---
title: "Who cites Meng Wang — 1,029 papers of our library"
description: "1,029 papers of the Elamur Research library cite the works of Meng Wang, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/meng-wang/cited-by/"
---
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# Who cites Meng Wang

1,029 citations of their works from 1,029 papers of our library (of the 149,439 whose bibliographies we read) · 172 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Meng Wang](https://md.research.elamur.ai/free/en/authors/meng-wang/)

**1** [2](https://md.research.elamur.ai/free/en/authors/meng-wang/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/meng-wang/cited-by/page/2/)

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. [**InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning arXiv:2305.06500**Wenliang Dai, Junnan Li, Dongxu Li, et al.*2023 · 1,100 citations*](https://md.research.elamur.ai/free/en/papers/dai-2023-instructblip-towards-general-purpose-vision/)
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. [**Regularizing Neural Networks by Penalizing Confident Output Distributions arXiv:1701.06548**Gabriel Pereyra, George Tucker, Jan Chorowski, et al.*2017 · 496 citations*](https://md.research.elamur.ai/free/en/papers/pereyra-2017-regularizing-neural-networks-penalizing-confident/)
5. [**Large Language Models: A Survey arXiv:2402.06196**Shervin Minaee, Tomas Mikolov, Narjes Nikzad, et al.*2024 · 471 citations*](https://md.research.elamur.ai/free/en/papers/minaee-2024-large-language-models-survey/)
6. [**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/)
7. **[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*
8. **[Large Language Models for Generative Information Extraction: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2023-large-language-models-generative-information/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Derong Xu, Wei Chen, Wenjun Peng, et al.*2023 · 406 citations*
9. [**A Survey on Large Language Models for Code Generation arXiv:2406.00515**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
10. [**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/)
11. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 320 citations*
12. [**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/)
13. [**The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) arXiv:2309.17421**Zhengyuan Yang, Linjie Li, Kevin Lin, et al.*2023 · 311 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-dawn-lmms-preliminary-explorations-gpt/)
14. [**InternLM2 Technical Report arXiv:2403.17297**Zheng Cai, Maosong Cao, Haojiong Chen, et al.*2024 · 301 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-internlm2-technical-report/)
15. [**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/)
16. [**Large Language Model based Multi-Agents: A Survey of Progress and Challenges arXiv:2402.01680**Taicheng Guo, Xiuying Chen, Yaqi Wang, et al.*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/guo-2024-large-language-model-based/)
17. **[Graph Retrieval-Augmented Generation: A Survey](https://md.research.elamur.ai/free/en/papers/peng-2024-graph-retrieval-augmented-generation-survey/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Boci Peng, Yun Zhu, Yongchao Liu, et al.*2024 · 276 citations*
18. [**Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools arXiv:2405.20362**Varun Magesh, Faiz Surani, Matthew Dahl, et al.*2024 · 271 citations*](https://md.research.elamur.ai/free/en/papers/magesh-2024-hallucination-free-assessing-reliability-leading/)
19. [**Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture arXiv:2306.16092**Jiaxi Cui; Munan Ning; Zongjian Li; Bohua Chen; Yang Yan; Hao Li; Bin Ling; Yonghong Tian;, Li Yuan*2023 · 248 citations*](https://md.research.elamur.ai/free/en/papers/cui-2023-chatlaw-multi-agent-legal-assistant/)
20. **[mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2024-mgte-generalized-long-context-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Zhang, Yanzhao Zhang, Dingkun Long, et al.*2024 · 237 citations*
21. **[On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey](https://md.research.elamur.ai/free/en/papers/long-2024-llms-driven-synthetic-data-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lin Long, Rui Wang, Ruixuan Xiao, et al.*2024 · 237 citations*
22. **[G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering](https://md.research.elamur.ai/free/en/papers/he-2024-g-retriever-retrieval-augmented-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoxin He, Yijun Tian, Yifei Sun, et al.*2024 · 236 citations*
23. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
24. **[Knowledge Conflicts for LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 182 citations*
25. **[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*
26. [**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/)
27. **[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*
28. [**R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning arXiv:2503.05592**Huatong Song, Jinhao Jiang, Yingqian Min, et al.*2025 · 141 citations*](https://md.research.elamur.ai/free/en/papers/song-2025-r1-searcher-incentivizing-search/)
29. **[DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments](https://md.research.elamur.ai/free/en/papers/zheng-2025-deepresearcher-scaling-deep-research-reinforcement/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuxiang Zheng, Dayuan Fu, Xiangkun Hu, et al.*2025 · 113 citations*
30. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
31. **[Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs](https://md.research.elamur.ai/free/en/papers/jin-2024-graph-chain-thought-augmenting-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bowen Jin, Chulin Xie, Jiawei Zhang, et al.*2024 · 89 citations*
32. [**A Survey of Large Language Models in Medicine: Progress, Application, and Challenge arXiv:2311.05112**Hongjian Zhou, Fenglin Liu, Boyang Gu, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-survey-large-language-models-medicine/)
33. **[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*
34. **[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*
35. **[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*
36. [**Self-Reflection in LLM Agents: Effects on Problem-Solving Performance arXiv:2405.06682 · 2nd International Conference on Foundation and Large Language Models (FLLM 2024), pp. 476-483**Matthew Renze, Erhan Guven*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/renze-2024-self-reflection-llm-agents-effects/)
37. **[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*
38. **[Generate-then-Ground in Retrieval-Augmented Generation for Multi-hop Question Answering](https://md.research.elamur.ai/free/en/papers/shi-2024-generate-then-ground-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengliang Shi, Shuo Zhang, Weiwei Sun, et al.*2024 · 65 citations*
39. **[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*
40. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/)
41. **[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*
42. **[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*
43. [**RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation arXiv:2403.05313**Zihao Wang, Anji Liu, Haowei Lin, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-rat-retrieval-augmented-thoughts-elicit/)
44. **[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*
45. [**SarcasmBench: Towards Evaluating Large Language Models on Sarcasm Understanding arXiv:2408.11319**Yazhou Zhang, Chunwang Zou, Zheng Lian, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-sarcasmbench-towards-evaluating-large-language/)
46. **[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*
47. [**Weaver: Foundation Models for Creative Writing arXiv:2401.17268**Tiannan Wang; Jiamin Chen; Qingrui Jia; Shuai Wang; Ruoyu Fang; Huilin Wang; Zhaowei Gao; Chunzhao Xie; Chuou Xu; Jihong Dai; Yibin Liu; Jialong Wu; Shengwei Ding; Long Li; Zhiwei Huang; Xinle Deng; Teng Yu; Gangan Ma; Han Xiao; Zixin Chen; Danjun Xiang; Yunxia Wang; Yuanyuan Zhu; Yi Xiao; Jing Wang; Yiru Wang; Siran Ding; Jiayang Huang; Jiayi Xu; Yilihamu Tayier; Zhenyu Hu; Yuan Gao; Chengfeng Zheng; Yueshu Ye; Yihang Li; Lei Wan; Xinyue Jiang; Yujie Wang; Siyu Cheng; Zhule Song; Xiangru Tang; Xiaohua Xu; Ningyu Zhang; Huajun Chen; Yuchen Eleanor Jiang;, Wangchunshu Zhou*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-weaver-foundation-models-creative-writing/)
48. **[CLAPnq: Cohesive Long-form Answers from Passages in Natural Questions for RAG systems](https://md.research.elamur.ai/free/en/papers/rosenthal-2025-clapnq-cohesive-long-form-answers/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Sara Rosenthal, Avirup Sil, Radu Florian, et al.*2025 · 29 citations*
49. [**Can Language Models Solve Olympiad Programming? arXiv:2404.10952**Quan Shi, Michael Tang, Karthik Narasimhan, et al.*2024 · 28 citations*](https://md.research.elamur.ai/free/en/papers/shi-2024-language-models-solve-olympiad-programming/)
50. **[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*
51. **[FaithfulRAG: Fact-Level Conflict Modeling for Context-Faithful Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhang-2025-faithfulrag-fact-level-conflict-modeling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qinggang Zhang, Zhishang Xiang, Yilin Xiao, et al.*2025 · 27 citations*
52. **[Hierarchical Document Refinement for Long-context Retrieval-augmented Generation](https://md.research.elamur.ai/free/en/papers/jin-2025-hierarchical-document-refinement-long-context/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiajie Jin, Xiaoxi Li, Guanting Dong, et al.*2025 · 25 citations*
53. **[Removal of Hallucination on Hallucination: Debate-Augmented RAG](https://md.research.elamur.ai/free/en/papers/hu-2025-removal-hallucination-hallucination-debate-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wentao Hu, Wengyu Zhang, Yiyang Jiang, et al.*2025 · 25 citations*
54. [**StateFlow: Enhancing LLM Task-Solving through State-Driven Workflows arXiv:2403.11322**Yiran Wu, Tianwei Yue, Shaokun Zhang, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-stateflow-enhancing-llm-task-solving/)
55. **[VRAG-RL: Empower Vision-Perception-Based RAG for Visually Rich Information Understanding via Iterative Reasoning with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2025-vrag-rl-empower-vision-perception/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Qiuchen Wang, Ruixue Ding, Yu Zeng, et al.*2025 · 23 citations*
56. **[What is the Role of Small Models in the LLM Era: A Survey](https://md.research.elamur.ai/free/en/papers/chen-2024-role-small-models-llm-era/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Lihu Chen, Gael Varoquaux*2024 · 23 citations*
57. **[VISA: Retrieval Augmented Generation with Visual Source Attribution](https://md.research.elamur.ai/free/en/papers/ma-2025-visa-retrieval-augmented-generation-visual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueguang Ma, Shengyao Zhuang, Bevan Koopman, et al.*2025 · 22 citations*
58. **[WavRAG: Audio-Integrated Retrieval Augmented Generation for Spoken Dialogue Models](https://md.research.elamur.ai/free/en/papers/chen-2025-wavrag-audio-integrated-retrieval-augmented/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifu Chen, Shengpeng Ji, Haoxiao Wang, et al.*2025 · 22 citations*
59. **[Exploring Retrieval Augmented Generation in Arabic](https://md.research.elamur.ai/free/en/papers/el-beltagy-2024-exploring-retrieval-augmented-generation-arabic/) [Procedia Computer Science](https://md.research.elamur.ai/free/en/venues/procedia-computer-science/)**Samhaa R. El-Beltagy, Mohamed A. Abdallah*2024 · 22 citations*
60. **[A Survey on Evaluation of LLM-based Agents](https://md.research.elamur.ai/free/en/papers/yehudai-2026-survey-evaluation-llm-based-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Asaf Yehudai, Lilach Eden, Alan Li, et al.*2026 · 21 citations*
61. **[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*
62. [**MoRAL: MoE Augmented LoRA for LLMs' Lifelong Learning arXiv:2402.11260**Shu Yang; Muhammad Asif Ali; Cheng-Long Wang; Lijie Hu;, Di Wang*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-moral-moe-augmented-lora-llms/)
63. **[DualRAG: A Dual-Process Approach to Integrate Reasoning and Retrieval for Multi-Hop Question Answering](https://md.research.elamur.ai/free/en/papers/cheng-2025-dualrag-dual-process-approach-integrate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rong Cheng, Jinyi Liu, Yan Zheng, et al.*2025 · 20 citations*
64. **[SURVEYFORGE : On the Outline Heuristics, Memory-Driven Generation, and Multi-dimensional Evaluation for Automated Survey Writing](https://md.research.elamur.ai/free/en/papers/yan-2025-surveyforge-outline-heuristics-memory-driven/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangchao Yan, Shiyang Feng, Jiakang Yuan, et al.*2025 · 20 citations*
65. **[Pandora's Box or Aladdin's Lamp: A Comprehensive Analysis Revealing the Role of RAG Noise in Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2025-pandora-s-box-or-aladdin/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinyang Wu, Shuai Zhang, Feihu Che, et al.*2025 · 19 citations*
66. **[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*
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73. [**Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models arXiv:2411.02382**Guangzhi Xiong, Eric Xie, Amir Hassan Shariatmadari, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2024-improving-scientific-hypothesis-generation-knowledge/)
74. **[MIRAGE-Bench: Automatic Multilingual Benchmark Arena for Retrieval-Augmented Generation Systems](https://md.research.elamur.ai/free/en/papers/thakur-2025-mirage-bench-automatic-multilingual-benchmark/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nandan Thakur, Suleman Kazi, Ge Luo, et al.*2025 · 15 citations*
75. **[Capture Human Disagreement Distributions by Calibrated Networks for Natural Language Inference](https://md.research.elamur.ai/free/en/papers/wang-2022-capture-human-disagreement-distributions-calibrated/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxia Wang, Minghan Wang, Yimeng Chen, et al.*2022 · 15 citations*
76. **[LLMs Know What They Need: Leveraging a Missing Information Guided Framework to Empower Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wang-2025-llms-know-what-they-need/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Keheng Wang, Feiyu Duan, Peiguang Li, et al.*2025 · 14 citations*
77. [**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/)
78. **[OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking](https://md.research.elamur.ai/free/en/papers/xi-2025-omnithink-expanding-knowledge-boundaries-machine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zekun Xi, Wenbiao Yin, Jizhan Fang, et al.*2025 · 14 citations*
79. **[RaDeR: Reasoning-aware Dense Retrieval Models](https://md.research.elamur.ai/free/en/papers/das-2025-rader-reasoning-aware-dense-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Debrup Das, Sam O'Nuallain, Razieh Rahimi*2025 · 14 citations*
80. **[A Reality Check on Context Utilisation for Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/hagstrom-2025-reality-check-context-utilisation-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lovisa Hagström, Sara Vera Marjanovic, Haeun Yu, et al.*2025 · 13 citations*
81. **[Alignment for Efficient Tool Calling of Large Language Models](https://md.research.elamur.ai/free/en/papers/xu-2025-alignment-efficient-tool-calling-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hongshen Xu, Zihan Wang, Zichen Zhu, et al.*2025 · 13 citations*
82. **[Mix-of-Granularity: Optimize the Chunking Granularity for Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/zhong-2025-mix-granularity-optimize-chunking-granularity/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zijie Zhong, Hanwen Liu, Xiaoya Cui, et al.*2025 · 13 citations*
83. **[Teaching Vision-Language Models to Ask: Resolving Ambiguity in Visual Questions](https://md.research.elamur.ai/free/en/papers/jian-2025-teaching-vision-language-models-ask/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pu Jian, Donglei Yu, Wen Yang, et al.*2025 · 13 citations*
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87. **[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*
88. **[Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization](https://md.research.elamur.ai/free/en/papers/huang-2025-improving-contextual-faithfulness-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Huang, Xiaocheng Feng, Weitao Ma, et al.*2025 · 11 citations*
89. **[SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence](https://md.research.elamur.ai/free/en/papers/liu-2025-selfelicit-your-language-model-secretly/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhining Liu, Rana Ali Amjad, Ravinarayana Adkathimar, et al.*2025 · 11 citations*
90. **[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*
91. **[Parenting: Optimizing Knowledge Selection of Retrieval-Augmented Language Models with Parameter Decoupling and Tailored Tuning](https://md.research.elamur.ai/free/en/papers/xu-2025-parenting-optimizing-knowledge-selection-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongxin Xu, Ruizhe Zhang, Xinke Jiang, et al.*2025 · 9 citations*
92. [**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/)
93. **[Large Language Models as Legal Translators of Arabic Legislation: Do ChatGPT and Gemini Care for Context and Terminology?](https://md.research.elamur.ai/free/en/papers/elfqih-2024-large-language-models-as-legal/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Khadija Ait ElFqih, Johanna Monti*2024 · 9 citations*
94. **[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/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bo Li, Mingda Wang, Gexiang Fang, et al.*2026 · 8 citations*
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96. [**GATE: General Arabic Text Embedding for Enhanced Semantic Textual Similarity with Matryoshka Representation Learning and Hybrid Loss Training arXiv:2505.24581**Omer Nacar, Anis Koubaa, Serry Sibaee, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/nacar-2025-gate-general-arabic-text-embedding/)
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98. **[Conflicting Needles in a Haystack: How LLMs behave when faced with contradictory information](https://md.research.elamur.ai/free/en/papers/kurfali-2025-conflicting-needles-haystack-how-llms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Murathan Kurfali, Robert Östling*2025 · 5 citations*
99. **[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*
100. **[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*

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