---
title: "Who cites Jiahao Xu — 315 papers of our library"
description: "315 papers of the Elamur Research library cite the works of Jiahao Xu, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Jiahao Xu

320 citations of their works from 315 papers of our library (of the 149,439 whose bibliographies we read) · 103 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Jiahao Xu](https://md.research.elamur.ai/free/en/authors/jiahao-xu/)

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1. [**Kimi k1.5: Scaling Reinforcement Learning with LLMs arXiv:2501.12599**Kimi Team, Angang Du, Bofei Gao, et al.*2025 · 431 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k1-5-scaling-reinforcement/)
2. [**Understanding R1-Zero-Like Training: A Critical Perspective arXiv:2503.20783**Zichen Liu, Changyu Chen, Wenjun Li, et al.*2025 · 286 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-understanding-r1-zero-like-training/)
3. **[Search-o1: Agentic Search-Enhanced Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/li-2025-search-o1-agentic-search-enhanced/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaoxi Li, Guanting Dong, Jiajie Jin, et al.*2025 · 211 citations*
4. **[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*
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. [**SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild arXiv:2503.18892**Weihao Zeng, Yuzhen Huang, Qian Liu, et al.*2025 · 154 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2025-simplerl-zoo-investigating-taming-zero/)
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. **[The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity](https://md.research.elamur.ai/free/en/papers/shojaee-2025-illusion-thinking-understanding-strengths-limitations/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, et al.*2025 · 104 citations*
10. [**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/)
11. [**Multi-Agent Collaboration Mechanisms: A Survey of LLMs arXiv:2501.06322**Khanh-Tung Tran, Dung Dao, Minh-Duong Nguyen, et al.*2025 · 95 citations*](https://md.research.elamur.ai/free/en/papers/tran-2025-multi-agent-collaboration-mechanisms/)
12. [**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/)
13. [**Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities arXiv:2408.07666**Enneng Yang, Li Shen, Guibing Guo, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-model-merging-llms-mllms-methods/)
14. [**DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing Reasoning arXiv:2504.11456**Zhiwei He, Tian Liang, Jiahao Xu, et al.*2025 · 78 citations*](https://md.research.elamur.ai/free/en/papers/he-2025-deepmath-103k-large-scale-challenging/)
15. [**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/)
16. **[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*
17. [**When More is Less: Understanding Chain-of-Thought Length in LLMs arXiv:2502.07266**Yuyang Wu, Yifei Wang, Ziyu Ye, et al.*2025 · 73 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-more-less-understanding-chain-thought/)
18. [**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/)
19. [**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/)
20. **[CoT-Valve: Length-Compressible Chain-of-Thought Tuning](https://md.research.elamur.ai/free/en/papers/ma-2025-cot-valve-length-compressible-chain/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyin Ma, Guangnian Wan, Runpeng Yu, et al.*2025 · 64 citations*
21. [**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/)
22. [**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/)
23. **[Translating Step-by-Step: Decomposing the Translation Process for Improved Translation Quality of Long-Form Texts](https://md.research.elamur.ai/free/en/papers/briakou-2024-translating-step-step-decomposing-translation/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Eleftheria Briakou, Jiaming Luo, Colin Cherry, et al.*2024 · 46 citations*
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. **[Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2025-towards-thinking-optimal-scaling-test/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wenkai Yang, Shuming Ma, Yankai Lin, et al.*2025 · 43 citations*
26. [**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/)
27. **[Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning?](https://md.research.elamur.ai/free/en/papers/he-2025-can-large-language-models-detect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yancheng He, Shilong Li, Jiaheng Liu, et al.*2025 · 30 citations*
28. **[S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/ma-2025-s-2-r-teaching-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruotian Ma, Peisong Wang, Cheng Liu, et al.*2025 · 26 citations*
29. **[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*
30. [**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/)
31. **[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*
32. **[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*
33. **[Benchmarking LLMs for Translating Classical Chinese Poetry: Evaluating Adequacy, Fluency, and Elegance](https://md.research.elamur.ai/free/en/papers/chen-2025-benchmarking-llms-translating-classical-chinese/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Andong Chen, Lianzhang Lou, Kehai Chen, et al.*2025 · 18 citations*
34. **[LLMs know their vulnerabilities: Uncover Safety Gaps through Natural Distribution Shifts](https://md.research.elamur.ai/free/en/papers/ren-2025-llms-know-their-vulnerabilities-uncover/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qibing Ren, Hao Li, Dongrui Liu, et al.*2025 · 18 citations*
35. [**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/)
36. **[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*
37. **[Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target Atoms](https://md.research.elamur.ai/free/en/papers/wang-2025-beyond-prompt-engineering-robust-behavior/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengru Wang, Ziwen Xu, Shengyu Mao, et al.*2025 · 14 citations*
38. **[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*
39. **[StepHint: Multi-level Stepwise Hints Enhance Reinforcement Learning to Reason](https://md.research.elamur.ai/free/en/papers/zhang-2026-stephint-multi-level-stepwise-hints/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kaiyi Zhang, Ang Lv, Jinpeng Li, et al.*2026 · 13 citations*
40. **[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*
41. **[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*
42. **[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*
43. **[Learning from Diverse Reasoning Paths with Routing and Collaboration](https://md.research.elamur.ai/free/en/papers/lei-2025-learning-diverse-reasoning-paths-routing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhenyu Lei, Zhen Tan, Song Wang, et al.*2025 · 11 citations*
44. [**The Open Proof Corpus: A Large-Scale Study of LLM-Generated Mathematical Proofs arXiv:2506.21621**Jasper Dekoninck, Ivo Petrov, Kristian Minchev, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/dekoninck-2025-open-proof-corpus-large-scale/)
45. **[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*
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. [**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/)
50. **[SafeKey: Amplifying Aha-Moment Insights for Safety Reasoning](https://md.research.elamur.ai/free/en/papers/zhou-2025-safekey-amplifying-aha-moment-insights/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kaiwen Zhou, Xuandong Zhao, Jayanth Srinivasa, et al.*2025 · 9 citations*
51. **[MUR: Momentum Uncertainty guided Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/yan-2026-mur-momentum-uncertainty-guided-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hang Yan, Fangzhi Xu, Rongman Xu, et al.*2026 · 8 citations*
52. **[Marco-o1 v2: Towards Widening The Distillation Bottleneck for Reasoning Models](https://md.research.elamur.ai/free/en/papers/yin-2025-marco-o1-v2-widening/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huifeng Yin, Yu Zhao, Minghao Wu, et al.*2025 · 8 citations*
53. [**ReForm: Reflective Autoformalization with Prospective Bounded Sequence Optimization arXiv:2510.24592**Guoxin Chen, Jing Wu, Xinjie Chen, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-reform-reflective-autoformalization-prospective-bounded/)
54. [**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/)
55. **[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*
56. **[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*
57. **[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*
58. **[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*
59. **[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*
60. **[Mapping the Minds of LLMs: A Graph-Based Analysis of Reasoning LLMs](https://md.research.elamur.ai/free/en/papers/xiong-2025-mapping-minds-llms-graph-based/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Xiong, Yujun Cai, Zhecheng Li, et al.*2025 · 5 citations*
61. [**Ring-lite: Scalable Reasoning via C3PO-Stabilized Reinforcement Learning for LLMs arXiv:2506.14731**Ling Team, Bin Hu, Cai Chen, et al.*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/ling-team-2025-ring-lite-scalable-reasoning/)
62. **[Teach Small Models to Reason by Curriculum Distillation](https://md.research.elamur.ai/free/en/papers/jiang-2025-teach-small-models-reason-curriculum/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wangyi Jiang, Yaojie Lu, Hongyu Lin, et al.*2025 · 5 citations*
63. **[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*
64. **[HiddenGuard: Fine-Grained Safe Generation with Specialized Representation Router](https://md.research.elamur.ai/free/en/papers/mei-2026-hiddenguard-fine-grained-safe-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.*2026 · 4 citations*
65. **[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*
66. **[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*
67. **[SAFE-QAQ: End-to-End Slow-Thinking Audio-Text Fraud Detection via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-safe-qaq-end-end-slow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peidong Wang, Zhiming Ma, Xin Dai, et al.*2026 · 3 citations*
68. **[Steering Large Language Models for Machine Translation Personalization](https://md.research.elamur.ai/free/en/papers/scalena-2026-steering-large-language-models-machine/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Daniel Scalena, Gabriele Sarti, Arianna Bisazza, et al.*2026 · 3 citations*
69. **[Too Good to be Bad: On the Failure of LLMs to Role-Play Villains](https://md.research.elamur.ai/free/en/papers/yi-2026-too-good-be-bad-failure/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihao Yi, Qingxuan Jiang, Ruotian Ma, et al.*2026 · 3 citations*
70. **[AdaTooler-V: Adaptive Tool-Use for Images and Videos](https://md.research.elamur.ai/free/en/papers/wang-2026-adatooler-v-adaptive-tool-use/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chaoyang Wang, Kaituo Feng, Dongyang Chen, et al.*2026 · 2 citations*
71. **[SCALER: Synthetic Scalable Adaptive Learning Environment for Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2026-scaler-synthetic-scalable-adaptive-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Caijun Xu, Changyi Xiao, Zhongyuan Peng, et al.*2026 · 2 citations*
72. **[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*
73. **[When More Thinking Hurts: Overthinking in LLM Test-Time Compute Scaling](https://md.research.elamur.ai/free/en/papers/zhou-2026-when-more-thinking-hurts-overthinking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shu Zhou, Rui Ling, Junan Chen, et al.*2026 · 2 citations*
74. **[Anti-Length Shift: Dynamic Outlier Truncation for Training Efficient Reasoning Models](https://md.research.elamur.ai/free/en/papers/wu-2026-anti-length-shift-dynamic-outlier/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Wu, Liyi Chen, Congxi Xiao, et al.*2026 · 1 citation*
75. **[ARISE: An Adaptive Resolution-Aware Metric for Test-Time Scaling Evaluation in Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/yin-2026-arise-adaptive-resolution-aware-metric/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhangyue Yin, Qiushi Sun, Zhiyuan Zeng, et al.*2026 · 1 citation*
76. **[ComfyUI-R1: Exploring Reasoning Models for Workflow Generation](https://md.research.elamur.ai/free/en/papers/xu-2026-comfyui-r1-exploring-reasoning-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenran Xu, Yiyu Wang, Xue Yang, et al.*2026 · 1 citation*
77. **[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*
78. **[Discourse Graph Guided Document Translation with Large Language Models](https://md.research.elamur.ai/free/en/papers/pham-2026-discourse-graph-guided-document-translation/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Viet Thanh Pham, Minghan Wang, Hao-Han Liao, et al.*2026 · 1 citation*
79. **[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*
80. **[Enhancing Long-Chain Reasoning Distillation through Error-Aware Self-Reflection](https://md.research.elamur.ai/free/en/papers/wu-2026-enhancing-long-chain-reasoning-distillation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoyang Wu, Xinze Li, Zhenghao Liu, et al.*2026 · 1 citation*
81. **[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*
82. **[Solve-Detect-Verify: Inference-Time Scaling with Flexible Generative Verifier](https://md.research.elamur.ai/free/en/papers/zhong-2026-solve-detect-verify-inference-time/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianyuan Zhong, Zeju Li, Zhijian Xu, et al.*2026 · 1 citation*
83. **[AdaMix: Adaptive Mixing for Short and Long Reasoning Adapters](https://md.research.elamur.ai/free/en/papers/luo-2026-adamix-adaptive-mixing-short-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Luo, Xiao Yan, Xinyan Li, et al.*2026*
84. **[AdapThink: Adaptive Thinking Preferences for Reasoning Language Models](https://md.research.elamur.ai/free/en/papers/xu-2026-adapthink-adaptive-thinking-preferences-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenyue Xu, Xu Wan, Wei Wang, et al.*2026*
85. **[ARM2: Adaptive Reasoning Model with Vision Understanding and Executable Code](https://md.research.elamur.ai/free/en/papers/xie-2026-arm2-adaptive-reasoning-model-vision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jian Xie, Zhendong Chu, Aoxiao Zhong, et al.*2026*
86. **[Can Multi-agent Help Disambiguation in Multi-domain Translation?](https://md.research.elamur.ai/free/en/papers/man-2026-can-multi-agent-help-disambiguation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhibo Man, Shaoyang Xu, Yujie Zhang, et al.*2026*
87. **[CLARO: Controlled Attribute-Driven Reasoning Optimization for Efficient Chain-of-Thought](https://md.research.elamur.ai/free/en/papers/schlesinger-2026-claro-controlled-attribute-driven-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Oded Schlesinger, Young Kyung Kim, J. Matias Di Martino, et al.*2026*
88. **[CogBench: Benchmarking Cognitive Alignment of Large Language Models in Educational Question Answering](https://md.research.elamur.ai/free/en/papers/lu-2026-cogbench-benchmarking-cognitive-alignment-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tong Lu, Zhichun Wang, Yuanhao Sun, et al.*2026*
89. **[ComfyFlow: Benchmarking LLMs for AIGC Workflow Generation](https://md.research.elamur.ai/free/en/papers/xu-2026-comfyflow-benchmarking-llms-aigc-workflow/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenran Xu, Yiyu Wang, Yunxin Li, et al.*2026*
90. **[CoTEvol: Self-Evolving Chain-of-Thoughts for Data Synthesis in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-cotevol-self-evolving-chain-thoughts/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuo Wang, Zhuo Zhang, Yafu Li, et al.*2026*
91. **[Do Multimodal LLMs Understand Order? Measuring the Fragility of Multimodal Reasoning under Input Order Perturbations](https://md.research.elamur.ai/free/en/papers/wei-2026-do-multimodal-llms-understand-order/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Sheng-Lun Wei, Yu-Ling Liao, Hen-Hsen Huang, et al.*2026*
92. **[ETR: Entropy Trend Reward for Efficient Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/xiong-2026-etr-entropy-trend-reward-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuan Xiong, Huan Liu, Li Gu, et al.*2026*
93. **[GrACE: A Generative Approach to Better Confidence Elicitation and Efficient Test-Time Scaling in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-grace-generative-approach-better-confidence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaohan Zhang, Ziquan Liu, Ioannis Patras*2026*
94. **[Multi-Agent Debate for Machine Translation: A Case Study on English-Japanese Translation](https://md.research.elamur.ai/free/en/papers/shen-2026-multi-agent-debate-machine-translation/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Zhan Shen, Jason Naradowsky, Xiaotian Wang, et al.*2026*
95. **[Multi-Agent Reasoning Improves Compute Efficiency: Pareto-Optimal Test-Time Scaling](https://md.research.elamur.ai/free/en/papers/wunderlich-2026-multi-agent-reasoning-improves-compute/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Florian Valentin Wunderlich, Lars Benedikt Kaesberg, Jan Philip Wahle, et al.*2026*
96. **[Multilingual Chain-of-Thought Compression via Cross-Lingual Distillation](https://md.research.elamur.ai/free/en/papers/wan-2026-multilingual-chain-thought-compression-cross/) [Workshop on Multilinguality in the Era of Large Language Models](https://md.research.elamur.ai/free/en/venues/mellm/)**Jiarui Wan, Songming Zhang, Yufeng Chen*2026*
97. **[Reliable Use of Lemmas via Eligibility Reasoning and Section-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/xu-2026-reliable-use-lemmas-eligibility-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhikun Xu, Xiaodong Yu, Ben Zhou, et al.*2026*
98. **[Shorten After You're Right: Lazy Length Penalties for Reasoning RL](https://md.research.elamur.ai/free/en/papers/yuan-2026-shorten-after-you-re-right/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Danlong Yuan, Tian Xie, Shaohan Huang, et al.*2026*
99. **[Smarter edits? Post-editing with error highlights and translation suggestions](https://md.research.elamur.ai/free/en/papers/tellingen-2026-smarter-edits-post-editing-error/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**Fleur V.J. van Tellingen, Gautam Ranka, Dora Žugčić, et al.*2026*
100. **[Social Welfare Function Leaderboard: On the Emergence of LLM Agents as the Welfare Dictator](https://md.research.elamur.ai/free/en/papers/shi-2026-social-welfare-function-leaderboard-emergence/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengliang Shi, Ruotian Ma, Jen-tse Huang, et al.*2026*

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