🧑‍🔬 Who cites Yanda Meng

120 citations of their works from 112 papers of our library (of the 149,439 whose bibliographies we read) · 37 with a page here, the most cited first · ← Yanda Meng

1. Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mosh Levy, Alon Jacoby, Yoav Goldberg2024 · 217 citations
2. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
3. Stop Overthinking: A Survey on Efficient Reasoning for Large Language ModelsarXiv:2503.16419Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.2025 · 157 citations
4. Token-Budget-Aware LLM ReasoningarXiv:2412.18547Tingxu Han, Zhenting Wang, Chunrong Fang, et al.2024 · 136 citations
5. TokenSkip: Controllable Chain-of-Thought Compression in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Heming Xia, Chak Tou Leong, Wenjie Wang, et al.2025 · 106 citations
6. Multi-Step Reasoning with Large Language Models, a SurveyACM Computing SurveysAske Plaat, Annie Wong, Suzan Verberne, et al.2024 · 106 citations
7. A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?arXiv:2503.24235Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.2025 · 79 citations
8. Training Language Models to Reason EfficientlyConference on Neural Information Processing Systems (NeurIPS)Daman Arora, Andrea Zanette2025 · 74 citations
9. When More is Less: Understanding Chain-of-Thought Length in LLMsarXiv:2502.07266Yuyang Wu, Yifei Wang, Ziyu Ye, et al.2025 · 73 citations
10. C3oT: Generating Shorter Chain-of-Thought without Compromising EffectivenessProceedings of the AAAI Conference on Artificial IntelligenceYu Kang, Xianghui Sun, Liangyu Chen, et al.2024 · 66 citations
11. CoT-Valve: Length-Compressible Chain-of-Thought TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Xinyin Ma, Guangnian Wan, Runpeng Yu, et al.2025 · 64 citations
12. A Peek into Token Bias: Large Language Models Are Not Yet Genuine ReasonersConference on Empirical Methods in Natural Language Processing (EMNLP)Bowen Jiang, Yangxinyu Xie, Zhuoqun Hao, et al.2024 · 64 citations
13. A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and BeyondarXiv:2503.21614Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.2025 · 55 citations
14. Disentangling Memory and Reasoning Ability in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mingyu Jin, Weidi Luo, Sitao Cheng, et al.2025 · 45 citations
15. Efficient Reasoning Models: A SurveyarXiv:2504.10903Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.2025 · 37 citations
16. Exploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?International Conference on Computational Linguistics (COLING)Mingyu Jin, Qinkai Yu, Jingyuan Huang, et al.2025 · 36 citations
17. Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM SamplingConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Guangya Wan, Yuqi Wu, Jie Chen, et al.2025 · 29 citations
18. How Likely Do LLMs with CoT Mimic Human Reasoning?International Conference on Computational Linguistics (COLING)Guangsheng Bao, Hongbo Zhang, Cunxiang Wang, et al.2025 · 22 citations
19. AGrail: A Lifelong Agent Guardrail with Effective and Adaptive Safety DetectionAnnual Meeting of the Association for Computational Linguistics (ACL)Weidi Luo, Shenghong Dai, Xiaogeng Liu, et al.2025 · 20 citations
20. Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language ModelsarXiv:2503.24377Rui Wang, Hongru Wang, Boyang Xue, et al.2025 · 16 citations
21. Measuring Chain of Thought Faithfulness by Unlearning Reasoning StepsConference on Empirical Methods in Natural Language Processing (EMNLP)Martin Tutek, Fateme Hashemi Chaleshtori, Ana Marasovic, et al.2025 · 15 citations
22. NeuReasoner: Towards Explainable, Controllable, and Unified Reasoning via Mixture-of-NeuronsAnnual Meeting of the Association for Computational Linguistics (ACL)Haonan Dong, Kehan Jiang, Haoran Ye, et al.2026 · 13 citations
23. What Makes a Good Reasoning Chain? Uncovering Structural Patterns in Long Chain-of-Thought ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Gangwei Jiang, Yahui Liu, Zhaoyi Li, et al.2025 · 11 citations
24. RoT: Enhancing Table Reasoning with Iterative Row-Wise TraversalsConference on Empirical Methods in Natural Language Processing (EMNLP)Xuanliang Zhang, Dingzirui Wang, Keyan Xu, et al.2025 · 10 citations
25. Token Prepending: A Training-Free Approach for Eliciting Better Sentence Embeddings from LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuchen Fu, Zifeng Cheng, Zhiwei Jiang, et al.2025 · 10 citations
26. Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language ModelsFindings of the Association for Computational LinguisticsHengyuan Zhang, Zhihao Zhang, Ercong Nie, et al.2026 · 9 citations
27. GMSA: Enhancing Context Compression via Group Merging and Layer Semantic AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Jiwei Tang, Zhicheng Zhang, Shunlong Wu, et al.2026 · 8 citations
28. Enhancing Auto-regressive Chain-of-Thought through Loop-Aligned ReasoningConference of the European Chapter of the Association for Computational Linguistics (EACL)Qifan Yu, Zhenyu He, Sijie Li, et al.2026 · 5 citations
29. Do LLMs Really Need 10+ Thoughts for “Find the Time 1000 Days Later”? Towards Structural Understanding of LLM OverthinkingAnnual Meeting of the Association for Computational Linguistics (ACL)Xinliang Frederick Zhang, Anhad Mohananey, Alexandra Chronopoulou, et al.2026 · 4 citations
30. On the Step Length Confounding in LLM Reasoning Data SelectionFindings of the Association for Computational LinguisticsBing Wang, Rui Miao, Chen Shen, et al.2026 · 1 citation
31. AdapThink: Adaptive Thinking Preferences for Reasoning Language ModelsFindings of the Association for Computational LinguisticsWenyue Xu, Xu Wan, Wei Wang, et al.2026
32. Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language ModelsFindings of the Association for Computational LinguisticsXudong Wang, Chaoning Zhang, Chenghao Li, et al.2026
33. GraphLoRA: Structure-Aware Low-Rank Adaptation for Large Language Model RecommendationFindings of the Association for Computational LinguisticsLin Mu, Guoji Wang, Li Ni, et al.2026
34. How Do LLMs Generate Contrastive Sentiments? A Mechanistic PerspectiveConference of the European Chapter of the Association for Computational Linguistics (EACL)Van Bach Nguyen, Jörg Schlötterer, Christin Seifert2026
35. How Retrieved Context Shapes Internal Representations in RAGFindings of the Association for Computational LinguisticsSamuel Yeh, Sharon Li2026
36. Layer-aware Dual-directional Modulation for Low-resource Machine TranslationFindings of the Association for Computational LinguisticsSiqi Zhang, Ran Song, Shuting Jiang, et al.2026
37. Learning Uncertainty from Sequential Internal Dispersion in Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Ponhvoan Srey, Xiaobao Wu, Cong-Duy T Nguyen, et al.2026

75 more citing papers of our library have no page here yet.

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/yanda-meng/cited-by/