---
title: "Who cites Jacob Kahn — 213 papers of our library"
description: "213 papers of the Elamur Research library cite the works of Jacob Kahn, found in their bibliographies; the most cited first."
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---
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# Who cites Jacob Kahn

213 citations of their works from 213 papers of our library (of the 149,439 whose bibliographies we read) · 49 with a page here, the most cited first · [← Jacob Kahn](https://md.research.elamur.ai/free/en/authors/jacob-kahn/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
2. [**Retrieval-Augmented Generation for Large Language Models: A Survey arXiv:2312.10997**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,663 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/)
3. **[A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models](https://md.research.elamur.ai/free/en/papers/fan-2024-survey-rag-meeting-llms-towards/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Wenqi Fan; Yujuan Ding; Liangbo Ning; Shijie Wang; Hengyun Li; Dawei Yin; Tat-Seng Chua;, Qing Li*2024 · 1,010 citations*
4. [**Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection arXiv:2310.11511**Akari Asai, Zeqiu Wu, Yizhong Wang, et al.*2023 · 677 citations*](https://md.research.elamur.ai/free/en/papers/asai-2023-self-rag-learning-retrieve-generate/)
5. **[Large Language Models for Information Retrieval: A Survey](https://md.research.elamur.ai/free/en/papers/zhu-2023-large-language-models-information-retrieval/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Yutao Zhu; Huaying Yuan; Shuting Wang; Jiongnan Liu; Wenhan Liu; Chenlong Deng; Haonan Chen; Zheng Liu; Zhicheng Dou;, Ji-Rong Wen*2023 · 339 citations*
6. [**Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning arXiv:2503.09516**Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.*2025 · 322 citations*](https://md.research.elamur.ai/free/en/papers/jin-2025-search-r1-training-llms-reason/)
7. **[A-MEM: Agentic Memory for LLM Agents](https://md.research.elamur.ai/free/en/papers/xu-2025-mem-agentic-memory-llm-agents/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wujiang Xu, Zujie Liang, Kai Mei, et al.*2025 · 178 citations*
8. [**Generative Representational Instruction Tuning arXiv:2402.09906**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 172 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
9. **[Searching for Best Practices in Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wang-2024-searching-best-practices-retrieval-augmented/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaohua Wang, Zhenghua Wang, Xuan Gao, et al.*2024 · 150 citations*
10. **[Self Forcing: Bridging the Train-Test Gap in Autoregressive Video Diffusion](https://md.research.elamur.ai/free/en/papers/huang-2025-self-forcing-bridging-train-test/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xun Huang, Zhengqi Li, Guande He, et al.*2025 · 146 citations*
11. [**RAFT: Adapting Language Model to Domain Specific RAG arXiv:2403.10131**Tianjun Zhang, Shishir G. Patil, Naman Jain, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-raft-adapting-language-model-domain/)
12. [**Hallucination of Multimodal Large Language Models: A Survey arXiv:2404.18930**Zechen Bai, Pichao Wang, Tianjun Xiao, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-hallucination-multimodal-large-language-models/)
13. [**Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling arXiv:2501.17811**Xiaokang Chen, Zhiyu Wu, Xingchao Liu, et al.*2025 · 112 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-janus-pro-unified-multimodal/)
14. **[Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and Generation](https://md.research.elamur.ai/free/en/papers/wu-2024-janus-decoupling-visual-encoding/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Chengyue Wu, Xiaokang Chen, Zhiyu Wu, et al.*2024 · 112 citations*
15. **[Large Language Model Instruction Following: A Survey of Progresses and Challenges](https://md.research.elamur.ai/free/en/papers/lou-2024-large-language-model-instruction-following/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Renze Lou, Kai Zhang, Wenpeng Yin*2024 · 83 citations*
16. **[Enhancing Noise Robustness of Retrieval-Augmented Language Models with Adaptive Adversarial Training](https://md.research.elamur.ai/free/en/papers/fang-2024-enhancing-noise-robustness-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Feiteng Fang, Yuelin Bai, Shiwen Ni, et al.*2024 · 75 citations*
17. [**In-context Pretraining: Language Modeling Beyond Document Boundaries arXiv:2310.10638**Weijia Shi, Sewon Min, Maria Lomeli, et al.*2023 · 61 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-context-pretraining-language-modeling-document/)
18. **[ChatQA: Surpassing GPT-4 on Conversational QA and RAG](https://md.research.elamur.ai/free/en/papers/liu-2024-chatqa-surpassing-gpt-4-conversational/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zihan Liu, Wei Ping, Rajarshi Roy, et al.*2024 · 58 citations*
19. **[REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2024-rear-relevance-aware-retrieval-augmented/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuhao Wang, Ruiyang Ren, Junyi Li, et al.*2024 · 55 citations*
20. **[JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ma-2024-janusflow-harmonizing-autoregression-rectified/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Yiyang Ma, Xingchao Liu, Xiaokang Chen, et al.*2024 · 52 citations*
21. **[Long-Context Language Modeling with Parallel Context Encoding](https://md.research.elamur.ai/free/en/papers/yen-2024-long-context-language-modeling-parallel/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Howard Yen, Tianyu Gao, Danqi Chen*2024 · 44 citations*
22. **[Personalized Generation In Large Model Era: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2025-personalized-generation-large-model-era/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiyan Xu, Jinghao Zhang, Alireza Salemi, et al.*2025 · 24 citations*
23. **[The Distracting Effect: Understanding Irrelevant Passages in RAG](https://md.research.elamur.ai/free/en/papers/amiraz-2025-distracting-effect-understanding-irrelevant-passages/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chen Amiraz, Florin Cuconasu, Simone Filice, et al.*2025 · 21 citations*
24. [**MindSearch: Mimicking Human Minds Elicits Deep AI Searcher arXiv:2407.20183**Zehui Chen, Kuikun Liu, Qiuchen Wang, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-mindsearch-mimicking-human-minds-elicits/)
25. **[RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions](https://md.research.elamur.ai/free/en/papers/liu-2025-rag-instruct-boosting-llms-diverse/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wanlong Liu, Junying Chen, Ke Ji, et al.*2025 · 19 citations*
26. [**HunyuanImage 3.0 Technical Report arXiv:2509.23951**Tencent Hunyuan Foundation Model Team*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-hunyuan-hunyuanimage-3-0-technical/)
27. [**Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs arXiv:2507.09477**Yangning Li, Weizhi Zhang, Yuyao Yang, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-towards-agentic-rag-deep-reasoning/)
28. [**MA-RAG: Multi-Agent Retrieval-Augmented Generation via Collaborative Chain-of-Thought Reasoning arXiv:2505.20096**Thang Nguyen, Peter Chin, Yu-Wing Tai*2025 · 14 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2025-ma-rag-multi-agent-retrieval/)
29. **[s3: You Don't Need That Much Data to Train a Search Agent via RL](https://md.research.elamur.ai/free/en/papers/jiang-2025-s3-you-don-t-need/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Pengcheng Jiang, Xueqiang Xu, Jiacheng Lin, et al.*2025 · 12 citations*
30. **[UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervision](https://md.research.elamur.ai/free/en/papers/fang-2026-unicorn-self-improving-unified-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Fang, Ruiyan Han, XinYu Sun, et al.*2026 · 11 citations*
31. **[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*
32. **[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*
33. **[Redefining Retrieval Evaluation in the Era of LLMs](https://md.research.elamur.ai/free/en/papers/trappolini-2026-redefining-retrieval-evaluation-era-llms/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Giovanni Trappolini, Florin Cuconasu, Simone Filice, et al.*2026 · 1 citation*
34. **[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*
35. **[AMATA: Adaptive Multi-Agent Trajectory Alignment for Knowledge-Intensive Question Answering](https://md.research.elamur.ai/free/en/papers/zhang-2026-amata-adaptive-multi-agent-trajectory/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taolin Zhang, Dongyang Li, Chen Chen, et al.*2026*
36. **[CIRAG: Construction–Integration Retrieval and Adaptive Generation for Multi-hop Question Answering](https://md.research.elamur.ai/free/en/papers/wei-2026-cirag-construction-integration-retrieval-adaptive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zili Wei, Yilin Wang, Xiaocui Yang, et al.*2026*
37. **[Dynamic Graph Navigation via Triplet Chains for Structure-Aware Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhao-2026-dynamic-graph-navigation-triplet-chains/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Feng Zhao, Yufei Wu, Xianggan Liu, et al.*2026*
38. **[Efficient Prior-Guided Reasoning for Robust Retrieval-Augmented Generation under Conflicts](https://md.research.elamur.ai/free/en/papers/yuan-2026-efficient-prior-guided-reasoning-robust/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaowei Yuan, Ziyang Huang, Zhao Yang, et al.*2026*
39. **[Eval-RAR: Evaluation-Driven Retrieval-Augmented Reasoning via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/yu-2026-eval-rar-evaluation-driven-retrieval/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Heng Yu, Rui Li, Qi Liu, et al.*2026*
40. **[FactVerse: A Benchmark for Factual Consistency in Interleaved Image–Text Generation](https://md.research.elamur.ai/free/en/papers/shan-2026-factverse-benchmark-factual-consistency-interleaved/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yubo Shan, Kun Zhang, Qiming Xu, et al.*2026*
41. **[MAB-DQA: Addressing Query Aspect Importance in Document Question Answering with Multi-Armed Bandits](https://md.research.elamur.ai/free/en/papers/xiang-2026-mab-dqa-addressing-query-aspect/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Xiang, Yunshan Ma, Xiaoyu Du, et al.*2026*
42. **[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*
43. **[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*
44. **[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*
45. **[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*
46. **[Structured Dialogue Refinement: Building Retrieval-Augmented Question Answering on Goal-Oriented Dialogues](https://md.research.elamur.ai/free/en/papers/wu-2026-structured-dialogue-refinement-building-retrieval/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bin Wu, Sawan Kumar, Prasetya Ajie Utama, et al.*2026*
47. **[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*
48. **[Towards Unified Multimodal Large Language Models: A survey](https://md.research.elamur.ai/free/en/papers/ma-2026-unified-multimodal-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Ma, Yitian Zhang, Yun Fu*2026*
49. **[UniCM: A Unified Consistency Model For Efficient Multimodal Generation and Understanding](https://md.research.elamur.ai/free/en/papers/xu-2026-unicm-unified-consistency-model-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenkai Xu, Xu Wang, Zhenyi Liao, et al.*2026*

164 more citing papers of our library have no page here yet.

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