🧑‍🔬 Who cites Yifan Wang

47 citations of their works from 47 papers of our library (of the 149,439 whose bibliographies we read) · 16 with a page here, the most cited first · ← Yifan Wang

1. Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language ModelsComputational LinguisticsYue Zhang, Yafu Li, Leyang Cui, et al.2023 · 977 citations
2. EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt OptimizersarXiv:2309.08532Qingyan Guo, Rui Wang, Junliang Guo, et al.2023 · 111 citations
3. A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and RecommendationsConference on Empirical Methods in Natural Language Processing (EMNLP)Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.2024 · 105 citations
4. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
5. Decoding Decoded: Understanding Hyperparameter Effects in Open-Ended Text GenerationInternational Conference on Computational Linguistics (COLING)Esteban Garces Arias, Meimingwei Li, Christian Heumann, et al.2025 · 12 citations
6. MorphMark: Flexible Adaptive Watermarking for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zongqi Wang, Tianle Gu, Baoyuan Wu, et al.2025 · 12 citations
7. Balancing Diversity and Risk in LLM Sampling: How to Select Your Method and Parameter for Open-Ended Text GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Yuxuan Zhou, Margret Keuper, Mario Fritz2025 · 11 citations
8. When Life Gives You Samples: The Benefits of Scaling up Inference Compute for Multilingual LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Ammar Khairi, Daniel D'souza, Ye Shen, et al.2025 · 6 citations
9. CoAct: Co-Active LLM Preference Learning with Human-AI SynergyAnnual Meeting of the Association for Computational Linguistics (ACL)Ruiyao Xu, Mihir Parmar, Tiankai Yang, et al.2026 · 1 citation
10. Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement LearningFindings of the Association for Computational LinguisticsZhiyin Yu, Bo Zhang, Qibin Hou, et al.2026 · 1 citation
11. A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and SolutionsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.2026
12. Calibrating Inference Time Alignment with Sequence-level Risk AccumulationAnnual Meeting of the Association for Computational Linguistics (ACL)Shanwen Tan, Ziyang Dong, Wei Ju, et al.2026
13. C³D: Enhancing LLM Reasoning via Confidence-Guided Contrastive DecodingFindings of the Association for Computational LinguisticsYufeng Zhang, Xuepeng Wang, Lingxiang Wu, et al.2026
14. DANCE: Diversity-attended Dynamic Caching with Asymmetric Quantization for Test-time Adaptation of Vision-Language ModelsFindings of the Association for Computational LinguisticsShunge Zou, Changhu Wang, Wei Ju, et al.2026
15. Parallel Test-Time Scaling for Latent Reasoning ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Runyang You, Yongqi Li, Meng Liu, et al.2026
16. SciPedia: Unlocking the Value of Scientific Data for Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Yiwei Qin, Zhen Huang, Tiantian Mi, et al.2026

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