---
title: "Who cites Zitong Yang — 550 papers of our library"
description: "550 papers of the Elamur Research library cite the works of Zitong Yang, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Zitong Yang

550 citations of their works from 550 papers of our library (of the 149,439 whose bibliographies we read) · 170 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Zitong Yang](https://md.research.elamur.ai/free/en/authors/zitong-yang/)

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1. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency arXiv:2508.18265**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
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. [**From System 1 to System 2: A Survey of Reasoning Large Language Models arXiv:2502.17419**Zhong-Zhi Li, Duzhen Zhang, Ming-Liang Zhang, et al.*2025 · 165 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-system-1-system-2-survey/)
4. [**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/)
5. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs arXiv:2503.01743**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 152 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
6. [**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/)
7. [**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/)
8. [**OpenThoughts: Data Recipes for Reasoning Models arXiv:2506.04178**Etash Guha, Ryan Marten, Sedrick Keh, et al.*2025 · 122 citations*](https://md.research.elamur.ai/free/en/papers/guha-2025-openthoughts-data-recipes-reasoning-models/)
9. **[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*
10. **[ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/chen-2025-research-learning-reason-search-llms/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Mingyang Chen, Linzhuang Sun, Tianpeng Li, et al.*2025 · 99 citations*
11. [**Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models arXiv:2601.18734**Siyan Zhao, Zhihui Xie, Mengchen Liu, et al.*2026 · 97 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2026-self-distilled-reasoner-policy-self/)
12. [**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/)
13. [**Dream 7B: Diffusion Large Language Models arXiv:2508.15487**Jiacheng Ye; Zhihui Xie; Lin Zheng; Jiahui Gao; Zirui Wu; Xin Jiang; Zhenguo Li;, Lingpeng Kong*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-dream-7b-diffusion-large-language/)
14. [**ReTool: Reinforcement Learning for Strategic Tool Use in LLMs arXiv:2504.11536**Jiazhan Feng, Shijue Huang, Xingwei Qu, et al.*2025 · 88 citations*](https://md.research.elamur.ai/free/en/papers/feng-2025-retool-reinforcement-learning-strategic-tool/)
15. **[Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and Beyond](https://md.research.elamur.ai/free/en/papers/wen-2025-light-r1-curriculum-sft-dpo/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liang Wen, Yunke Cai, Fenrui Xiao, et al.*2025 · 84 citations*
16. **[AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning](https://md.research.elamur.ai/free/en/papers/fu-2025-areal-large-scale-asynchronous-reinforcement/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wei Fu, Jiaxuan Gao, Xujie Shen, et al.*2025 · 80 citations*
17. [**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/)
18. [**Llama-Nemotron: Efficient Reasoning Models arXiv:2505.00949**Akhiad Bercovich, Itay Levy, Izik Golan, et al.*2025 · 76 citations*](https://md.research.elamur.ai/free/en/papers/bercovich-2025-llama-nemotron-efficient-reasoning-models/)
19. [**Reinforcement Learning via Self-Distillation arXiv:2601.20802**Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.*2026 · 74 citations*](https://md.research.elamur.ai/free/en/papers/hubotter-2026-reinforcement-learning-self-distillation/)
20. [**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/)
21. **[Apertus: Democratizing Open and Compliant LLMs for Global Language Environments](https://md.research.elamur.ai/free/en/papers/cano-2026-apertus-democratizing-open-compliant-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.*2026 · 68 citations*
22. **[Learning to Reason under Off-Policy Guidance](https://md.research.elamur.ai/free/en/papers/yan-2025-learning-reason-under-off-policy/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jianhao Yan, Yafu Li, Zican Hu, et al.*2025 · 68 citations*
23. [**ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning arXiv:2504.01296**Bairu Hou, Yang Zhang, Jiabao Ji, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/hou-2025-thinkprune-pruning-long-chain-thought/)
24. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
25. [**Deep Think with Confidence arXiv:2508.15260**Yichao Fu, Xuewei Wang, Yuandong Tian, et al.*2025 · 61 citations*](https://md.research.elamur.ai/free/en/papers/fu-2025-deep-think-confidence/)
26. [**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/)
27. **[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*
28. **[General-Reasoner: Advancing LLM Reasoning Across All Domains](https://md.research.elamur.ai/free/en/papers/ma-2025-general-reasoner-advancing-llm-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xueguang Ma, Qian Liu, Dongfu Jiang, et al.*2025 · 43 citations*
29. **[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*
30. [**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/)
31. [**OpenCodeReasoning: Advancing Data Distillation for Competitive Coding arXiv:2504.01943**Wasi Uddin Ahmad, Sean Narenthiran, Somshubra Majumdar, et al.*2025 · 33 citations*](https://md.research.elamur.ai/free/en/papers/ahmad-2025-opencodereasoning-advancing-data-distillation-competitive/)
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. **[Audio-Reasoner: Improving Reasoning Capability in Large Audio Language Models](https://md.research.elamur.ai/free/en/papers/zhifei-2025-audio-reasoner-improving-reasoning-capability/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xie Zhifei, Mingbao Lin, Zihang Liu, et al.*2025 · 25 citations*
34. **[Linguistic Generalizability of Test-Time Scaling in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/son-2025-linguistic-generalizability-test-time-scaling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guijin Son, Jiwoo Hong, Hyunwoo Ko, et al.*2025 · 24 citations*
35. **[Online Difficulty Filtering for Reasoning Oriented Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/bae-2026-online-difficulty-filtering-reasoning-oriented/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sanghwan Bae, Jiwoo Hong, Min Young Lee, et al.*2026 · 22 citations*
36. [**AceReason-Nemotron 1.1: Advancing Math and Code Reasoning through SFT and RL Synergy arXiv:2506.13284**Zihan Liu, Zhuolin Yang, Yang Chen, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-acereason-nemotron-1-1-advancing/)
37. [**DRP: Distilled Reasoning Pruning with Skill-aware Step Decomposition for Efficient Large Reasoning Models arXiv:2505.13975**Yuxuan Jiang, Dawei Li, Francis Ferraro*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2025-drp-distilled-reasoning-pruning-skill/)
38. **[START: Self-taught Reasoner with Tools](https://md.research.elamur.ai/free/en/papers/li-2025-start-self-taught-reasoner-tools/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chengpeng Li, Mingfeng Xue, Zhenru Zhang, et al.*2025 · 21 citations*
39. **[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*
40. **[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*
41. [**Hunyuan-MT Technical Report arXiv:2509.05209**Mao Zheng, Zheng Li, Bingxin Qu, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2025-hunyuan-mt-technical-report/)
42. [**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/)
43. [**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/)
44. **[Inner Thinking Transformer: Leveraging Dynamic Depth Scaling to Foster Adaptive Internal Thinking](https://md.research.elamur.ai/free/en/papers/chen-2025-inner-thinking-transformer-leveraging-dynamic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilong Chen, Junyuan Shang, Zhenyu Zhang, et al.*2025 · 16 citations*
45. **[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*
46. **[METAL: A Multi-Agent Framework for Chart Generation with Test-Time Scaling](https://md.research.elamur.ai/free/en/papers/li-2025-metal-multi-agent-framework-chart/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bingxuan Li, Yiwei Wang, Jiuxiang Gu, et al.*2025 · 15 citations*
47. [**Rethinking Reflection in Pre-Training arXiv:2504.04022**Essential AI: Darsh J Shah, Peter Rushton, Somanshu Singla, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shah-2025-rethinking-reflection-pre-training/)
48. [**Long-Short Chain-of-Thought Mixture Supervised Fine-Tuning Eliciting Efficient Reasoning in Large Language Models arXiv:2505.03469**Bin Yu, Hang Yuan, Haotian Li, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/yu-2025-long-short-chain-thought-mixture/)
49. [**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/)
50. [**QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning arXiv:2505.17667**Fanqi Wan, Weizhou Shen, Shengyi Liao, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/wan-2025-qwenlong-l1-long-context/)
51. **[CriticLean: Critic-Guided Reinforcement Learning for Mathematical Formalization](https://md.research.elamur.ai/free/en/papers/peng-2026-criticlean-critic-guided-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhongyuan Peng, Yifan Yao, Kaijing Ma, et al.*2026 · 12 citations*
52. **[Scaling Reasoning, Losing Control: Evaluating Instruction Following in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/fu-2026-scaling-reasoning-losing-control-evaluating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tingchen Fu, Yafu Li, Jiawei Gu, et al.*2026 · 12 citations*
53. **[Please Translate Again: Two Simple Experiments on Whether Human-Like Reasoning Helps Translation](https://md.research.elamur.ai/free/en/papers/wu-2025-please-translate-again-two-simple/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Di Wu, Seth Aycock, Christof Monz*2025 · 12 citations*
54. **[Is That Your Final Answer? Test-Time Scaling Improves Selective Question Answering](https://md.research.elamur.ai/free/en/papers/jurayj-2025-is-that-your-final-answer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**William Jurayj, Jeffrey Cheng, Benjamin Van Durme*2025 · 11 citations*
55. **[ReasonMed: A 370K Multi-Agent Generated Dataset for Advancing Medical Reasoning](https://md.research.elamur.ai/free/en/papers/sun-2025-reasonmed-370k-multi-agent-generated/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yu Sun, Xingyu Qian, Weiwen Xu, et al.*2025 · 11 citations*
56. **[What Makes a Good Reasoning Chain? Uncovering Structural Patterns in Long Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/jiang-2025-what-makes-good-reasoning-chain/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gangwei Jiang, Yahui Liu, Zhaoyi Li, et al.*2025 · 11 citations*
57. **[The Sparse Frontier: Sparse Attention Trade-offs in Transformer LLMs](https://md.research.elamur.ai/free/en/papers/nawrot-2026-sparse-frontier-sparse-attention-trade/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Piotr Nawrot, Jianing Li, Renjie Huang, et al.*2026 · 10 citations*
58. **[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*
59. **[AnyMAC: Cascading Flexible Multi-Agent Collaboration via Next-Agent Prediction](https://md.research.elamur.ai/free/en/papers/wang-2025-anymac-cascading-flexible-multi-agent/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Song Wang, Zhen Tan, Zihan Chen, et al.*2025 · 10 citations*
60. [**Could Thinking Multilingually Empower LLM Reasoning? arXiv:2504.11833**Changjiang Gao, Xu Huang, Wenhao Zhu, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/gao-2025-could-thinking-multilingually-empower-llm/)
61. **[MOLE: Metadata Extraction and Validation in Scientific Papers Using LLMs](https://md.research.elamur.ai/free/en/papers/alyafeai-2025-mole-metadata-extraction-validation-scientific/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zaid Alyafeai, Maged S. Al-shaibani, Bernard Ghanem*2025 · 10 citations*
62. **[RoT: Enhancing Table Reasoning with Iterative Row-Wise Traversals](https://md.research.elamur.ai/free/en/papers/zhang-2025-rot-enhancing-table-reasoning-iterative/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xuanliang Zhang, Dingzirui Wang, Keyan Xu, et al.*2025 · 10 citations*
63. **[Knowing When to Abstain: Medical LLMs Under Clinical Uncertainty](https://md.research.elamur.ai/free/en/papers/machcha-2026-knowing-when-abstain-medical-llms/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sravanthi Machcha, Sushrita Yerra, Sahil Gupta, et al.*2026 · 9 citations*
64. **[Nemotron-CrossThink: Scaling Self-Learning beyond Math Reasoning](https://md.research.elamur.ai/free/en/papers/akter-2026-nemotron-crossthink-scaling-self-learning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Syeda Nahida Akter, Shrimai Prabhumoye, Matvei Novikov, et al.*2026 · 9 citations*
65. [**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/)
66. [**Guiding Reasoning in Small Language Models with LLM Assistance arXiv:2504.09923**Yujin Kim, Euiin Yi, Minu Kim, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/kim-2025-guiding-reasoning-small-language-models/)
67. **[Theorem Prover as a Judge for Synthetic Data Generation](https://md.research.elamur.ai/free/en/papers/leang-2025-theorem-prover-as-judge-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joshua Ong Jun Leang, Giwon Hong, Wenda Li, et al.*2025 · 9 citations*
68. [**TL;DR: Too Long, Do Re-weighting for Efficient LLM Reasoning Compression arXiv:2506.02678**Zhong-Zhi Li, Xiao Liang, Zihao Tang, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-tl-dr-too-long-re/)
69. **[A Comprehensive Evaluation of Multilingual Chain-of-Thought Reasoning: Performance, Consistency, and Faithfulness Across Languages](https://md.research.elamur.ai/free/en/papers/zhao-2026-comprehensive-evaluation-multilingual-chain-thought/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Raoyuan Zhao, Yihong Liu, Hinrich Schuetze, et al.*2026 · 7 citations*
70. **[AutoL2S: Auto Long-Short Reasoning for Efficient Large Language Models](https://md.research.elamur.ai/free/en/papers/luo-2026-autol2s-auto-long-short-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Feng Luo, Yu-Neng Chuang, Guanchu Wang, et al.*2026 · 7 citations*
71. **[Scaling Collaborative Effort with Agents](https://md.research.elamur.ai/free/en/papers/shen-2026-scaling-collaborative-effort-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shannon Zejiang Shen, Valerie Chen, Ken Gu, et al.*2026 · 7 citations*
72. **[Stop When Enough: Adaptive Early-Stopping for Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/sun-2026-stop-when-enough-adaptive-early/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Renliang Sun, Wei Cheng, Dawei Li, et al.*2026 · 7 citations*
73. [**Pushing on Multilingual Reasoning Models with Language-Mixed Chain-of-Thought arXiv:2510.04230**Guijin Son, Donghun Yang, Hitesh Laxmichand Patel, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/son-2025-pushing-multilingual-reasoning-models-language/)
74. **[Through the Valley: Path to Effective Long CoT Training for Small Language Models](https://md.research.elamur.ai/free/en/papers/luo-2025-through-valley-path-effective-long/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Renjie Luo, Jiaxi Li, Chen Huang, et al.*2025 · 7 citations*
75. [**TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation arXiv:2503.04872**Lin Sun, Guangxiang Zhao, Xiaoqi Jian, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/sun-2025-tinyr1-32b-preview-boosting-accuracy/)
76. **[Dissecting Failure Dynamics in Large Language Model Reasoning](https://md.research.elamur.ai/free/en/papers/zhu-2026-dissecting-failure-dynamics-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Zhu, Jian Zhang, Lixing Yu, et al.*2026 · 6 citations*
77. **[The Evolution of Thought: Tracking LLM Overthinking via Reasoning Dynamics Analysis](https://md.research.elamur.ai/free/en/papers/wei-2026-evolution-thought-tracking-llm-overthinking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zihao Wei, Liang Pang, Jiahao Liu, et al.*2026 · 6 citations*
78. **[FineReason: Evaluating and Improving LLMs' Deliberate Reasoning through Reflective Puzzle Solving](https://md.research.elamur.ai/free/en/papers/chen-2025-finereason-evaluating-improving-llms-deliberate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guizhen Chen, Weiwen Xu, Hao Zhang, et al.*2025 · 6 citations*
79. **[Understanding the Thinking Process of Reasoning Models: A Perspective from Schoenfeld's Episode Theory](https://md.research.elamur.ai/free/en/papers/li-2025-understanding-thinking-process-reasoning-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ming Li, Nan Zhang, Chenrui Fan, et al.*2025 · 6 citations*
80. **[PaCoRe: Learning to Scale Test-Time Compute with Parallel Coordinated Reasoning](https://md.research.elamur.ai/free/en/papers/hu-2026-pacore-learning-scale-test-time/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingcheng Hu, Yinmin Zhang, Shijie Shang, et al.*2026 · 5 citations*
81. **[Test-Time Scaling of Reasoning Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/li-2026-test-time-scaling-reasoning-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zihao Li, Shaoxiong Ji, Jörg Tiedemann*2026 · 5 citations*
82. **[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*
83. **[Dynamic Sampling that Adapts: Self-Aware Iterative Data Persistent Optimization for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/rao-2026-dynamic-sampling-that-adapts-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jun Rao, Xuebo Liu, Hexuan Deng, et al.*2026 · 4 citations*
84. [**ExpLang: Improved Exploration and Exploitation in LLM Reasoning with On-Policy Thinking Language Selection arXiv:2602.21887**Changjiang Gao, Zixian Huang, Kaichen Yang, et al.*2026 · 4 citations*](https://md.research.elamur.ai/free/en/papers/gao-2026-explang-improved-exploration-exploitation-llm/)
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86. **[Select2Reason: Efficient Instruction-Tuning Data Selection for Long-CoT Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2026-select2reason-efficient-instruction-tuning-data/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cehao Yang, Xueyuan Lin, Xiaojun Wu, et al.*2026 · 4 citations*
87. **[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*
88. **[Which Reasoning Trajectories Teach Students to Reason Better? A Simple Metric of Informative Alignment](https://md.research.elamur.ai/free/en/papers/yang-2026-which-reasoning-trajectories-teach-students/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuming Yang, Mingyoung Lai, Wanxu Zhao, et al.*2026 · 4 citations*
89. [**Read Your Own Mind: Reasoning Helps Surface Self-Confidence Signals in LLMs arXiv:2505.23845 · UncertaiNLP Workshop at Empirical Methods in Natural Language Processing 2025 (EMNLP 2025)**Jakub Podolak, Rajeev Verma*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/podolak-2025-read-own-mind-reasoning-helps/)
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91. **[Controllable LLM Reasoning via Sparse Autoencoder-Based Steering](https://md.research.elamur.ai/free/en/papers/fang-2026-controllable-llm-reasoning-sparse-autoencoder/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Fang, Wenjie Wang, Mingfeng Xue, et al.*2026 · 3 citations*
92. **[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*
93. **[dLLM: Simple Diffusion Language Modeling](https://md.research.elamur.ai/free/en/papers/zhou-2026-dllm-simple-diffusion-language-modeling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhanhui Zhou, Lingjie Chen, Hanghang Tong, et al.*2026 · 3 citations*
94. **[Harnessing Negative Signals: Reinforcement Distillation from Teacher Data for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2026-harnessing-negative-signals-reinforcement-distillation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuyao Xu, Cheng Peng, Jiangxuan Long, et al.*2026 · 3 citations*
95. **[Long-Chain Reasoning Distillation via Adaptive Prefix Alignment](https://md.research.elamur.ai/free/en/papers/liu-2026-long-chain-reasoning-distillation-adaptive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenghao Liu, Zhuoyang Wu, Xinze Li, et al.*2026 · 3 citations*
96. **[MathAgent: Adversarial Evolution of Constraint Graphs for Mathematical Reasoning Data Synthesis](https://md.research.elamur.ai/free/en/papers/yu-2026-mathagent-adversarial-evolution-constraint-graphs/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zixiong Yu, Jun Rao, Guhan Chen, et al.*2026 · 3 citations*
97. **[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*
98. [**Large Means Left: Political Bias in Large Language Models Increases with Their Number of Parameters arXiv:2505.04393**David Exler, Mark Schutera, Markus Reischl, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/exler-2025-large-means-left-political-bias/)
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100. **[Adam's Law: Textual Frequency Law on Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2026-adam-s-law-textual-frequency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongyuan Lu, Zixuan Li, Zefan Zhang, et al.*2026 · 2 citations*

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