---
title: "Who cites Yuyao Wang — 357 papers of our library"
description: "357 papers of the Elamur Research library cite the works of Yuyao Wang, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/yuyao-wang/cited-by/"
---
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# Who cites Yuyao Wang

357 citations of their works from 357 papers of our library (of the 149,439 whose bibliographies we read) · 82 with a page here, the most cited first · [← Yuyao Wang](https://md.research.elamur.ai/free/en/authors/yuyao-wang/)

1. [**The Llama 3 Herd of Models arXiv:2407.21783**Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.*2024 · 7,682 citations*](https://md.research.elamur.ai/free/en/papers/grattafiori-2024-llama-3-herd-models/)
2. **[A Survey on Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,648 citations*
3. [**Qwen3 Technical Report arXiv:2505.09388**An Yang, Anfeng Li, Baosong Yang, et al.*2025 · 3,382 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-qwen3-technical-report/)
4. **[CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society](https://md.research.elamur.ai/free/en/papers/li-2023-camel-communicative-agents-mind/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani, et al.*2023 · 706 citations*
5. [**SWE-bench: Can Language Models Resolve Real-World GitHub Issues? arXiv:2310.06770**Carlos E. Jimenez, John Yang, Alexander Wettig, et al.*2024 · 704 citations*](https://md.research.elamur.ai/free/en/papers/jimenez-2024-swe-bench-can-language-models/)
6. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
7. [**Qwen2.5-Coder Technical Report arXiv:2409.12186**Binyuan Hui, Jian Yang, Zeyu Cui, et al.*2024 · 559 citations*](https://md.research.elamur.ai/free/en/papers/hui-2024-qwen2-5-coder-technical-report/)
8. **[SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering](https://md.research.elamur.ai/free/en/papers/yang-2024-swe-agent-agent-computer-interfaces/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**John Yang, Carlos E. Jimenez, Alexander Wettig, et al.*2024 · 552 citations*
9. [**Phi-4 Technical Report arXiv:2412.08905**Marah Abdin, Jyoti Aneja, Harkirat Behl, et al.*2024 · 502 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-4-technical-report/)
10. [**Tulu 3: Pushing Frontiers in Open Language Model Post-Training arXiv:2411.15124**Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.*2024 · 423 citations*](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/)
11. [**A Survey on Large Language Models for Code Generation arXiv:2406.00515**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
12. [**Kimi K2: Open Agentic Intelligence arXiv:2507.20534**Kimi Team, Yifan Bai, Yiping Bao, et al.*2025 · 347 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k2-open-agentic/)
13. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
14. [**Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model? arXiv:2504.13837 · NeurIPS 2025 Oral; ICML 2025 AI4MATH workshop best paper**Yang Yue, Zhiqi Chen, Rui Lu, et al.*2025 · 216 citations*](https://md.research.elamur.ai/free/en/papers/yue-2025-reinforcement-learning-really-incentivize-reasoning/)
15. [**Aligning Large Language Models with Human: A Survey arXiv:2307.12966**Yufei Wang, Wanjun Zhong, Liangyou Li, et al.*2023 · 202 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-aligning-large-language-models-human/)
16. **[A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 200 citations*
17. [**DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence arXiv:2406.11931**DeepSeek-AI, Qihao Zhu, Daya Guo, et al.*2024 · 196 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2024-deepseek-coder-v2-breaking-barrier/)
18. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
19. [**BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions arXiv:2406.15877**Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.*2024 · 176 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-bigcodebench-benchmarking-code-generation-diverse/)
20. [**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/)
21. [**CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution arXiv:2401.03065**Alex Gu, Baptiste Rozière, Hugh Leather, et al.*2024 · 122 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-cruxeval-benchmark-code-reasoning-understanding/)
22. [**Nemotron-4 340B Technical Report arXiv:2406.11704**Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/adler-2024-nemotron-4-340b-technical-report/)
23. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
24. **[MAmmoTH2: Scaling Instructions from the Web](https://md.research.elamur.ai/free/en/papers/yue-2024-mammoth2-scaling-instructions-web/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiang Yue, Tuney Zheng, Ge Zhang, et al.*2024 · 96 citations*
25. **[OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models](https://md.research.elamur.ai/free/en/papers/huang-2025-opencoder-open-cookbook-top-tier/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Siming Huang, Tianhao Cheng, Jason Klein Liu, et al.*2025 · 81 citations*
26. **[What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering](https://md.research.elamur.ai/free/en/papers/errica-2025-what-did-i-do-wrong/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Federico Errica, Davide Sanvito, Giuseppe Siracusano, et al.*2025 · 63 citations*
27. [**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/)
28. [**RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and Style arXiv:2410.16184**Yantao Liu, Zijun Yao, Rui Min, et al.*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-rm-bench-benchmarking-reward-models/)
29. [**Kimi Linear: An Expressive, Efficient Attention Architecture arXiv:2510.26692**Kimi Team, Yu Zhang, Zongyu Lin, et al.*2025 · 51 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-linear-expressive-efficient/)
30. [**RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning arXiv:2410.02089**Jonas Gehring, Kunhao Zheng, Jade Copet, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/gehring-2024-rlef-grounding-code-llms-execution/)
31. [**MiniMax-01: Scaling Foundation Models with Lightning Attention arXiv:2501.08313**MiniMax, Aonian Li, Bangwei Gong, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-01-scaling-foundation/)
32. **[Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback](https://md.research.elamur.ai/free/en/papers/ivison-2024-unpacking-dpo-ppo-disentangling-best/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hamish Ivison, Yizhong Wang, Jiacheng Liu, et al.*2024 · 50 citations*
33. [**RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation arXiv:2403.05313**Zihao Wang, Anji Liu, Haowei Lin, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-rat-retrieval-augmented-thoughts-elicit/)
34. [**DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models arXiv:2507.09955**Luolin Xiong, Haofen Wang, Xi Chen, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2025-deepseek-paradigm-shifts-technical/)
35. [**Observational Scaling Laws and the Predictability of Language Model Performance arXiv:2405.10938**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/)
36. [**NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model arXiv:2508.14444**NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.*2025 · 39 citations*](https://md.research.elamur.ai/free/en/papers/basant-2025-nvidia-nemotron-nano-2-accurate/)
37. [**Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models arXiv:2504.03624**NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.*2025 · 38 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-h-family-accurate-efficient/)
38. [**Through the Lens of Core Competency: Survey on Evaluation of Large Language Models arXiv:2308.07902**Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-through-lens-core-competency-survey/)
39. **[Evaluating Language Models as Synthetic Data Generators](https://md.research.elamur.ai/free/en/papers/kim-2025-evaluating-language-models-as-synthetic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Seungone Kim, Juyoung Suk, Xiang Yue, et al.*2025 · 32 citations*
40. **[SelfCodeAlign: Self-Alignment for Code Generation](https://md.research.elamur.ai/free/en/papers/wei-2024-selfcodealign-self-alignment-code-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuxiang Wei, Federico Cassano, Jiawei Liu, et al.*2024 · 32 citations*
41. [**Exploring the Relationship between LLM Hallucinations and Prompt Linguistic Nuances: Readability, Formality, and Concreteness arXiv:2309.11064**Vipula Rawte, Prachi Priya, S.M Towhidul Islam Tonmoy, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/rawte-2023-exploring-relationship-between-llm-hallucinations/)
42. [**Seed-Coder: Let the Code Model Curate Data for Itself arXiv:2506.03524**ByteDance Seed, Yuyu Zhang, Jing Su, et al.*2025 · 25 citations*](https://md.research.elamur.ai/free/en/papers/bytedance-seed-2025-seed-coder-let-code/)
43. [**Baichuan-M1: Pushing the Medical Capability of Large Language Models arXiv:2502.12671**Bingning Wang, Haizhou Zhao, Huozhi Zhou, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-baichuan-m1-pushing-medical/)
44. [**Scaling Latent Reasoning via Looped Language Models arXiv:2510.25741**Rui-Jie Zhu, Zixuan Wang, Kai Hua, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-scaling-latent-reasoning-looped-language/)
45. [**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/)
46. **[“Give Me BF16 or Give Me Death”? Accuracy-Performance Trade-Offs in LLM Quantization](https://md.research.elamur.ai/free/en/papers/kurtic-2025-give-me-bf16-or-give/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Eldar Kurtic, Alexandre Noll Marques, Shubhra Pandit, et al.*2025 · 21 citations*
47. **[CodeDPO: Aligning Code Models with Self Generated and Verified Source Code](https://md.research.elamur.ai/free/en/papers/zhang-2025-codedpo-aligning-code-models-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kechi Zhang, Ge Li, Yihong Dong, et al.*2025 · 20 citations*
48. **[NaturalCodeBench: Examining Coding Performance Mismatch on HumanEval and Natural User Queries](https://md.research.elamur.ai/free/en/papers/zhang-2024-naturalcodebench-examining-coding-performance-mismatch/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shudan Zhang, Hanlin Zhao, Xiao Liu, et al.*2024 · 17 citations*
49. [**Qwen3-Coder-Next Technical Report arXiv:2603.00729**Ruisheng Cao, Mouxiang Chen, Jiawei Chen, et al.*2026 · 15 citations*](https://md.research.elamur.ai/free/en/papers/cao-2026-qwen3-coder-next-technical/)
50. [**Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance arXiv:2507.22448**Jingwei Zuo, Maksim Velikanov, Ilyas Chahed, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/zuo-2025-falcon-h1-family-hybrid-head/)
51. [**Data-driven Discovery with Large Generative Models arXiv:2402.13610**Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/majumder-2024-data-driven-discovery-large-generative/)
52. [**From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging arXiv:2410.01215**Yuling Shi, Songsong Wang, Chengcheng Wan, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shi-2024-code-correctness-closing-last-mile/)
53. **[Prompting Large Language Models to Tackle the Full Software Development Lifecycle: A Case Study](https://md.research.elamur.ai/free/en/papers/li-2025-prompting-large-language-models-tackle/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Bowen Li, Wenhan Wu, Ziwei Tang, et al.*2025 · 13 citations*
54. [**EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuning arXiv:2410.10209**Dong Huang, Guangtao Zeng, Jianbo Dai, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-efficoder-enhancing-code-generation-large/)
55. **[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*
56. **[rStar-Coder: Scaling Competitive Code Reasoning with a Large-Scale Verified Dataset](https://md.research.elamur.ai/free/en/papers/liu-2025-rstar-coder-scaling-competitive/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yifei Liu, Li Lyna Zhang, Yi Zhu, et al.*2025 · 8 citations*
57. **[Assessing the Creativity of LLMs in Proposing Novel Solutions to Mathematical Problems](https://md.research.elamur.ai/free/en/papers/ye-2024-assessing-creativity-llms-proposing-novel/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Junyi Ye, Jingyi Gu, Xinyun Zhao, et al.*2024 · 8 citations*
58. [**StepFun-Formalizer: Unlocking the Autoformalization Potential of LLMs through Knowledge-Reasoning Fusion arXiv:2508.04440**Yutong Wu, Di Huang, Ruosi Wan, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wu-2025-stepfun-formalizer-unlocking-autoformalization/)
59. **[From Completion to Editing: Unlocking Context-Aware Code Infilling via Search-and-Replace Instruction Tuning](https://md.research.elamur.ai/free/en/papers/zhang-2026-completion-editing-unlocking-context-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiajun Zhang, Zeyu Cui, Jiaxi Yang, et al.*2026 · 6 citations*
60. **[CODERL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment](https://md.research.elamur.ai/free/en/papers/jiang-2026-coderl-improving-code-generation-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xue Jiang, Yihong Dong, Mengyang Liu, et al.*2026 · 5 citations*
61. **[Don't Judge Code by Its Cover: Exploring Biases in LLM Judges for Code Evaluation](https://md.research.elamur.ai/free/en/papers/moon-2026-don-t-judge-code-its/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiwon Moon, Yerin Hwang, Dongryeol Lee, et al.*2026 · 5 citations*
62. [**Less is More: Selective Reflection for Compatible and Efficient Knowledge Distillation in Large Language Models arXiv:2508.06135**Lingyuan Liu, Mengxiang Zhang*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-less-more-selective-reflection-compatible/)
63. **[MAPRO: Recasting Multi-Agent Prompt Optimization as Maximum a Posteriori Inference](https://md.research.elamur.ai/free/en/papers/zhang-2026-mapro-recasting-multi-agent-prompt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheyuan Zhang, Lin Ge, Hongjiang Li, et al.*2026 · 3 citations*
64. [**Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models arXiv:2605.11887**Boyi Deng, Xu Wang, Yaoning Wang, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/deng-2026-qwen-scope-turning-sparse/)
65. **[Skill Discovery for Software Scripting Automation via Offline Simulations with LLMs](https://md.research.elamur.ai/free/en/papers/xu-2026-skill-discovery-software-scripting-automation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Paiheng Xu, Gang Wu, Xiang Chen, et al.*2026 · 3 citations*
66. [**MiniMax Sparse Attention arXiv:2606.13392**Xunhao Lai, Weiqi Xu, Yufeng Yang, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/lai-2026-minimax-sparse-attention/)
67. **[CodeEvo: Interaction-Driven Synthesis of Code-centric Data through Hybrid and Iterative Feedback](https://md.research.elamur.ai/free/en/papers/sun-2026-codeevo-interaction-driven-synthesis-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qiushi Sun, Jingyang Gong, Lei Li, et al.*2026 · 1 citation*
68. **[Compatibility-Aware Dynamic Fine-Tuning for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2026-compatibility-aware-dynamic-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yucheng Zhou, Junwei Sheng, Qianning Wang, et al.*2026 · 1 citation*
69. **[ExecVerify: White-Box RL with Verifiable Stepwise Rewards for Code Execution Reasoning](https://md.research.elamur.ai/free/en/papers/tang-2026-execverify-white-box-rl-verifiable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingxiao Tang, He Ye, Zhaoyang Chu, et al.*2026 · 1 citation*
70. [**Hunyuan-A13B Technical Report arXiv:2609.27284**Tencent Hunyuan Team, Ao Liu, Botong Zhou, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/team-2026-hunyuan-hunyuan-a13b-technical-report/)
71. **[POSTCONDBENCH: Benchmarking Correctness and Completeness in Formal Postcondition Inference](https://md.research.elamur.ai/free/en/papers/zhang-2026-postcondbench-benchmarking-correctness-completeness-formal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gehao Zhang, Juan Zhai*2026 · 1 citation*
72. **[SWE-Mutation: Can LLMs Generate Reliable Test Suites in Software Engineering?](https://md.research.elamur.ai/free/en/papers/sun-2026-swe-mutation-can-llms-generate/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxuan Sun, Yuze Zhao, Yufeng Wang, et al.*2026 · 1 citation*
73. **[ARCHITECT: Uncertainty-Aware Dynamic Tool Learning via Causal Intervention for Open-World Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-architect-uncertainty-aware-dynamic-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhangyi Wang, Jiexiang Xu, Bingnan Yu, et al.*2026*
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75. **[CoDial: Interpretable Task-Oriented Dialogue Systems Through Dialogue Flow Alignment](https://md.research.elamur.ai/free/en/papers/shayanfar-2026-codial-interpretable-task-oriented-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Radin Shayanfar, Chu Fei Luo, Rohan V Bhambhoria, et al.*2026*
76. **[DynamixSFT: Dynamic Mixture Optimization of Instruction Tuning Collections](https://md.research.elamur.ai/free/en/papers/shin-2026-dynamixsft-dynamic-mixture-optimization-instruction/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haebin Shin, Lei Ji, Xiao Liu, et al.*2026*
77. **[LogicEval: A Systematic Framework for Evaluating Automated Repair Techniques for Logical Vulnerabilities in Real-World Software](https://md.research.elamur.ai/free/en/papers/rashid-2026-logiceval-systematic-framework-evaluating-automated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Syed Md Mukit Rashid, Abdullah Al Ishtiaq, Kai Tu, et al.*2026*
78. **[Mitigating Position Bias in Transformers via Layer-Specific Positional Embedding Scaling](https://md.research.elamur.ai/free/en/papers/wang-2026-mitigating-position-bias-transformers-layer/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenghua Wang, Yiran Ding, Changze Lv, et al.*2026*
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80. **[Student Guides Teacher: Weak-to-Strong Inference via Spectral Orthogonal Exploration](https://md.research.elamur.ai/free/en/papers/wang-2026-student-guides-teacher-weak-strong/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dayu Wang, Jiaye Yang, Weikang Li, et al.*2026*
81. **[ThinkBooster: A Unified Framework for Seamless Test-Time Scaling of LLM Reasoning](https://md.research.elamur.ai/free/en/papers/smirnov-2026-thinkbooster-unified-framework-seamless-test/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vladislav Smirnov, Quang-Chieu Nguyen, Sergey Senichev, et al.*2026*
82. **[Survey on Code Generation with LLM-based Agents (基于大语言模型智能体的代码生成综述)](https://md.research.elamur.ai/free/en/papers/dong-2025-code-generation-llm/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yihong Dong (董益宏), Xue Jiang (姜雪), Jiaru Qian (钱家如), et al.*2025*

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