---
title: "Who cites Jinhao Liu — 165 papers of our library"
description: "165 papers of the Elamur Research library cite the works of Jinhao Liu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/jinhao-liu/cited-by/"
---
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# Who cites Jinhao Liu

166 citations of their works from 165 papers of our library (of the 149,439 whose bibliographies we read) · 65 with a page here, the most cited first · [← Jinhao Liu](https://md.research.elamur.ai/free/en/authors/jinhao-liu/)

1. **[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*
2. [**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/)
3. **[WebThinker: Empowering Large Reasoning Models with Deep Research Capability](https://md.research.elamur.ai/free/en/papers/li-2025-webthinker-empowering-large-reasoning-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoxi Li, Jiajie Jin, Guanting Dong, et al.*2025 · 72 citations*
4. [**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/)
5. [**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/)
6. **[HiAgent: Hierarchical Working Memory Management for Solving Long-Horizon Agent Tasks with Large Language Model](https://md.research.elamur.ai/free/en/papers/hu-2025-hiagent-hierarchical-working-memory-management/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengkang Hu, Tianxing Chen, Qiguang Chen, et al.*2025 · 49 citations*
7. [**Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy arXiv:2507.01352**Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.*2025 · 48 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-skywork-reward-v2-scaling/)
8. [**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/)
9. **[Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens](https://md.research.elamur.ai/free/en/papers/zhao-2026-is-chain-thought-reasoning-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chengshuai Zhao, Zhen Tan, Pingchuan Ma, et al.*2026 · 21 citations*
10. **[AI4Research: A Survey of Artificial Intelligence for Scientific Research](https://md.research.elamur.ai/free/en/papers/chen-2025-ai4research-survey-artificial-intelligence/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Mingda Yang, Libo Qin, et al.*2025 · 21 citations*
11. [**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/)
12. **[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*
13. **[Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning](https://md.research.elamur.ai/free/en/papers/shi-2025-search-refine-during-think-facilitating/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yaorui Shi, Sihang Li, Chang Wu, et al.*2025 · 18 citations*
14. [**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/)
15. [**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/)
16. **[Language Mixing in Reasoning Language Models: Patterns, Impact, and Internal Causes](https://md.research.elamur.ai/free/en/papers/wang-2025-language-mixing-reasoning-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mingyang Wang, Lukas Lange, Heike Adel, et al.*2025 · 16 citations*
17. **[What are the Essential Factors in Crafting Effective Long Context Multi-Hop Instruction Datasets? Insights and Best Practices](https://md.research.elamur.ai/free/en/papers/chen-2025-what-are-essential-factors-crafting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhi Chen, Qiguang Chen, Libo Qin, et al.*2025 · 15 citations*
18. **[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*
19. **[DeepTrans: Deep Reasoning Translation via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-deeptrans-deep-reasoning-translation-reinforcement/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiaan Wang, Fandong Meng, Jie Zhou*2026 · 11 citations*
20. **[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*
21. **[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*
22. **[A Survey of Inductive Reasoning for Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2026-survey-inductive-reasoning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kedi Chen, Dezhao Ruan, Yuhao Dan, et al.*2026 · 10 citations*
23. [**EvoScientist: Towards Multi-Agent Evolving AI Scientists for End-to-End Scientific Discovery arXiv:2603.08127**Yougang Lyu, Xi Zhang, Xinhao Yi, et al.*2026 · 10 citations*](https://md.research.elamur.ai/free/en/papers/lyu-2026-evoscientist-towards-multi-agent-evolving/)
24. **[An Efficient and Precise Training Data Construction Framework for Process-supervised Reward Model in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/sun-2025-efficient-precise-training-data-construction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Sun, Qianlong Du, Fuwei Cui, et al.*2025 · 10 citations*
25. [**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/)
26. **[AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific Research](https://md.research.elamur.ai/free/en/papers/zhao-2025-abgen-evaluating-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilun Zhao, Weiyuan Chen, Zhijian Xu, et al.*2025 · 9 citations*
27. **[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*
28. **[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*
29. **[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*
30. **[Sparse-RL: Breaking the Memory Wall in LLM Reinforcement Learning via Stable Sparse Rollouts](https://md.research.elamur.ai/free/en/papers/luo-2026-sparse-rl-breaking-memory-wall/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sijia Luo, Xiaokang Zhang, Yuxuan Hu, et al.*2026 · 4 citations*
31. **[Beyond Templates: Dynamic Adaptation of Reasoning Demonstrations via Feasibility-Aware Exploration](https://md.research.elamur.ai/free/en/papers/wu-2026-beyond-templates-dynamic-adaptation-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yong Wu, Weihang Pan, Ke Li, et al.*2026 · 3 citations*
32. **[Blind Spot Navigation in Large Language Model Reasoning with Thought Space Explorer](https://md.research.elamur.ai/free/en/papers/zhang-2026-blind-spot-navigation-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinghan Zhang, Fengran Mo, Tharindu Cyril Weerasooriya, et al.*2026 · 3 citations*
33. **[HAUNTATTACK: When Attack Follows Reasoning as a Shadow](https://md.research.elamur.ai/free/en/papers/ma-2026-hauntattack-when-attack-follows-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingyuan Ma, Rui Li, Zheng Li, et al.*2026 · 3 citations*
34. **[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*
35. **[Agentic Conversational Search with Contextualized Reasoning via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/mo-2026-agentic-conversational-search-contextualized-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fengran Mo, Yifan Gao, Sha Li, et al.*2026 · 2 citations*
36. **[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*
37. **[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*
38. **[Can AI Be a Good Peer Reviewer? A Survey of Peer Review Process, Evaluation, and the Future](https://md.research.elamur.ai/free/en/papers/wu-2026-can-ai-be-good-peer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sihong Wu, Owen Jiang, Yilun Zhao, et al.*2026 · 1 citation*
39. **[COMPASS: Enhancing Agent Long-Horizon Reasoning with Evolving Context](https://md.research.elamur.ai/free/en/papers/wan-2026-compass-enhancing-agent-long-horizon/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guangya Wan, Mingyang Ling, Xiaoqi Ren, et al.*2026 · 1 citation*
40. **[Process Reward Models Meet Planning: Generating Precise and Scalable Datasets for Step-Level Rewards](https://md.research.elamur.ai/free/en/papers/pisano-2026-process-reward-models-meet-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Raffaele Pisano, Roberto Navigli*2026 · 1 citation*
41. **[Reasoning Fails Where Step Flow Breaks](https://md.research.elamur.ai/free/en/papers/xu-2026-reasoning-fails-where-step-flow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyu Xu, Yulan Pan, Xiaosong Yuan, et al.*2026 · 1 citation*
42. **[ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments](https://md.research.elamur.ai/free/en/papers/wang-2026-reasoningguard-safeguarding-large-reasoning-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuquan Wang, Mi Zhang, Yining Wang, et al.*2026 · 1 citation*
43. **[ThinkBrake: Efficient Reasoning via Log-Probability Margin Guided Decoding](https://md.research.elamur.ai/free/en/papers/song-2026-thinkbrake-efficient-reasoning-log-probability/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sangjun Song, Minjae Oh, Seungkyu Lee, et al.*2026 · 1 citation*
44. **[What Factors Affect LLMs and RLLMs in Financial Question Answering?](https://md.research.elamur.ai/free/en/papers/wang-2026-what-factors-affect-llms-rllms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Peng Wang, Xuesi Hu, Jiageng Wu, et al.*2026 · 1 citation*
45. **[When Is Thinking Enough? Early Exit via Sufficiency Assessment for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/xiang-2026-when-is-thinking-enough-early/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Xiang, Yixin Ji, Ruotao Xu, et al.*2026 · 1 citation*
46. **[Where Reasoning Breaks: Logic-Aware Path Selection by Controlling Logical Connectives in LLMs Reasoning Chains](https://md.research.elamur.ai/free/en/papers/park-2026-where-reasoning-breaks-logic-aware/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Seunghyun Park, Yuanyuan Lei*2026 · 1 citation*
47. **[AlgBench: To What Extent Do Large Reasoning Models Understand Algorithms?](https://md.research.elamur.ai/free/en/papers/sun-2026-algbench-what-extent-do-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Henan Sun, Kaichi Yu, Yuyao Wang, et al.*2026*
48. **[Automatic Paper Analysis and Categorisation for Systematic Reviews with Combined Reasoning-Augmented SFT and DAPO RL](https://md.research.elamur.ai/free/en/papers/lorandi-2026-automatic-paper-analysis-categorisation-systematic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Michela Lorandi, Anya Belz, Simon Mille, et al.*2026*
49. **[Automatic Slide Updating with User-Defined Dynamic Templates and Natural Language Instructions](https://md.research.elamur.ai/free/en/papers/zhou-2026-automatic-slide-updating-user-defined/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kun Zhou, Jiakai He, Wenmian Yang, et al.*2026*
50. **[Beyond Unimodal Shortcuts: MLLMs as Cross-Modal Reasoners for Grounded Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/ma-2026-beyond-unimodal-shortcuts-mllms-as/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinlong Ma, Yu Zhang, Xuefeng Bai, et al.*2026*
51. **[CheckRLM: Effective Knowledge–Thought Coherence Checking in Retrieval-Augmented Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2026-checkrlm-effective-knowledge-thought-coherence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dingling Xu, Ruobing Wang, Qingfei Zhao, et al.*2026*
52. **[ChemVLR: Prioritizing Reasoning in Perception for Chemical Vision-Language Understanding](https://md.research.elamur.ai/free/en/papers/zhao-2026-chemvlr-prioritizing-reasoning-perception-chemical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuanle Zhao, Xinyuan Cai, Xiang Cheng, et al.*2026*
53. **[Curing Miracle Steps in LLM Mathematical Reasoning with Rubric Rewards](https://md.research.elamur.ai/free/en/papers/yuan-2026-curing-miracle-steps-llm-mathematical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youliang Yuan, Qiuyang Mang, Jingbang Chen, et al.*2026*
54. **[Exploring Layer Activation Dynamic of CoT via Knowledge Probe](https://md.research.elamur.ai/free/en/papers/zhang-2026-exploring-layer-activation-dynamic-cot/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chuanxin Zhang, Jiajun Liu, Yao He, et al.*2026*
55. **[FeedTrans: Enhance Machine Translation via Feedback](https://md.research.elamur.ai/free/en/papers/sun-2026-feedtrans-enhance-machine-translation-feedback/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zengkui Sun, Jiali Zeng, Jiaan Wang, et al.*2026*
56. **[Fico: Evaluating Vision-Language Models under Visual Fidelity and Compression at Scale](https://md.research.elamur.ai/free/en/papers/tu-2026-fico-evaluating-vision-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianhong Tu, Nicholas Crispino, Kyle Montgomery, et al.*2026*
57. **[Less Languages, Less Tokens: An Efficient Unified Logic Cross-lingual Chain-of-Thought Reasoning Framework](https://md.research.elamur.ai/free/en/papers/zhang-2026-less-languages-less-tokens-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenyuan Zhang, Qiguang Chen, Xie Chen, et al.*2026*
58. **[MMSciCode: Real-world Evaluation of Multilingual Multi-Discipline Scientific Research Coding](https://md.research.elamur.ai/free/en/papers/xia-2026-mmscicode-real-world-evaluation-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xue Xia, Zheyuan Yang, Arman Cohan, et al.*2026*
59. **[ODTQA-FoRe: An Open-Domain Tabular Question Answering Dataset for Future Data Forecasting and Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2026-odtqa-fore-open-domain-tabular/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhensheng Wang, Xiaole Liu, Wenmian Yang, et al.*2026*
60. **[ReCoQA: A Benchmark for Tool-Augmented and Multi-Step Reasoning in Real Estate Question and Answering](https://md.research.elamur.ai/free/en/papers/zhang-2026-recoqa-benchmark-tool-augmented-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yindong Zhang, Wenmian Yang, Yiquan Zhang, et al.*2026*
61. **[RiT: Rubrics-in-Thinking Reinforcement Learning for Improved Reasoning in Large Language Models](https://md.research.elamur.ai/free/en/papers/tian-2026-rit-rubrics-thinking-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaobin Tian, Shuai Yuan, Muyun Ding, et al.*2026*
62. **[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*
63. **[Think Less, Know More: State-Aware Reasoning Compression with Knowledge Guidance for Efficient Reasoning](https://md.research.elamur.ai/free/en/papers/sui-2026-think-less-know-more-state/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yi Sui, Chaozhuo Li, Dawei Song*2026*
64. **[Time-for-Accuracy: Formalizing Chain-of-Thought as an Expansion of Logical Depth](https://md.research.elamur.ai/free/en/papers/wang-2026-time-accuracy-formalizing-chain-thought/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yue Wang, Zhi Zhang, Wang Xi, et al.*2026*
65. **[What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations](https://md.research.elamur.ai/free/en/papers/luo-2026-what-makes-ai-research-replicable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yujie Luo, Zhuoyun Yu, Xuehai Wang, et al.*2026*

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