman, Sergey Levine, et al.*2025 · 26 citations*](https://md.research.elamur.ai/free/en/papers/setlur-2025-scaling-test-time-compute-verification/)
34. **[StepTool: Enhancing Multi-Step Tool Usage in LLMs via Step-Grained Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yu-2024-steptool-enhancing-multi-step-tool/) [ACM International Conference on Information and Knowledge Management (CIKM)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-information-and-knowledge-management-cikm/)**Yuanqing Yu, Zhefan Wang, Weizhi Ma, et al.*2024 · 20 citations*
35. **[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*
36. **[AttnPO: Attention-Guided Process Supervision for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/nie-2026-attnpo-attention-guided-process-supervision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuaiyi Nie, Dingsiyu, Wenyuan Zhang, et al.*2026 · 18 citations*
37. **[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*
38. [**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/)
39. **[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*
40. [**Outcome-based Exploration for LLM Reasoning arXiv:2509.06941**Yuda Song, Julia Kempe, Remi Munos*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/song-2025-outcome-based-exploration-llm-reasoning/)
41. **[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*
42. **[Dynamic Parallel Tree Search for Efficient LLM Reasoning](https://md.research.elamur.ai/free/en/papers/ding-2025-dynamic-parallel-tree-search-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifu Ding, Wentao Jiang, Shunyu Liu, et al.*2025 · 13 citations*
43. [**Pangu Embedded: An Efficient Dual-system LLM Reasoner with Metacognition arXiv:2505.22375**Hanting Chen, Yasheng Wang, Kai Han, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-pangu-embedded-efficient-dual/)
44. **[VisuoThink: Empowering LVLM Reasoning with Multimodal Tree Search](https://md.research.elamur.ai/free/en/papers/wang-2025-visuothink-empowering-lvlm-reasoning-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yikun Wang, Siyin Wang, Qinyuan Cheng, et al.*2025 · 13 citations*
45. **[Optimizing Length Compression in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/cheng-2026-optimizing-length-compression-large-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxiang Cheng, Dongping Chen, Mingyang Fu, et al.*2026 · 11 citations*
46. **[AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time](https://md.research.elamur.ai/free/en/papers/zhang-2025-alphaone-reasoning-models-thinking-slow/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junyu Zhang, Runpei Dong, Han Wang, et al.*2025 · 10 citations*
47. **[Reinforced Efficient Reasoning via Semantically Diverse Exploration](https://md.research.elamur.ai/free/en/papers/zhao-2026-reinforced-efficient-reasoning-semantically-diverse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziqi Zhao, Zhaochun Ren, Jiahong Zou, et al.*2026 · 9 citations*
48. [**100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language Models arXiv:2505.00551**Chong Zhang, Yue Deng, Xiang Lin, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-100-days-after-deepseek/)
49. **[Problem Solving Through Human–AI Preference-based Cooperation](https://md.research.elamur.ai/free/en/papers/dutta-2025-problem-solving-through-human-ai/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Subhabrata Dutta, Timo Kaufmann, Goran Glavaš, et al.*2025 · 9 citations*
50. [**Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering arXiv:2411.11504**Xinyan Guan, Yanjiang Liu, Xinyu Lu, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/guan-2024-search-verify-feedback-towards-next/)
51. [**PAG: Multi-Turn Reinforced LLM Self-Correction with Policy as Generative Verifier arXiv:2506.10406**Yuhua Jiang, Yuwen Xiong, Yufeng Yuan, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2025-pag-multi-turn-reinforced-llm/)
52. **[Android Coach: Improve Online Agentic Training Efficiency with Single State Multiple Actions](https://md.research.elamur.ai/free/en/papers/gan-2026-android-coach-improve-online-agentic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guo Gan, Yuxuan Ding, Cong Chen, et al.*2026 · 7 citations*
53. **[Revisiting Model Interpolation for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-revisiting-model-interpolation-efficient-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taiqiang Wu, Runming Yang, Tao Liu, et al.*2026 · 6 citations*
54. **[When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMs](https://md.research.elamur.ai/free/en/papers/khairi-2025-when-life-gives-you-samples/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ammar Khairi, Daniel D'souza, Ye Shen, et al.*2025 · 6 citations*
55. **[Do LLMs Really Need 10+ Thoughts for “Find the Time 1000 Days Later”? Towards Structural Understanding of LLM Overthinking](https://md.research.elamur.ai/free/en/papers/zhang-2026-do-llms-really-need-10/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinliang Frederick Zhang, Anhad Mohananey, Alexandra Chronopoulou, et al.*2026 · 4 citations*
56. **[Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities](https://md.research.elamur.ai/free/en/papers/oh-2026-uncertainty-quantification-llm-agents-foundations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Changdae Oh, Seongheon Park, To Eun Kim, et al.*2026 · 4 citations*
57. **[DeepPrune: Parallel Scaling without Inter-trace Redundancy](https://md.research.elamur.ai/free/en/papers/tu-2026-deepprune-parallel-scaling-without-inter/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shangqing Tu, Yaxuan Li, Yushi Bai, et al.*2026 · 3 citations*
58. **[REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at Once](https://md.research.elamur.ai/free/en/papers/pan-2026-rest-stress-testing-large-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhuoshi Pan, Qizhi Pei, Yu Li, et al.*2026 · 3 citations*
59. **[SAT: Balancing Reasoning Accuracy and Efficiency with Stepwise Adaptive Thinking](https://md.research.elamur.ai/free/en/papers/huang-2026-sat-balancing-reasoning-accuracy-efficiency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weiyang Huang, Xuefeng Bai, Kehai Chen, et al.*2026 · 3 citations*
60. **[TROJail: Trajectory-Level Optimization for Multi-Turn Large Language Model Jailbreaks with Process Rewards](https://md.research.elamur.ai/free/en/papers/xiong-2026-trojail-trajectory-level-optimization-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiqiao Xiong, Ouxiang Li, Zhuo Liu, et al.*2026 · 3 citations*
61. **[Beyond Token Length: Step Pruner for Efficient and Accurate Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-token-length-step-pruner/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Canhui Wu, Qiong Cao, Chang Li, et al.*2026 · 2 citations*
62. **[Foresight Optimization for Strategic Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-foresight-optimization-strategic-reasoning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jessie Wang, Jiawen Duan, Jian Wang, et al.*2026 · 2 citations*
63. **[Think How to Think: Mitigating Overthinking with Autonomous Difficulty Cognition in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/liu-2026-think-how-think-mitigating-overthinking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongjiang Liu, Haoxi Li, Xiaosong Ma, et al.*2026 · 2 citations*
64. **[What If Consensus Lies? Selective-Complementary Reinforcement Learning at Test Time](https://md.research.elamur.ai/free/en/papers/yan-2026-what-if-consensus-lies-selective/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dong Yan, Jian Liang, Yanbo Wang, et al.*2026 · 2 citations*
65. **[A Survey on LLM-based Conversational User Simulation](https://md.research.elamur.ai/free/en/papers/ni-2026-survey-llm-based-conversational-user/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bo Ni, Yu Wang, Leyao Wang, et al.*2026 · 1 citation*
66. **[CoAct: Co-Active LLM Preference Learning with Human-AI Synergy](https://md.research.elamur.ai/free/en/papers/xu-2026-coact-co-active-llm-preference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruiyao Xu, Mihir Parmar, Tiankai Yang, et al.*2026 · 1 citation*
67. **[Confidence-Calibrated Small-Large Language Model Collaboration for Cost-Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/zhang-2026-confidence-calibrated-small-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Chuang Zhang, Zizhen Zhu, Yihao Wei, et al.*2026 · 1 citation*
68. **[Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yu-2026-easy-samples-are-all-you/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiyin Yu, Bo Zhang, Qibin Hou, et al.*2026 · 1 citation*
69. **[Graph-Based Chain-of-Thought Pruning for Reducing Redundant Reflections in Reasoning LLMs](https://md.research.elamur.ai/free/en/papers/yuan-2026-graph-based-chain-thought-pruning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hongyuan Yuan, Xinran He, Run Shao, et al.*2026 · 1 citation*
70. **[Listen, Pause, and Reason: Toward Perception-Grounded Hybrid Reasoning for Audio Understanding](https://md.research.elamur.ai/free/en/papers/wang-2026-listen-pause-reason-perception-grounded/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jieyi Wang, Yazhe Niu, Dexuan Xu, et al.*2026 · 1 citation*
71. **[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*
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