---
title: "Who cites Dor Muhlgay — 438 papers of our library"
description: "438 papers of the Elamur Research library cite the works of Dor Muhlgay, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Dor Muhlgay

443 citations of their works from 438 papers of our library (of the 149,439 whose bibliographies we read) · 132 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Dor Muhlgay](https://md.research.elamur.ai/free/en/authors/dor-muhlgay/)

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1. **[Survey of Hallucination in Natural Language Generation](https://md.research.elamur.ai/free/en/papers/ji-2022-survey-hallucination-natural-language-generation/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Ziwei Ji, Nayeon Lee, Rita Frieske, et al.*2022 · 5,974 citations*
2. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
3. **[Lost in the Middle: How Language Models Use Long Contexts](https://md.research.elamur.ai/free/en/papers/liu-2023-lost-middle-language-models-use/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nelson F. Liu, Kevin Lin, John Hewitt, et al.*2023 · 2,584 citations*
4. [**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/)
5. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
6. **[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*
7. [**A Survey on In-context Learning arXiv:2301.00234**Qingxiu Dong, Lei Li, Damai Dai, et al.*2023 · 978 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-survey-context-learning/)
8. **[Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2023-siren-s-song-ai-ocean/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Yue Zhang, Yafu Li, Leyang Cui, et al.*2023 · 977 citations*
9. **[Active Retrieval Augmented Generation](https://md.research.elamur.ai/free/en/papers/jiang-2023-active-retrieval-augmented-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhengbao Jiang, Frank Xu, Luyu Gao, et al.*2023 · 872 citations*
10. **[In-Context Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/ram-2023-context-retrieval-augmented-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ori Ram, Yoav Levine, Itay Dalmedigos, et al.*2023 · 793 citations*
11. [**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/)
12. [**Unleashing the potential of prompt engineering for large language models arXiv:2310.14735 · Patterns 6(6) 101,260 (2025)**Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.*2023 · 536 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-unleashing-potential-prompt-engineering-large/)
13. [**Large Legal Fictions: Profiling Legal Hallucinations in Large Language Models arXiv:2401.01301 · Journal of Legal Analysis 16, no. 1 (2024): 64-93**Matthew Dahl, Varun Magesh, Mirac Suzgun, et al.*2024 · 437 citations*](https://md.research.elamur.ai/free/en/papers/dahl-2024-large-legal-fictions-profiling-legal/)
14. **[Benchmarking Retrieval-Augmented Generation for Medicine](https://md.research.elamur.ai/free/en/papers/xiong-2024-benchmarking-retrieval-augmented-generation-medicine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guangzhi Xiong, Qiao Jin, Zhiyong Lu, et al.*2024 · 430 citations*
15. [**Towards General Text Embeddings with Multi-stage Contrastive Learning arXiv:2308.03281**Zehan Li, Xin Zhang, Yanzhao Zhang, et al.*2023 · 384 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-towards-general-text-embeddings-multi/)
16. **[Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity](https://md.research.elamur.ai/free/en/papers/jeong-2024-adaptive-rag-learning-adapt-retrieval/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Soyeong Jeong, Jinheon Baek, Sukmin Cho, et al.*2024 · 382 citations*
17. **[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*
18. [**LightRAG: Simple and Fast Retrieval-Augmented Generation arXiv:2410.05779**Zirui Guo, Lianghao Xia, Yanhua Yu, et al.*2024 · 316 citations*](https://md.research.elamur.ai/free/en/papers/guo-2024-lightrag-simple-fast-retrieval-augmented/)
19. **[The Power of Noise: Redefining Retrieval for RAG Systems](https://md.research.elamur.ai/free/en/papers/cuconasu-2024-power-noise-redefining-retrieval-rag/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Florin Cuconasu, Giovanni Trappolini, Federico Siciliano, et al.*2024 · 312 citations*
20. [**Retrieval-Augmented Generation for AI-Generated Content: A Survey arXiv:2402.19473**Penghao Zhao, Hailin Zhang, Qinhan Yu, et al.*2024 · 301 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-retrieval-augmented-generation-ai-generated/)
21. [**Ragas: Automated Evaluation of Retrieval Augmented Generation arXiv:2309.15217**Shahul Es, Jithin James, Luis Espinosa-Anke, et al.*2023 · 283 citations*](https://md.research.elamur.ai/free/en/papers/es-2023-ragas-automated-evaluation-retrieval-augmented/)
22. [**Corrective Retrieval Augmented Generation arXiv:2401.15884**Shi-Qi Yan, Jia-Chen Gu, Yun Zhu, et al.*2024 · 273 citations*](https://md.research.elamur.ai/free/en/papers/yan-2024-corrective-retrieval-augmented-generation/)
23. [**DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models arXiv:2309.03883**Yung-Sung Chuang, Yujia Xie, Hongyin Luo, et al.*2023 · 269 citations*](https://md.research.elamur.ai/free/en/papers/chuang-2023-dola-decoding-contrasting-layers-improves/)
24. **[HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models](https://md.research.elamur.ai/free/en/papers/gutierrez-2024-hipporag-neurobiologically-inspired-long-term/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, et al.*2024 · 268 citations*
25. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
26. **[Combating Misinformation in the Age of LLMs: Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/chen-2023-combating-misinformation-age-llms-opportunities/) [AI Magazine](https://md.research.elamur.ai/free/en/venues/ai-magazine/)**Canyu Chen, Kai Shu*2023 · 214 citations*
27. [**Making Retrieval-Augmented Language Models Robust to Irrelevant Context arXiv:2310.01558**Ori Yoran, Tomer Wolfson, Ori Ram, et al.*2023 · 195 citations*](https://md.research.elamur.ai/free/en/papers/yoran-2023-making-retrieval-augmented-language-models/)
28. [**RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval arXiv:2401.18059**Parth Sarthi, Salman Abdullah, Aditi Tuli, et al.*2024 · 193 citations*](https://md.research.elamur.ai/free/en/papers/sarthi-2024-raptor-recursive-abstractive-processing-tree/)
29. [**Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts arXiv:2305.13300**Jian Xie, Kai Zhang, Jiangjie Chen, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/xie-2023-adaptive-chameleon-stubborn-sloth-revealing/)
30. **[Long-form factuality in large language models](https://md.research.elamur.ai/free/en/papers/wei-2024-long-form-factuality-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jerry Wei, Chengrun Yang, Xinying Song, et al.*2024 · 165 citations*
31. **[LooGLE: Can Long-Context Language Models Understand Long Contexts?](https://md.research.elamur.ai/free/en/papers/li-2023-loogle-long-context-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaqi Li, Mengmeng Wang, Zilong Zheng, et al.*2023 · 165 citations*
32. **[A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness](https://md.research.elamur.ai/free/en/papers/wang-2024-comprehensive-survey-small-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Fali Wang, Zhiwei Zhang, Xianren Zhang, et al.*2024 · 159 citations*
33. [**RA-DIT: Retrieval-Augmented Dual Instruction Tuning arXiv:2310.01352**Xi Victoria Lin, Xilun Chen, Mingda Chen, et al.*2023 · 149 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-ra-dit-retrieval-augmented-dual/)
34. **[DRAGIN: Dynamic Retrieval Augmented Generation based on the Real-time Information Needs of Large Language Models](https://md.research.elamur.ai/free/en/papers/su-2024-dragin-dynamic-retrieval-augmented-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weihang Su, Yichen Tang, Qingyao Ai, et al.*2024 · 137 citations*
35. [**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/)
36. **[Assisting in Writing Wikipedia-like Articles From Scratch with Large Language Models](https://md.research.elamur.ai/free/en/papers/shao-2024-assisting-writing-wikipedia-like-articles/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yijia Shao, Yucheng Jiang, Theodore Kanell, et al.*2024 · 131 citations*
37. [**Fanar: An Arabic-Centric Multimodal Generative AI Platform arXiv:2501.13944**Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.*2025 · 127 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2025-fanar-arabic-centric-multimodal-generative/)
38. [**Nomic Embed: Training a Reproducible Long Context Text Embedder arXiv:2402.01613**Zach Nussbaum, John X. Morris, Brandon Duderstadt, et al.*2024 · 126 citations*](https://md.research.elamur.ai/free/en/papers/nussbaum-2024-nomic-embed-training-reproducible-long/)
39. [**RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation arXiv:2303.12570**Fengji Zhang, Bei Chen, Yue Zhang, et al.*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-repocoder-repository-level-code-completion/)
40. [**RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation arXiv:2310.04408**Fangyuan Xu, Weijia Shi, Eunsol Choi*2023 · 115 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-recomp-improving-retrieval-augmented-lms/)
41. **[ExpertQA: Expert-Curated Questions and Attributed Answers](https://md.research.elamur.ai/free/en/papers/malaviya-2024-expertqa-expert-curated-questions-attributed/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chaitanya Malaviya, Subin Lee, Sihao Chen, et al.*2024 · 113 citations*
42. [**ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models arXiv:2404.07738**Jinheon Baek, Sujay Kumar Jauhar, Silviu Cucerzan, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/baek-2024-researchagent-iterative-research-idea/)
43. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations*
44. **[Learning to Retrieve In-Context Examples for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-learning-retrieve-context-examples-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Liang Wang, Nan Yang, Furu Wei*2024 · 106 citations*
45. **[Answering Questions by Meta-Reasoning over Multiple Chains of Thought](https://md.research.elamur.ai/free/en/papers/yoran-2023-answering-questions-meta-reasoning-over/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ori Yoran, Tomer Wolfson, Ben Bogin, et al.*2023 · 99 citations*
46. [**MinerU: An Open-Source Solution for Precise Document Content Extraction arXiv:2409.18839**Bin Wang, Chao Xu, Xiaomeng Zhao, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-mineru-open-source-solution-precise/)
47. [**On the Tool Manipulation Capability of Open-source Large Language Models arXiv:2305.16504**Qiantong Xu, Fenglu Hong, Bo Li, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-tool-manipulation-capability-open-source/)
48. **[How to Train Long-Context Language Models (Effectively)](https://md.research.elamur.ai/free/en/papers/gao-2025-how-train-long-context-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Alexander Wettig, Howard Yen, et al.*2025 · 89 citations*
49. **[Complex Claim Verification with Evidence Retrieved in the Wild](https://md.research.elamur.ai/free/en/papers/chen-2024-complex-claim-verification-evidence-retrieved/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jifan Chen, Grace Kim, Aniruddh Sriram, et al.*2024 · 86 citations*
50. **[Retrieval-Augmented Generation for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/wu-2024-retrieval-augmented-generation-natural-language/) [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/)**Shangyu Wu, Ying Xiong, Yufei Cui, et al.*2024 · 86 citations*
51. **[Generating Benchmarks for Factuality Evaluation of Language Models](https://md.research.elamur.ai/free/en/papers/muhlgay-2024-generating-benchmarks-factuality-evaluation-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Dor Muhlgay, Ori Ram, Inbal Magar, et al.*2024 · 81 citations*
52. **[Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation](https://md.research.elamur.ai/free/en/papers/wang-2025-knowledge-graph-retrieval-augmented-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shijie Wang, Wenqi Fan, Yue Feng, et al.*2025 · 77 citations*
53. **[Factuality of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/wang-2024-factuality-large-language-models-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuxia Wang, Minghan Wang, Muhammad Arslan Manzoor, et al.*2024 · 77 citations*
54. **[VeriScore: Evaluating the factuality of verifiable claims in long-form text generation](https://md.research.elamur.ai/free/en/papers/song-2024-veriscore-evaluating-factuality-verifiable-claims/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yixiao Song, Yekyung Kim, Mohit Iyyer*2024 · 72 citations*
55. [**Physics of Language Models: Part 3.2, Knowledge Manipulation arXiv:2309.14402**Zeyuan Allen-Zhu, Yuanzhi Li*2023 · 72 citations*](https://md.research.elamur.ai/free/en/papers/allen-zhu-2023-physics-language-models-part-3-2/)
56. **[Tug-of-War between Knowledge: Exploring and Resolving Knowledge Conflicts in Retrieval-Augmented Language Models](https://md.research.elamur.ai/free/en/papers/jin-2024-tug-war-between-knowledge-exploring/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zhuoran Jin, Pengfei Cao, Yubo Chen, et al.*2024 · 70 citations*
57. [**MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention arXiv:2506.13585**MiniMax, Aili Chen, Aonian Li, et al.*2025 · 66 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-m1-scaling-test/)
58. **[MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/chang-2025-main-rag-multi-agent-filtering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chia-Yuan Chang, Zhimeng Jiang, Vineeth Rakesh, et al.*2025 · 65 citations*
59. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
60. [**OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs arXiv:2411.14199**Akari Asai, Jacqueline He, Rulin Shao, et al.*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/asai-2024-openscholar-synthesizing-scientific-literature/)
61. [**Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling arXiv:2406.07522**Liliang Ren, Yang Liu, Yadong Lu, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/ren-2024-samba-simple-hybrid-state-space/)
62. **[TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space](https://md.research.elamur.ai/free/en/papers/zhang-2024-truthx-alleviating-hallucinations-editing-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaolei Zhang, Tian Yu, Yang Feng*2024 · 57 citations*
63. **[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*
64. **[SeaKR: Self-aware Knowledge Retrieval for Adaptive Retrieval Augmented Generation](https://md.research.elamur.ai/free/en/papers/yao-2025-seakr-self-aware-knowledge-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zijun Yao, Weijian Qi, Liangming Pan, et al.*2025 · 52 citations*
65. [**AutoML-GPT: Automatic Machine Learning with GPT arXiv:2305.02499**Shujian Zhang, Chengyue Gong, Lemeng Wu, et al.*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-automl-gpt-automatic-machine-learning/)
66. [**MiniMax-01: Scaling Foundation Models with Lightning Attention arXiv:2501.08313**MiniMax, Aonian Li, Bangwei Gong, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/minimax-2025-minimax-01-scaling-foundation/)
67. [**ZeroSearch: Incentivize the Search Capability of LLMs without Searching arXiv:2505.04588**Hao Sun, Zile Qiao, Jiayan Guo, et al.*2025 · 50 citations*](https://md.research.elamur.ai/free/en/papers/sun-2025-zerosearch-incentivize-search-capability-llms/)
68. [**Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy arXiv:2507.01352**Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.*2025 · 48 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-skywork-reward-v2-scaling/)
69. [**Resolving Knowledge Conflicts in Large Language Models arXiv:2310.00935**Yike Wang, Shangbin Feng, Heng Wang, et al.*2023 · 48 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-resolving-knowledge-conflicts-large-language/)
70. **[AssistantBench: Can Web Agents Solve Realistic and Time-Consuming Tasks?](https://md.research.elamur.ai/free/en/papers/yoran-2024-assistantbench-can-web-agents-solve/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ori Yoran, Samuel Joseph Amouyal, Chaitanya Malaviya, et al.*2024 · 46 citations*
71. **[Blinded by Generated Contexts: How Language Models Merge Generated and Retrieved Contexts When Knowledge Conflicts?](https://md.research.elamur.ai/free/en/papers/tan-2024-blinded-generated-contexts-how-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hexiang Tan, Fei Sun, Wanli Yang, et al.*2024 · 37 citations*
72. **[TurboRAG: Accelerating Retrieval-Augmented Generation with Precomputed KV Caches for Chunked Text](https://md.research.elamur.ai/free/en/papers/lu-2025-turborag-accelerating-retrieval-augmented-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Songshuo Lu, Hua Wang, Yutian Rong, et al.*2025 · 32 citations*
73. **[Improving Retrieval Augmented Language Model with Self-Reasoning](https://md.research.elamur.ai/free/en/papers/xia-2024-improving-retrieval-augmented-language-model/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yuan Xia, Jingbo Zhou, Zhenhui Shi, et al.*2024 · 32 citations*
74. [**Augmented Large Language Models with Parametric Knowledge Guiding arXiv:2305.04757**Ziyang Luo, Can Xu, Pu Zhao, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-augmented-large-language-models-parametric/)
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76. [**Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent arXiv:2411.02265**Xingwu Sun, Yanfeng Chen, Yiqing Huang, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-hunyuan-large-open-source/)
77. [**Understanding Retrieval Augmentation for Long-Form Question Answering arXiv:2310.12150**Hung-Ting Chen, Fangyuan Xu, Shane Arora, et al.*2023 · 24 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-understanding-retrieval-augmentation-long-form/)
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80. [**GSM-Infinite: How Do Your LLMs Behave over Infinitely Increasing Context Length and Reasoning Complexity? arXiv:2502.05252**Yang Zhou, Hongyi Liu, Zhuoming Chen, et al.*2025 · 21 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2025-gsm-infinite-llms-behave-over/)
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86. [**Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance arXiv:2507.22448**Jingwei Zuo, Maksim Velikanov, Ilyas Chahed, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/zuo-2025-falcon-h1-family-hybrid-head/)
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88. [**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/)
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92. [**QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning arXiv:2505.17667**Fanqi Wan, Weizhou Shen, Shengyi Liao, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/wan-2025-qwenlong-l1-long-context/)
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96. [**Bridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding arXiv:2410.01671**Yanming Liu, Xinyue Peng, Jiannan Cao, et al.*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-bridging-context-gaps-leveraging-coreference/)
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