--- title: "Who cites Xingchen Wan — 58 papers of our library" description: "58 papers of the Elamur Research library cite the works of Xingchen Wan, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/xingchen-wan/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/xingchen-wan/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Xingchen Wan](https://md.research.elamur.ai/free/en/authors/xingchen-wan/) / cited by # Who cites Xingchen Wan 58 citations of their works from 58 papers of our library (of the 149,439 whose bibliographies we read) · 18 with a page here, the most cited first · [← Xingchen Wan](https://md.research.elamur.ai/free/en/authors/xingchen-wan/) 1. [**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/) 2. [**Retrieval-Augmented Generation with Graphs (GraphRAG) arXiv:2501.00309**Haoyu Han, Yu Wang, Harry Shomer, et al.*2025 · 87 citations*](https://md.research.elamur.ai/free/en/papers/han-2025-retrieval-augmented-generation-graphs-graphrag/) 3. [**Aligning with Human Judgement: The Role of Pairwise Preference in Large Language Model Evaluators arXiv:2403.16950**Yinhong Liu, Han Zhou, Zhijiang Guo, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-aligning-human-judgement-role-pairwise/) 4. **[RAG-Star: Enhancing Deliberative Reasoning with Retrieval Augmented Verification and Refinement](https://md.research.elamur.ai/free/en/papers/jiang-2025-rag-star-enhancing-deliberative-reasoning/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jinhao Jiang, Jiayi Chen, Junyi Li, et al.*2025 · 31 citations* 5. **[Revealing and Enhancing Core Visual Regions: Harnessing Internal Attention Dynamics for Hallucination Mitigation in LVLMs](https://md.research.elamur.ai/free/en/papers/lyu-2026-revealing-enhancing-core-visual-regions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangtao Lyu, Qi Liu, Chenghao Xu, et al.*2026 · 5 citations* 6. **[Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach](https://md.research.elamur.ai/free/en/papers/zeng-2025-context-robust-llms-gated-representation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shenglai Zeng, Pengfei He, Kai Guo, et al.*2025 · 5 citations* 7. **[Self-Evolving Multi-Agent Systems via Textual Backpropagation](https://md.research.elamur.ai/free/en/papers/ma-2026-self-evolving-multi-agent-systems/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaowen Ma, Yunpu Ma, Chenyang Lin, et al.*2026 · 3 citations* 8. **[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* 9. **[ThinkNote: Enhancing Knowledge Integration and Utilization of Large Language Models via Constructivist Cognition Modeling](https://md.research.elamur.ai/free/en/papers/xu-2026-thinknote-enhancing-knowledge-integration-utilization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhipeng Xu, Zhenghao Liu, Yukun Yan, et al.*2026 · 2 citations* 10. **[Context-attended Adversarial Reinforcement Learning for Robust Multi-step Retrieval Augmented Generation](https://md.research.elamur.ai/free/en/papers/ren-2026-context-attended-adversarial-reinforcement-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yingtao Ren, Xiao Luo, Yu-Cheng Chang, et al.*2026 · 1 citation* 11. **[TempPerturb-Eval: On the Joint Effects of Internal Temperature and External Perturbations in RAG Robustness](https://md.research.elamur.ai/free/en/papers/zhou-2026-tempperturb-eval-joint-effects-internal/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yongxin Zhou, Philippe Mulhem, Didier Schwab*2026 · 1 citation* 12. [**A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战) Acta Automatica Sinica (自动化学报)**Anda Tang (唐岸达), Zhouchen Lin (林宙辰)*2026*](https://md.research.elamur.ai/free/en/papers/tang-2026-parameter-efficient-fine/) 13. **[AED-RAG: Continuous Multi-Granular Context Fusion for Retrieval-Augmented Generation via Adaptive Ensemble Decoding](https://md.research.elamur.ai/free/en/papers/zhou-2026-aed-rag-continuous-multi-granular/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junzhe Zhou, Fulin Lin, Tairan Cheng, et al.*2026* 14. **[Conjecture and Inquiry: Quantifying Software Performance Requirements via Interactive Retrieval-Augmented Preference Elicitation](https://md.research.elamur.ai/free/en/papers/wang-2026-conjecture-inquiry-quantifying-software-performance/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shihai Wang, Tao Chen*2026* 15. **[Dissecting GraphRAG: A Modular Analysis of Knowledge Structuring for Factoid Question Answering](https://md.research.elamur.ai/free/en/papers/nishida-2026-dissecting-graphrag-modular-analysis-knowledge/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Noriki Nishida, Rumana Ferdous Munne, Shanshan Liu, et al.*2026* 16. **[PRA-RAG: Provably Robust Aggregation in Retrieval-Augmented Generation against Retrieval Corruption](https://md.research.elamur.ai/free/en/papers/tan-2026-pra-rag-provably-robust-aggregation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xue Tan, Yi Zheng, Chang Huo, et al.*2026* 17. **[Training-Free Test-Time Contrastive Learning for Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-training-free-test-time-contrastive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaiwen Zheng, Kai Zhou, Jinwu Hu, et al.*2026* 18. **[When Facts Change: Temporal Knowledge Conflict Resolution in LLMs](https://md.research.elamur.ai/free/en/papers/wallat-2026-when-facts-change-temporal-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jonas Wallat, Wolfgang Nejdl, Sandipan Sikdar*2026* 40 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/xingchen-wan/) — Xingchen Wan