--- title: "Who cites Astute RAG: Overcoming — 35 citing papers" description: "35 papers of the Elamur Research library cite «Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for…" canonical: "https://research.elamur.ai/free/en/papers/wang-2025-astute-rag-overcoming-imperfect-retrieval/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/wang-2025-astute-rag-overcoming-imperfect-retrieval/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Astute RAG: Overcoming Imperfect Retrieval…](https://md.research.elamur.ai/free/en/papers/wang-2025-astute-rag-overcoming-imperfect-retrieval/) / cited by # Who cites «Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models» 35 papers of our library cite it (of the 149,439 whose bibliographies we read) · 15 with a page here, the most cited first · [← back to «Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models»](https://md.research.elamur.ai/free/en/papers/wang-2025-astute-rag-overcoming-imperfect-retrieval/) 1. [**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/) 2. **[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* 3. **[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* 4. **[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* 5. **[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* 6. **[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* 7. **[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* 8. **[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* 9. **[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* 10. **[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* 11. **[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* 12. **[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* 13. **[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* 14. **[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* 15. **[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* 20 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/wang-2025-astute-rag-overcoming-imperfect-retrieval/) — Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models