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title: "Who cites Atlas: Few-shot — page 2 — 477 citing papers"
description: "477 papers of the Elamur Research library cite «Atlas: Few-shot Learning with Retrieval Augmented Language Models», found in their…"
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# Who cites «Atlas: Few-shot Learning with Retrieval Augmented Language Models»

477 papers of our library cite it (of the 149,439 whose bibliographies we read) · 133 with a page here, the most cited first · page 2 of 2 · 101–133 · [← back to «Atlas: Few-shot Learning with Retrieval Augmented Language Models»](https://md.research.elamur.ai/free/en/papers/izacard-2022-atlas-few-shot-learning-retrieval/)

[← prev](https://md.research.elamur.ai/free/en/papers/izacard-2022-atlas-few-shot-learning-retrieval/cited-by/) [1](https://md.research.elamur.ai/free/en/papers/izacard-2022-atlas-few-shot-learning-retrieval/cited-by/) **2**

101. **[Can LLMs Identify Critical Limitations within Scientific Research? A Systematic Evaluation on AI Research Papers](https://md.research.elamur.ai/free/en/papers/xu-2025-can-llms-identify-critical-limitations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhijian Xu, Yilun Zhao, Manasi Patwardhan, et al.*2025 · 11 citations*
102. **[RichRAG: Crafting Rich Responses for Multi-faceted Queries in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wang-2025-richrag-crafting-rich-responses-multi/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Shuting Wang, Xin Yu, Mang Wang, et al.*2025 · 10 citations*
103. **[BELLE: A Bi-Level Multi-Agent Reasoning Framework for Multi-Hop Question Answering](https://md.research.elamur.ai/free/en/papers/zhang-2025-belle-bi-level-multi-agent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taolin Zhang, Dongyang Li, Qizhou Chen, et al.*2025 · 9 citations*
104. [**You Don't Need Pre-built Graphs for RAG: Retrieval Augmented Generation with Adaptive Reasoning Structures arXiv:2508.06105**Shengyuan Chen, Chuang Zhou, Zheng Yuan, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-don-t-need-pre-built/)
105. **[Can LLMs Automate Fact-Checking Article Writing?](https://md.research.elamur.ai/free/en/papers/sahnan-2026-can-llms-automate-fact-checking/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Dhruv Sahnan, David Corney, Irene Larraz, et al.*2026 · 5 citations*
106. **[AutoGraph-R1: End-to-End Reinforcement Learning for Knowledge Graph Construction](https://md.research.elamur.ai/free/en/papers/tsang-2026-autograph-r1-end-end-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hong Ting Tsang, Jiaxin Bai, Haoyu Huang, et al.*2026 · 4 citations*
107. **[LVLM-Aware Multimodal Retrieval for RAG-Based Medical Diagnosis with General-Purpose Models](https://md.research.elamur.ai/free/en/papers/mazor-2026-lvlm-aware-multimodal-retrieval-rag/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nir Mazor, Tom Hope*2026 · 2 citations*
108. **[Knowing When Not to Answer: Lightweight KB-Aligned OOD Detection for Safe RAG](https://md.research.elamur.ai/free/en/papers/triantafyllopoulos-2026-knowing-when-not-answer-lightweight/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ilias Triantafyllopoulos, Renyi Qu, Salvatore Giorgi, et al.*2026 · 1 citation*
109. **[MEVER: Multi-Modal and Explainable Claim Verification with Graph-based Evidence Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2026-mever-multi-modal-explainable-claim/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Delvin Ce Zhang, Suhan Cui, Zhelin Chu, et al.*2026 · 1 citation*
110. **[PRISP: Privacy-Safe Few-Shot Personalization via Lightweight Adaptation](https://md.research.elamur.ai/free/en/papers/park-2026-prisp-privacy-safe-few-shot/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junho Park, Dohoon Kim, Taesup Moon*2026 · 1 citation*
111. **[RAGVUE: A Diagnostic View for Explainable and Automated Evaluation of Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/murugaraj-2026-ragvue-diagnostic-view-explainable-automated/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Keerthana Murugaraj, Salima Lamsiyah, Martin Theobald*2026 · 1 citation*
112. **[TAGS: A Test-Time Generalist–Specialist Framework with Retrieval-Augmented Reasoning and Verification](https://md.research.elamur.ai/free/en/papers/wu-2026-tags-test-time-generalist-specialist/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jianghao Wu, Feilong Tang, Yulong Li, et al.*2026 · 1 citation*
113. **[An Iterative Utility Judgment Framework Inspired by Philosophical Relevance via LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-iterative-utility-judgment-framework-inspired/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hengran Zhang, Keping Bi, Jiafeng Guo, et al.*2026*
114. **[Augmenting LLM Reasoning with Dynamic Notes Writing for Complex MultiHop QA](https://md.research.elamur.ai/free/en/papers/maheshwary-2026-augmenting-llm-reasoning-dynamic-notes/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Rishabh Maheshwary, Masoud Hashemi, Khyati Mahajan, et al.*2026*
115. **[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*
116. **[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*
117. **[CheckRLM: Effective Knowledge–Thought Coherence Checking in Retrieval-Augmented Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2026-checkrlm-effective-knowledge-thought-coherence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dingling Xu, Ruobing Wang, Qingfei Zhao, et al.*2026*
118. **[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*
119. **[EgoMemory: Memory-Augmented Personalized Retrieval for Long-Context Egocentric Video](https://md.research.elamur.ai/free/en/papers/tang-2026-egomemory-memory-augmented-personalized-retrieval/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanmin Tang, Jue Zhang, Xiaoting Qin, et al.*2026*
120. **[Frozen LLMs are Native Decoders for High-Norm Semantic Vectors](https://md.research.elamur.ai/free/en/papers/zeng-2026-frozen-llms-are-native-decoders/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yunsheng Zeng, Yongmei Tan*2026*
121. **[How to Make LMs Strong Node Classifiers?](https://md.research.elamur.ai/free/en/papers/xu-2026-how-make-lms-strong-node/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhe Xu, Kaveh Hassani, Si Zhang, et al.*2026*
122. **[Improving Retrieval-Augmented Generation without Taxonomy-based Error Categorization](https://md.research.elamur.ai/free/en/papers/zhang-2026-improving-retrieval-augmented-generation-without/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gongbo Zhang, Yifan Peng, Chunhua Weng*2026*
123. **[Learning to Extract Rational Evidence via Reinforcement Learning for Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhao-2026-learning-extract-rational-evidence-reinforcement/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinping Zhao, Shouzheng Huang, Yan Zhong, et al.*2026*
124. **[LOKA: Conflict-Aware LLM Knowledge Update with Adaptive Knowledge Memory](https://md.research.elamur.ai/free/en/papers/zhang-2026-loka-conflict-aware-llm-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Binchi Zhang, Zhengzhang Chen, Zaiyi Zheng, et al.*2026*
125. **[LongTailQA: Benchmarking LLMs and RAG Models on Disambiguated Long-Tail Entities](https://md.research.elamur.ai/free/en/papers/xion-2026-longtailqa-benchmarking-llms-rag-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**William Xion, Uwe Hadler, Tim Cofala, et al.*2026*
126. **[MASS-RAG: Multi-Agent Synthesis Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/xiao-2026-mass-rag-multi-agent-synthesis/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xingchen Xiao, Heyan Huang, Runheng Liu, et al.*2026*
127. **[MATCH: Modulating Attention via In-Context Retrieval for Long-Context Transformers](https://md.research.elamur.ai/free/en/papers/ma-2026-match-modulating-attention-context-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linrui Ma, Chun Hei Lo, Xinyu Wang, et al.*2026*
128. **[Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wu-2026-optimizing-rag-rerankers-llm-feedback/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuhang Wu, Xiangqing Shen, Fanfan Wang, et al.*2026*
129. **[Pushing the Frontiers of Scientific Fact-Checking: The SCINLP Dataset](https://md.research.elamur.ai/free/en/papers/maab-2026-pushing-frontiers-scientific-fact-checking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Iffat Maab, Junichi Yamagishi*2026*
130. **[Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data](https://md.research.elamur.ai/free/en/papers/yang-2026-quantifying-improving-robustness-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shiping Yang, Jie Wu, Wenbiao Ding, et al.*2026*
131. **[RAG in the Wild: On the (In)effectiveness of LLMs with Mixture-of-Knowledge Retrieval Augmentation](https://md.research.elamur.ai/free/en/papers/xu-2026-rag-wild-effectiveness-llms-mixture/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ran Xu, Yuchen Zhuang, Yue Yu, et al.*2026*
132. **[The Retrieval Bottleneck: Scaling Laws for Reinforcement Learning in RAG](https://md.research.elamur.ai/free/en/papers/zhou-2026-retrieval-bottleneck-scaling-laws-reinforcement/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shu Zhou, Jinman Leng, Yufei Song, et al.*2026*
133. **[Think Parallax: Solving Multi-Hop Problems via Multi-View Knowledge-Graph-Based Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/liu-2026-think-parallax-solving-multi-hop/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinliang Liu, Jiale Bai, Shaoning Zeng*2026*

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344 more papers of our library cite it; they have no page here yet.

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