---
title: "Who cites Shiyi Cao — 941 papers of our library"
description: "941 papers of the Elamur Research library cite the works of Shiyi Cao, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Shiyi Cao

1,035 citations of their works from 941 papers of our library (of the 149,439 whose bibliographies we read) · 116 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Shiyi Cao](https://md.research.elamur.ai/free/en/authors/shiyi-cao/)

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1. **[SGLang: Efficient Execution of Structured Language Model Programs](https://md.research.elamur.ai/free/en/papers/zheng-2023-sglang-efficient-execution-structured-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.*2023 · 729 citations*
2. [**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/)
3. **[Large Language Models for Generative Information Extraction: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2023-large-language-models-generative-information/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Derong Xu, Wei Chen, Wenjun Peng, et al.*2023 · 406 citations*
4. [**Splitwise: Efficient generative LLM inference using phase splitting ISCA 2024**Pratyush Patel, Esha Choukse, Chaojie Zhang, et al.*2023 · 379 citations*](https://md.research.elamur.ai/free/en/papers/patel-2023-splitwise-efficient-generative-llm-inference/)
5. [**A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications arXiv:2402.07927**Pranab Sahoo; Ayush Kumar Singh; Sriparna Saha; Vinija Jain; Samrat Mondal;, Aman Chadha*2024 · 375 citations*](https://md.research.elamur.ai/free/en/papers/sahoo-2024-systematic-survey-prompt-engineering-large/)
6. [**Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve OSDI 2024**Amey Agrawal, Nitin Kedia, Ashish Panwar, et al.*2024 · 369 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2024-taming-throughput-latency-tradeoff-llm/)
7. **[PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU](https://md.research.elamur.ai/free/en/papers/song-2023-powerinfer-fast-large-language-model/) [ACM SIGOPS Symposium on Operating Systems Principles (SOSP)](https://md.research.elamur.ai/free/en/venues/acm-sigops-symposium-on-operating-systems-principles-sosp/)**Yixin Song, Zeyu Mi, Haotong Xie, et al.*2023 · 272 citations*
8. [**Large Language Monkeys: Scaling Inference Compute with Repeated Sampling arXiv:2407.21787**Bradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.*2024 · 270 citations*](https://md.research.elamur.ai/free/en/papers/brown-2024-large-language-monkeys-scaling-inference/)
9. [**Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey arXiv:2403.14608**Zeyu Han, Chao Gao, Jinyang Liu, et al.*2024 · 240 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-parameter-efficient-fine-tuning-large/)
10. [**FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving MLSys 2025**Zihao Ye, Lequn Chen, Ruihang Lai, et al.*2025 · 177 citations*](https://md.research.elamur.ai/free/en/papers/ye-2025-flashinfer-efficient-customizable-attention-engine/)
11. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
12. [**Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving FAST 2025**Ruoyu Qin, Zheming Li, Weiran He, et al.*2024 · 161 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-mooncake-kvcache-centric-disaggregated-architecture/)
13. **[Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-80-20-rule-high-entropy/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shenzhi Wang, Le Yu, Chang Gao, et al.*2025 · 152 citations*
14. [**Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs arXiv:2503.01307**Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.*2025 · 123 citations*](https://md.research.elamur.ai/free/en/papers/gandhi-2025-cognitive-behaviors-that-enable-self/)
15. [**Fast Distributed Inference Serving for Large Language Models arXiv 2023**Bingyang Wu, Yinmin Zhong, Zili Zhang, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-fast-distributed-inference-serving-large/)
16. [**Demystifying Long Chain-of-Thought Reasoning in LLMs arXiv:2502.03373**Edward Yeo, Yuxuan Tong, Morry Niu, et al.*2025 · 119 citations*](https://md.research.elamur.ai/free/en/papers/yeo-2025-demystifying-long-chain-thought-reasoning/)
17. [**Llumnix: Dynamic Scheduling for Large Language Model Serving OSDI 2024**Biao Sun, Ziming Huang, Hanyu Zhao, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-llumnix-dynamic-scheduling-large-language/)
18. [**A Survey on Efficient Inference for Large Language Models arXiv:2404.14294**Zixuan Zhou, Xuefei Ning, Ke Hong, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-survey-efficient-inference-large-language/)
19. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations*
20. **[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*
21. [**Cost-Efficient Large Language Model Serving for Multi-turn Conversations with CachedAttention USENIX ATC 2024**Bin Gao, Zhuomin He, Puru Sharma, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/gao-2024-cost-efficient-large-language-model/)
22. [**ServerlessLLM: Low-Latency Serverless Inference for Large Language Models arXiv:2401.14351**Yao Fu, Leyang Xue, Yeqi Huang, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-serverlessllm-low-latency-serverless-inference/)
23. **[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*
24. **[Optimizing Instructions and Demonstrations for Multi-Stage Language Model Programs](https://md.research.elamur.ai/free/en/papers/ong-2024-optimizing-instructions-demonstrations-multi-stage/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Krista Opsahl-Ong, Michael J Ryan, Josh Purtell, et al.*2024 · 99 citations*
25. [**AFlow: Automating Agentic Workflow Generation arXiv:2410.10762**Jiayi Zhang, Jinyu Xiang, Zhaoyang Yu, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-aflow-automating-agentic-workflow/)
26. **[LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style Plugin](https://md.research.elamur.ai/free/en/papers/dou-2024-loramoe-alleviating-world-knowledge-forgetting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shihan Dou, Enyu Zhou, Yan Liu, et al.*2024 · 93 citations*
27. **[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*
28. [**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/)
29. [**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/)
30. [**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/)
31. [**VinePPO: Refining Credit Assignment in RL Training of LLMs arXiv:2410.01679**Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, et al.*2024 · 63 citations*](https://md.research.elamur.ai/free/en/papers/kazemnejad-2024-vineppo-refining-credit-assignment-rl/)
32. [**MiMo-V2-Flash Technical Report arXiv:2601.02780**Xiaomi LLM-Core Team; Bangjun Xiao; Bingquan Xia; Bo Yang; Bofei Gao; Bowen Shen; Chen Zhang; Chenhong He; Chiheng Lou; Fuli Luo; Gang Wang; Gang Xie; Hailin Zhang; Hanglong Lv; Hanyu Li; Heyu Chen; Hongshen Xu; Houbin Zhang; Huaqiu Liu; Jiangshan Duo; Jianyu Wei; Jiebao Xiao; Jinhao Dong; Jun Shi; Junhao Hu; Kainan Bao; Kang Zhou; Lei Li; Liang Zhao; Linghao Zhang; Peidian Li; Qianli Chen; Shaohui Liu; Shihua Yu; Shijie Cao; Shimao Chen; Shouqiu Yu; Shuo Liu; Tianling Zhou; Weijiang Su; Weikun Wang; Wenhan Ma; Xiangwei Deng; Bohan Mao; Bowen Ye; Can Cai; Chenghua Wang; Chengxuan Zhu; Chong Ma; Chun Chen; Chunan Li; Dawei Zhu; Deshan Xiao; Dong Zhang; Duo Zhang; Fangyue Liu; Feiyu Yang; Fengyuan Shi; Guoan Wang; Hao Tian; Hao Wu; Heng Qu; Hongfei Yi; Hongxu An; Hongyi Guan; Xing Zhang; Yifan Song; Yihan Yan; Yihao Zhao; Yingchun Lai; Yizhao Gao; Yu Cheng; Yuanyuan Tian; Yudong Wang; Zhen Tang; Zhengju Tang; Zhengtao Wen; Zhichao Song; Zhixian Zheng; Zihan Jiang; Jian Wen; Jiarui Sun; Jiawei Li; Jinlong Xue; Jun Xia; Kai Fang; Menghang Zhu; Nuo Chen; Qian Tu; Qihao Zhang; Qiying Wang; Rang Li; Rui Ma; Shaolei Zhang; Shengfan Wang; Shicheng Li; Shuhao Gu; Shuhuai Ren; Sirui Deng; Tao Guo; Tianyang Lu; Weiji Zhuang; Weikang Zhang; Weimin Xiong; Wenshan Huang; Wenyu Yang; Xin Zhang; Xing Yong; Xu Wang; Xueyang Xie; Yilin Jiang; Yixin Yang; Yongzhe He; Yu Tu; Yuanliang Dong; Yuchen Liu; Yue Ma; Yue Yu; Yuxing Xiang; Zhaojun Huang; Zhenru Lin; Zhipeng Xu; Zhiyang Chen; Zhonghua Deng; Zihan Zhang;, Zihao Yue*2026 · 60 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-llm-mimo-v2-flash-technical/)
33. [**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/)
34. **[VariErr NLI: Separating Annotation Error from Human Label Variation](https://md.research.elamur.ai/free/en/papers/genzel-2024-varierr-nli-separating-annotation-error/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Leon Weber-Genzel, Siyao Peng, Marie-Catherine De Marneffe, et al.*2024 · 51 citations*
35. [**olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language Models arXiv:2502.18443**Jake Poznanski, Aman Rangapur, Jon Borchardt, et al.*2025 · 44 citations*](https://md.research.elamur.ai/free/en/papers/poznanski-2025-olmocr-unlocking-trillions-tokens-pdfs/)
36. [**Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning arXiv:2412.09078**Zhenni Bi, Kai Han, Chuanjian Liu, et al.*2024 · 43 citations*](https://md.research.elamur.ai/free/en/papers/bi-2024-forest-thought-scaling-test-time/)
37. **[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*
38. **[Dynamic Cheatsheet: Test-Time Learning with Adaptive Memory](https://md.research.elamur.ai/free/en/papers/suzgun-2026-dynamic-cheatsheet-test-time-learning/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mirac Suzgun, Mert Yuksekgonul, Federico Bianchi, et al.*2026 · 37 citations*
39. [**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/)
40. [**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/)
41. **[Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space](https://md.research.elamur.ai/free/en/papers/zhang-2025-soft-thinking-unlocking-reasoning-potential/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhen Zhang, Xuehai He, Weixiang Yan, et al.*2025 · 25 citations*
42. **[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*
43. [**Baichuan-M2: Scaling Medical Capability with Large Verifier System arXiv:2509.02208**Chengfeng Dou, Chong Liu, Fan Yang, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-m2-baichuan-m2-scaling-medical/)
44. [**JSONSchemaBench: A Rigorous Benchmark of Structured Outputs for Language Models arXiv:2501.10868**Saibo Geng, Hudson Cooper, Michał Moskal, et al.*2025 · 19 citations*](https://md.research.elamur.ai/free/en/papers/geng-2025-jsonschemabench-rigorous-benchmark-structured-outputs/)
45. [**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/)
46. **[PlanGEN: A Multi-Agent Framework for Generating Planning and Reasoning Trajectories for Complex Problem Solving](https://md.research.elamur.ai/free/en/papers/parmar-2025-plangen-multi-agent-framework-generating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mihir Parmar, Xin Liu, Palash Goyal, et al.*2025 · 16 citations*
47. [**ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning arXiv:2501.06590**Xiangru Tang, Tianyu Hu, Muyang Ye, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/tang-2025-chemagent-self-updating-library-large/)
48. **[FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative Sampling](https://md.research.elamur.ai/free/en/papers/zhao-2025-fr-spec-accelerating-large-vocabulary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weilin Zhao, Tengyu Pan, Xu Han, et al.*2025 · 15 citations*
49. [**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/)
50. [**Scaling Speech-Text Pre-training with Synthetic Interleaved Data arXiv:2411.17607**Aohan Zeng, Zhengxiao Du, Mingdao Liu, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-scaling-speech-text-pre-training/)
51. **[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*
52. **[Memory as Action: Autonomous Context Curation for Long-Horizon Agentic Tasks](https://md.research.elamur.ai/free/en/papers/zhang-2026-memory-as-action-autonomous-context/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxiang Zhang, Jiangming Shu, Ye Ma, et al.*2026 · 10 citations*
53. **[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*
54. **[Stepwise Reasoning Disruption Attack of LLMs](https://md.research.elamur.ai/free/en/papers/peng-2025-stepwise-reasoning-disruption-attack-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingyu Peng, Maolin Wang, Xiangyu Zhao, et al.*2025 · 10 citations*
55. **[TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/wu-2026-templaterl-structured-template-guided-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jinyang Wu, Chonghua Liao, Mingkuan Feng, et al.*2026 · 8 citations*
56. **[CER: Confidence Enhanced Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/razghandi-2025-cer-confidence-enhanced-reasoning-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ali Razghandi, Seyed Mohammad Hadi Hosseini, Mahdieh Soleymani Baghshah*2025 · 8 citations*
57. **[FastMCTS: A Simple Sampling Strategy for Data Synthesis](https://md.research.elamur.ai/free/en/papers/li-2025-fastmcts-simple-sampling-strategy-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peiji Li, Kai Lv, Yunfan Shao, et al.*2025 · 8 citations*
58. **[MetaScale: Test-Time Scaling with Evolving Meta-Thoughts](https://md.research.elamur.ai/free/en/papers/liu-2026-metascale-test-time-scaling-evolving/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qin Liu, Wenxuan Zhou, Nan Xu, et al.*2026 · 7 citations*
59. [**rStar2-Agent: Agentic Reasoning Technical Report arXiv:2508.20722**Ning Shang, Yifei Liu, Yi Zhu, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/shang-2025-rstar2-agent-agentic-reasoning/)
60. **[INFACT: A Diagnostic Benchmark for Induced Faithfulness and Factuality Hallucinations in Video-LLMs](https://md.research.elamur.ai/free/en/papers/yangjunqi-2026-infact-diagnostic-benchmark-induced-faithfulness/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yangjunqi, Yuecong Min, Jie Zhang, et al.*2026 · 5 citations*
61. **[Is Chain-of-Thought Really Not Explainability? Chain-of-Thought Can Be Faithful without Hint Verbalization](https://md.research.elamur.ai/free/en/papers/zaman-2026-is-chain-thought-really-not/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kerem Zaman, Shashank Srivastava*2026 · 5 citations*
62. **[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*
63. **[Recitation over Reasoning: How Cutting-Edge Language Models Can Fail on Elementary School-Level Reasoning Problems?](https://md.research.elamur.ai/free/en/papers/yan-2025-recitation-over-reasoning-how-cutting/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Kai Yan, Yufei Xu, Zhengyin Du, et al.*2025 · 5 citations*
64. **[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*
65. **[SSSD: Simply-Scalable Speculative Decoding](https://md.research.elamur.ai/free/en/papers/marzollo-2026-sssd-simply-scalable-speculative-decoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michele Marzollo, Jiawei Zhuang, Niklas Roemer, et al.*2026 · 3 citations*
66. [**Baichuan-M3: Modeling Clinical Inquiry for Reliable Medical Decision-Making arXiv:2602.06570**Chengfeng Dou, Fan Yang, Fei Li, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/team-2026-m3-baichuan-m3-modeling-clinical/)
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93. **[Experience is the Teacher: Reusing Atomic Thoughts from LLMs to Improve Medical Dialogue](https://md.research.elamur.ai/free/en/papers/yu-2026-experience-is-teacher-reusing-atomic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangya Yu, Hui Luo, Qi Ye, et al.*2026*
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