---
title: "Who cites Retrieval as Generation: A Unified — 8 citing papers"
description: "8 papers of the Elamur Research library cite «Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning», found…"
canonical: "https://research.elamur.ai/free/en/papers/li-2026-retrieval-as-generation-unified-framework/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Retrieval as Generation: A Unified Framework with…](https://md.research.elamur.ai/free/en/papers/li-2026-retrieval-as-generation-unified-framework/) / cited by

# Who cites «Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning»

8 papers of our library cite it (of the 149,439 whose bibliographies we read) · 8 with a page here, the most cited first · [← back to «Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning»](https://md.research.elamur.ai/free/en/papers/li-2026-retrieval-as-generation-unified-framework/)

1. **[Stable-RAG: Mitigating Retrieval-Permutation-Induced Hallucinations in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhang-2026-stable-rag-mitigating-retrieval-permutation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qianchi Zhang, Hainan Zhang, Liang Pang, et al.*2026 · 27 citations*
2. **[Self-Correcting RAG: Enhancing Faithfulness via MMKP Context Selection and NLI-Guided MCTS](https://md.research.elamur.ai/free/en/papers/xu-2026-self-correcting-rag-enhancing-faithfulness/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shijia Xu, Zhou Wu, Xiaolong Jia, et al.*2026 · 15 citations*
3. **[RCBSF: A Multi-Agent Framework for Automated Contract Revision via Stackelberg Game](https://md.research.elamur.ai/free/en/papers/xu-2026-rcbsf-multi-agent-framework-automated/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shijia Xu, Yu Wang, Xiaolong Jia, et al.*2026 · 11 citations*
4. **[FinCARDS: Card-Based Analyst Reranking for Financial Document Question Answering](https://md.research.elamur.ai/free/en/papers/zhou-2026-fincards-card-based-analyst-reranking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yixi Zhou, Fan Zhang, YU Chen, et al.*2026 · 8 citations*
5. **[Dissecting Failure Dynamics in Large Language Model Reasoning](https://md.research.elamur.ai/free/en/papers/zhu-2026-dissecting-failure-dynamics-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Zhu, Jian Zhang, Lixing Yu, et al.*2026 · 6 citations*
6. **[BubbleRAG: Interactive Cognitive Offloading with Thought Bubble in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/ye-2026-bubblerag-interactive-cognitive-offloading-thought/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Fuda Ye, Jiachuan Wang, Yongqi Zhang, et al.*2026*
7. **[Chart-MRAG: Benchmarking Multimodal Retrieval Augmented Generation on Chart-based Documents](https://md.research.elamur.ai/free/en/papers/ymyang-2026-chart-mrag-benchmarking-multimodal-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ymyang, Jiang Zhong, Li Jin, et al.*2026*
8. **[Subgraph-Guided Executable Logical Form Generation for Knowledge Base Question Answering](https://md.research.elamur.ai/free/en/papers/tian-2026-subgraph-guided-executable-logical-form/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuhang Tian, Dandan Song, Zhijing Wu, et al.*2026*
- [← back to](https://md.research.elamur.ai/free/en/papers/li-2026-retrieval-as-generation-unified-framework/) — Retrieval as Generation: A Unified Framework with Self-Triggered Information Planning
