---
title: "Who cites Nick M. Barnes — 246 papers of our library"
description: "246 papers of the Elamur Research library cite the works of Nick M. Barnes, found in their bibliographies; the most cited first."
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---
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# Who cites Nick M. Barnes

247 citations of their works from 246 papers of our library (of the 149,439 whose bibliographies we read) · 41 with a page here, the most cited first · [← Nick M. Barnes](https://md.research.elamur.ai/free/en/authors/nick-m-barnes/)

1. **[Security and Privacy Challenges of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/das-2024-security-privacy-challenges-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu*2024 · 424 citations*
2. **[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*
3. **[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*
4. **[Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces](https://md.research.elamur.ai/free/en/papers/yang-2024-thinking-space-multimodal-large-language/) [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/)**Jihan Yang, Shusheng Yang, Anjali W. Gupta, et al.*2024 · 182 citations*
5. [**LongNet: Scaling Transformers to 1,000,000,000 Tokens arXiv:2307.02486**Jiayu Ding, Shuming Ma, Li Dong, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/ding-2023-longnet-scaling-transformers-1-000/)
6. [**Small Language Models are the Future of Agentic AI arXiv:2506.02153**Peter Belcak, Greg Heinrich, Shizhe Diao, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/belcak-2025-small-language-models-future-agentic/)
7. **[LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing](https://md.research.elamur.ai/free/en/papers/du-2024-llms-assist-nlp-researchers-critique/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiangshu Du, Yibo Wang, Wenting Zhao, et al.*2024 · 71 citations*
8. [**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/)
9. [**Simple linear attention language models balance the recall-throughput tradeoff arXiv:2402.18668**Simran Arora, Sabri Eyuboglu, Michael Zhang, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/arora-2024-simple-linear-attention-language-models/)
10. [**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/)
11. [**TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer arXiv:2307.14995**Zhen Qin, Dong Li, Weigao Sun, et al.*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-transnormerllm-faster-better-large/)
12. [**Lightning Attention-2: A Free Lunch for Handling Unlimited Sequence Lengths in Large Language Models arXiv:2401.04658**Zhen Qin, Weigao Sun, Dong Li, et al.*2024 · 31 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-lightning-attention-2-free/)
13. [**Linearizing Large Language Models arXiv:2405.06640**Jean Mercat, Igor Vasiljevic, Sedrick Keh, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/mercat-2024-linearizing-large-language-models/)
14. **[UORA: Uniform Orthogonal Reinitialization Adaptation in Parameter Efficient Fine-Tuning of Large Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-uora-uniform-orthogonal-reinitialization-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueyan Zhang, Jinman Zhao, Zhifei Yang, et al.*2025 · 14 citations*
15. **[Psyche-R1: Towards Reliable Psychological LLMs through Unified Empathy, Expertise, and Reasoning](https://md.research.elamur.ai/free/en/papers/dai-2026-psyche-r1-reliable-psychological-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chongyuan Dai, Jinpeng Hu, Hongchang Shi, et al.*2026 · 8 citations*
16. [**Evaluating Arabic Large Language Models: A Survey of Benchmarks, Methods, and Gaps arXiv:2510.13430**Ahmed Alzubaidi, Shaikha Alsuwaidi, Basma El Amel Boussaha, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/alzubaidi-2025-evaluating-arabic-large-language-models/)
17. **[ASOS at KSAA-CAD 2024: One Embedding is All You Need for Your Dictionary](https://md.research.elamur.ai/free/en/papers/sibaee-2024-asos-ksaa-cad-2024-one/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Serry Sibaee, Abdullah Alharbi, Samar Ahmad, et al.*2024 · 6 citations*
18. **[A Study of LLMs' Preferences for Libraries and Programming Languages](https://md.research.elamur.ai/free/en/papers/twist-2026-study-llms-preferences-libraries-programming/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lukas Twist, Mark Harman, Don Syme, et al.*2026 · 5 citations*
19. [**GemmAr: Enhancing LLMs Through Arabic Instruction-Tuning arXiv:2407.02147**Hasna Chouikhi, Manel Aloui, Cyrine Ben Hammou, et al.*2024 · 4 citations*](https://md.research.elamur.ai/free/en/papers/chouikhi-2024-gemmar-enhancing-llms-through-arabic/)
20. [**Large Means Left: Political Bias in Large Language Models Increases with Their Number of Parameters arXiv:2505.04393**David Exler, Mark Schutera, Markus Reischl, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/exler-2025-large-means-left-political-bias/)
21. **[Attention to Non-Adopters](https://md.research.elamur.ai/free/en/papers/zhou-2026-attention-non-adopters/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaitlyn Zhou, Kristina Gligorić, Myra Cheng, et al.*2026 · 1 citation*
22. **[Evaluating Robustness of Large Language Models Against Multilingual Typographical Errors](https://md.research.elamur.ai/free/en/papers/zhao-2026-evaluating-robustness-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Raoyuan Zhao, Yihong Liu, Lena Altinger, et al.*2026 · 1 citation*
23. **[Agent-GWO: Collaborative Agents for Dynamic Prompt Optimization in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-agent-gwo-collaborative-agents-dynamic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xudong Wang, Chaoning Zhang, Chenghao Li, et al.*2026*
24. **[Are All Prompt Components Value-Neutral? Understanding the Heterogeneous Adversarial Robustness of Dissected Prompt in LLMs](https://md.research.elamur.ai/free/en/papers/zheng-2026-are-all-prompt-components-value/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yujia Zheng, Tianhao Li, Haotian Huang, et al.*2026*
25. **[Beyond Static Persona Consistency: Dynamic Persona Coherence in LLM Role-Playing](https://md.research.elamur.ai/free/en/papers/qi-2026-beyond-static-persona-consistency-dynamic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yirui QI, Xiaoming Zhang, Ruilin Zeng, et al.*2026*
26. **[Calibrating Inference Time Alignment with Sequence-level Risk Accumulation](https://md.research.elamur.ai/free/en/papers/tan-2026-calibrating-inference-time-alignment-sequence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shanwen Tan, Ziyang Dong, Wei Ju, et al.*2026*
27. **[Datasets for Scientific Literature Understanding: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2026-datasets-scientific-literature-understanding-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuanzhe Zhang, Xun Zhao, Maodi Hu, et al.*2026*
28. **[ELO: Efficient Layer-Specific Optimization for Continual Pretraining of Multilingual LLMs](https://md.research.elamur.ai/free/en/papers/yoo-2026-elo-efficient-layer-specific-optimization/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hangyeol Yoo, ChangSu Choi, Minjun Kim, et al.*2026*
29. **[From Isolated Scoring to Collaborative Ranking: A Comparison-Native Framework for LLM-Based Paper Evaluation](https://md.research.elamur.ai/free/en/papers/zheng-2026-isolated-scoring-collaborative-ranking-comparison/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pujun Zheng, Jiacheng Yao, Jinquan Zheng, et al.*2026*
30. **[HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs](https://md.research.elamur.ai/free/en/papers/peng-2026-hss-synth-humanities-social-sciences/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ru Peng, Tianyu Zhao, Xijun Gu, et al.*2026*
31. **[InfiAgent: An Infinite-Horizon Framework for General-Purpose Autonomous Agents](https://md.research.elamur.ai/free/en/papers/yu-2026-infiagent-infinite-horizon-framework-general/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenglin Yu, Yuchen Wang, Songmiao Wang, et al.*2026*
32. **[Linguistically-Informed Evaluation of LLMs on Acceptability Judgments in a Forced-Choice Paradigm](https://md.research.elamur.ai/free/en/papers/liu-2026-linguistically-informed-evaluation-llms-acceptability/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyue Liu, Nils Reiter*2026*
33. **[Machine Translation for Low-Resource Languages through Monolingual Data and LLM: A Case Study of English-to-Basque](https://md.research.elamur.ai/free/en/papers/luu-2026-machine-translation-low-resource-languages/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Nam Luu, Aitor Soroa, German Rigau, et al.*2026*
34. **[MetaBench: A Multi-task Benchmark for Assessing LLMs in Metabolomics](https://md.research.elamur.ai/free/en/papers/lu-2026-metabench-multi-task-benchmark-assessing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxing Lu, Xukai Zhao, J. Ben Tamo, et al.*2026*
35. **[Model-Based Imaginative Planning for Embodied Agents](https://md.research.elamur.ai/free/en/papers/song-2026-model-based-imaginative-planning-embodied/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junru Song, Hengzhe Jin, Yucong Huang, et al.*2026*
36. **[Reflective RAG: Self-Evaluation Driven Strategy Optimization in Agentic Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/wu-2026-reflective-rag-self-evaluation-driven/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haiyan Wu, Chenchen Wang, Chaoqun Sun, et al.*2026*
37. **[Social Welfare Function Leaderboard: On the Emergence of LLM Agents as the Welfare Dictator](https://md.research.elamur.ai/free/en/papers/shi-2026-social-welfare-function-leaderboard-emergence/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengliang Shi, Ruotian Ma, Jen-tse Huang, et al.*2026*
38. **[TeachMaster: Generative Teaching via Code](https://md.research.elamur.ai/free/en/papers/wang-2026-teachmaster-generative-teaching-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuheng Wang, Runde Yang, Lin Wu, et al.*2026*
39. **[TeamFusion: Supporting Open-ended Teamwork with Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/liu-2026-teamfusion-supporting-open-ended-teamwork/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiale Liu, Victor Bursztyn, Lin Ai, et al.*2026*
40. **[What Makes a Good Query? Measuring the Impact of Human-Confusing Linguistic Features on LLM Performance](https://md.research.elamur.ai/free/en/papers/watson-2026-what-makes-good-query-measuring/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**William Watson, Nicole Cho, Sumitra Ganesh, et al.*2026*
41. **[Survey on Code Generation with LLM-based Agents (基于大语言模型智能体的代码生成综述)](https://md.research.elamur.ai/free/en/papers/dong-2025-code-generation-llm/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yihong Dong (董益宏), Xue Jiang (姜雪), Jiaru Qian (钱家如), et al.*2025*

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

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