---
title: "Who cites Jon Ander Campos — 473 papers of our library"
description: "473 papers of the Elamur Research library cite the works of Jon Ander Campos, found in their bibliographies · page 1 of 2 · 1–100; the most…"
canonical: "https://research.elamur.ai/free/en/authors/jon-ander-campos/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/jon-ander-campos/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Jon Ander Campos](https://md.research.elamur.ai/free/en/authors/jon-ander-campos/) / cited by

# Who cites Jon Ander Campos

497 citations of their works from 473 papers of our library (of the 149,439 whose bibliographies we read) · 131 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Jon Ander Campos](https://md.research.elamur.ai/free/en/authors/jon-ander-campos/)

**1** [2](https://md.research.elamur.ai/free/en/authors/jon-ander-campos/cited-by/page/2/) [next →](https://md.research.elamur.ai/free/en/authors/jon-ander-campos/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. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
3. **[LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2024-llamafactory-unified-efficient-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.*2024 · 1,048 citations*
4. [**Constitutional AI: Harmlessness from AI Feedback arXiv:2212.08073**Yuntao Bai, Saurav Kadavath, Sandipan Kundu, et al.*2022 · 1,028 citations*](https://md.research.elamur.ai/free/en/papers/bai-2022-constitutional-ai-harmlessness-ai-feedback/)
5. **[AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback](https://md.research.elamur.ai/free/en/papers/dubois-2023-alpacafarm-simulation-framework-methods-that/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yann Dubois, Xuechen Li, Rohan Taori, et al.*2023 · 456 citations*
6. [**Large Language Models as Optimizers arXiv:2309.03409**Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al.*2023 · 413 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-large-language-models-optimizers/)
7. [**CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing arXiv:2305.11738**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 326 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-critic-large-language-models-self/)
8. [**RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment arXiv:2304.06767**Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-raft-reward-ranked-finetuning-generative/)
9. [**Self-critiquing models for assisting human evaluators arXiv:2206.05802**William Saunders, Catherine Yeh, Jeff Wu, et al.*2022 · 228 citations*](https://md.research.elamur.ai/free/en/papers/saunders-2022-self-critiquing-models-assisting-human/)
10. [**Fine-Grained Human Feedback Gives Better Rewards for Language Model Training arXiv:2306.01693**Zeqiu Wu, Yushi Hu, Weijia Shi, et al.*2023 · 223 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-fine-grained-human-feedback-gives/)
11. **[Same Task, More Tokens: the Impact of Input Length on the Reasoning Performance of Large Language Models](https://md.research.elamur.ai/free/en/papers/levy-2024-same-task-more-tokens-impact/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mosh Levy, Alon Jacoby, Yoav Goldberg*2024 · 217 citations*
12. [**From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline arXiv:2406.11939**Tianle Li, Wei-Lin Chiang, Evan Frick, et al.*2024 · 210 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-crowdsourced-data-high-quality-benchmarks/)
13. [**Aya Expanse: Combining Research Breakthroughs for a New Multilingual Frontier arXiv:2412.04261**John Dang, Shivalika Singh, Daniel D'souza, et al.*2024 · 184 citations*](https://md.research.elamur.ai/free/en/papers/dang-2024-aya-expanse-combining-research-breakthroughs/)
14. **[Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation](https://md.research.elamur.ai/free/en/papers/singh-2025-global-mmlu-understanding-addressing-cultural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shivalika Singh, Angelika Romanou, Clémentine Fourrier, et al.*2025 · 182 citations*
15. [**REFINER: Reasoning Feedback on Intermediate Representations arXiv:2304.01904**Debjit Paul, Mete Ismayilzada, Maxime Peyrard, et al.*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/paul-2023-refiner-reasoning-feedback-intermediate-representations/)
16. **[BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages](https://md.research.elamur.ai/free/en/papers/myung-2024-blend-benchmark-llms-everyday-knowledge/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Junho Myung, Nayeon Lee, Yi Zhou, et al.*2024 · 152 citations*
17. [**Understanding the Effects of RLHF on LLM Generalisation and Diversity arXiv:2310.06452**Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, et al.*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/kirk-2023-understanding-effects-rlhf-llm-generalisation/)
18. **[Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction Strategies](https://md.research.elamur.ai/free/en/papers/pan-2024-automatically-correcting-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Liangming Pan, Michael Saxon, Wenda Xu, et al.*2024 · 140 citations*
19. **[Investigating Data Contamination in Modern Benchmarks for Large Language Models](https://md.research.elamur.ai/free/en/papers/deng-2024-investigating-data-contamination-modern-benchmarks/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.*2024 · 137 citations*
20. **[The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models](https://md.research.elamur.ai/free/en/papers/kirk-2024-prism-alignment-dataset-participatory-representative/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hannah Rose Kirk, Alexander Whitefield, Paul Rottger, et al.*2024 · 133 citations*
21. [**Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback arXiv:2305.10142**Yao Fu, Hao Peng, Tushar Khot, et al.*2023 · 132 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-improving-language-model-negotiation-self/)
22. **[OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement](https://md.research.elamur.ai/free/en/papers/zheng-2024-opencodeinterpreter-integrating-code-generation-execution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianyu Zheng, Ge Zhang, Tianhao Shen, et al.*2024 · 129 citations*
23. [**Chain of Hindsight Aligns Language Models with Feedback arXiv:2302.02676**Hao Liu, Carmelo Sferrazza, Pieter Abbeel*2023 · 126 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-chain-hindsight-aligns-language-models/)
24. [**Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step arXiv:2402.16906**Li Zhong, Zilong Wang, Jingbo Shang*2024 · 124 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-debug-like-human-large-language/)
25. [**Large Language Model Alignment: A Survey arXiv:2309.15025**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/)
26. [**Pretraining Language Models with Human Preferences arXiv:2302.08582**Tomasz Korbak, Kejian Shi, Angelica Chen, et al.*2023 · 121 citations*](https://md.research.elamur.ai/free/en/papers/korbak-2023-pretraining-language-models-human-preferences/)
27. [**GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction arXiv:2310.03668**Oscar Sainz, Iker Garcia-Ferrero, Rodrigo Agerri, et al.*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/sainz-2023-gollie-annotation-guidelines-improve-zero/)
28. [**Don't Make Your LLM an Evaluation Benchmark Cheater arXiv:2311.01964**Kun Zhou, Yutao Zhu, Zhipeng Chen, et al.*2023 · 112 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-don-t-make-llm-evaluation/)
29. **[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*
30. **[A Careful Examination of Large Language Model Performance on Grade School Arithmetic](https://md.research.elamur.ai/free/en/papers/zhang-2024-careful-examination-large-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugh Zhang, Jeff Da, Dean Lee, et al.*2024 · 101 citations*
31. **[InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback](https://md.research.elamur.ai/free/en/papers/yang-2023-intercode-standardizing-benchmarking-interactive-coding/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**John Yang, Akshara Prabhakar, Karthik Narasimhan, et al.*2023 · 95 citations*
32. **[RL4F: Generating Natural Language Feedback with Reinforcement Learning for Repairing Model Outputs](https://md.research.elamur.ai/free/en/papers/akyurek-2023-rl4f-generating-natural-language-feedback/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Afra Feyza Akyurek, Ekin Akyurek, Ashwin Kalyan, et al.*2023 · 89 citations*
33. **[Task Contamination: Language Models May Not Be Few-Shot Anymore](https://md.research.elamur.ai/free/en/papers/li-2023-task-contamination-language-models-may/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Changmao Li, Jeffrey Flanigan*2023 · 89 citations*
34. [**Language Model Cascades arXiv:2207.10342**David Dohan, Winnie Xu, Aitor Lewkowycz, et al.*2022 · 89 citations*](https://md.research.elamur.ai/free/en/papers/dohan-2022-language-model-cascades/)
35. **[BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack](https://md.research.elamur.ai/free/en/papers/kuratov-2024-babilong-testing-limits-llms-long/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuri Kuratov, Aydar Bulatov, Petr Anokhin, et al.*2024 · 88 citations*
36. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
37. [**HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs arXiv:2412.18925**Junying Chen, Zhenyang Cai, Ke Ji, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-huatuogpt-o1-towards-medical-complex/)
38. [**Benchmark Data Contamination of Large Language Models: A Survey arXiv:2406.04244**Cheng Xu, Shuhao Guan, Derek Greene, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmark-data-contamination-large/)
39. **[Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations*
40. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
41. **[WMT24++: Expanding the Language Coverage of WMT24 to 55 Languages & Dialects](https://md.research.elamur.ai/free/en/papers/deutsch-2025-wmt24-expanding-language-coverage-wmt24/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Daniel Deutsch, Eleftheria Briakou, Isaac Rayburn Caswell, et al.*2025 · 80 citations*
42. [**SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling arXiv:2312.15166**Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-solar-10-7b-scaling-large/)
43. **[Benchmarking Large Language Models on Answering and Explaining Challenging Medical Questions](https://md.research.elamur.ai/free/en/papers/chen-2025-benchmarking-large-language-models-answering/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hanjie Chen, Zhouxiang Fang, Yash Singla, et al.*2025 · 75 citations*
44. **[MMLU-ProX: A Multilingual Benchmark for Advanced Large Language Model Evaluation](https://md.research.elamur.ai/free/en/papers/xuan-2025-mmlu-prox-multilingual-benchmark-advanced/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weihao Xuan, Rui Yang, Heli Qi, et al.*2025 · 75 citations*
45. [**Reinforcement Learning via Self-Distillation arXiv:2601.20802**Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.*2026 · 74 citations*](https://md.research.elamur.ai/free/en/papers/hubotter-2026-reinforcement-learning-self-distillation/)
46. [**INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge arXiv:2411.19799**Angelika Romanou, Negar Foroutan, Anna Sotnikova, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/romanou-2024-include-evaluating-multilingual-language-understanding/)
47. **[Can Language Models Handle Recursively Nested Grammatical Structures? A Case Study on Comparing Models and Humans](https://md.research.elamur.ai/free/en/papers/lampinen-2024-can-language-models-handle-recursively/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Andrew Lampinen*2024 · 63 citations*
48. **[MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance](https://md.research.elamur.ai/free/en/papers/pi-2024-mllm-protector-ensuring-mllm-s/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Renjie Pi, Tianyang Han, Jianshu Zhang, et al.*2024 · 58 citations*
49. **[SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages](https://md.research.elamur.ai/free/en/papers/lovenia-2024-seacrowd-multilingual-multimodal-data-hub/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Holy Lovenia, Rahmad Mahendra, Salsabil Maulana Akbar, et al.*2024 · 54 citations*
50. [**Improving Language Models via Plug-and-Play Retrieval Feedback arXiv:2305.14002**Wenhao Yu, Zhihan Zhang, Zhenwen Liang, et al.*2023 · 54 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-improving-language-models-plug-play/)
51. [**RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning arXiv:2410.02089**Jonas Gehring, Kunhao Zheng, Jade Copet, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/gehring-2024-rlef-grounding-code-llms-execution/)
52. [**Self-Verification Improves Few-Shot Clinical Information Extraction arXiv:2306.00024 · IMLH 2023**Zelalem Gero, Chandan Singh, Hao Cheng, et al.*2023 · 51 citations*](https://md.research.elamur.ai/free/en/papers/gero-2023-self-verification-improves-few-shot/)
53. **[The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm](https://md.research.elamur.ai/free/en/papers/aakanksha-2024-multilingual-alignment-prism-aligning-global/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Aakanksha, Arash Ahmadian, Beyza Ermis, et al.*2024 · 49 citations*
54. [**From LLM to NMT: Advancing Low-Resource Machine Translation with Claude arXiv:2404.13813**Maxim Enis, Mark Hopkins*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/enis-2024-llm-nmt-advancing-low-resource/)
55. [**GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements arXiv:2402.10963**Alex Havrilla, Sharath Raparthy, Christoforus Nalmpantis, et al.*2024 · 45 citations*](https://md.research.elamur.ai/free/en/papers/havrilla-2024-glore-where-improve-llm-reasoning/)
56. [**Aligning Language Models with Preferences through f-divergence Minimization arXiv:2302.08215**Dongyoung Go, Tomasz Korbak, German Kruszewski, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/go-2023-aligning-language-models-preferences-through/)
57. **[Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluation](https://md.research.elamur.ai/free/en/papers/wang-2025-benchmark-self-evolving-multi-agent/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Siyuan Wang, Zhuohan Long, Zhihao Fan, et al.*2025 · 30 citations*
58. **[ProxyQA: An Alternative Framework for Evaluating Long-Form Text Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/tan-2024-proxyqa-alternative-framework-evaluating-long/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haochen Tan, Zhijiang Guo, Zhan Shi, et al.*2024 · 30 citations*
59. **[M-RewardBench: Evaluating Reward Models in Multilingual Settings](https://md.research.elamur.ai/free/en/papers/gureja-2025-m-rewardbench-evaluating-reward-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Srishti Gureja, Lester James V. Miranda, Shayekh Bin Islam, et al.*2025 · 28 citations*
60. **[Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Above](https://md.research.elamur.ai/free/en/papers/balepur-2025-which-these-best-describes-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Rachel Rudinger, Jordan Boyd-Graber*2025 · 28 citations*
61. **[Separating Tongue from Thought: Activation Patching Reveals Language-Agnostic Concept Representations in Transformers](https://md.research.elamur.ai/free/en/papers/dumas-2025-separating-tongue-thought-activation-patching/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Clément Dumas, Chris Wendler, Veniamin Veselovsky, et al.*2025 · 27 citations*
62. [**LLM-as-a-Judge & Reward Model: What They Can and Cannot Do arXiv:2409.11239**Guijin Son, Hyunwoo Ko, Hoyoung Lee, et al.*2024 · 27 citations*](https://md.research.elamur.ai/free/en/papers/son-2024-llm-judge-reward-model-they/)
63. **[Linguistic Generalizability of Test-Time Scaling in Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/son-2025-linguistic-generalizability-test-time-scaling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guijin Son, Jiwoo Hong, Hyunwoo Ko, et al.*2025 · 24 citations*
64. **[CodeTree: Agent-guided Tree Search for Code Generation with Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2025-codetree-agent-guided-tree-search/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jierui Li, Hung Le, Yingbo Zhou, et al.*2025 · 21 citations*
65. [**CamelEval: Advancing Culturally Aligned Arabic Language Models and Benchmarks arXiv:2409.12623**Zhaozhi Qian, Faroq Altam, Muhammad Alqurishi, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/qian-2024-cameleval-advancing-culturally-aligned-arabic/)
66. **[DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph](https://md.research.elamur.ai/free/en/papers/zhang-2024-darg-dynamic-evaluation-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhehao Zhang, Jiaao Chen, Diyi Yang*2024 · 17 citations*
67. **[Towards Data Contamination Detection for Modern Large Language Models: Limitations, Inconsistencies, and Oracle Challenges](https://md.research.elamur.ai/free/en/papers/samuel-2025-data-contamination-detection-modern-large/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Vinay Samuel, Yue Zhou, Henry Peng Zou*2025 · 16 citations*
68. **[Analyzing and Adapting Large Language Models for Few-Shot Multilingual NLU: Are We There Yet?](https://md.research.elamur.ai/free/en/papers/razumovskaia-2025-analyzing-adapting-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Evgeniia Razumovskaia, Ivan Vulić, Anna Korhonen*2025 · 15 citations*
69. **[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*
70. **[On The Origin of Cultural Biases in Language Models: From Pre-training Data to Linguistic Phenomena](https://md.research.elamur.ai/free/en/papers/naous-2025-origin-cultural-biases-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tarek Naous, Wei Xu*2025 · 15 citations*
71. [**WorldSense: A Synthetic Benchmark for Grounded Reasoning in Large Language Models arXiv:2311.15930**Youssef Benchekroun, Megi Dervishi, Mark Ibrahim, et al.*2023 · 15 citations*](https://md.research.elamur.ai/free/en/papers/benchekroun-2023-worldsense-synthetic-benchmark-grounded-reasoning/)
72. **[Parity-Aware Byte-Pair Encoding: Improving Cross-lingual Fairness in Tokenization](https://md.research.elamur.ai/free/en/papers/foroutan-2026-parity-aware-byte-pair-encoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Negar Foroutan, Clara Meister, Debjit Paul, et al.*2026 · 12 citations*
73. [**Multilingual Arbitrage: Optimizing Data Pools to Accelerate Multilingual Progress arXiv:2408.14960**Ayomide Odumakinde, Daniel D'souza, Pat Verga, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/odumakinde-2024-multilingual-arbitrage-optimizing-data-pools/)
74. [**Aligning Large Language Models with Human Opinions through Persona Selection and Value — Belief — Norm Reasoning arXiv:2311.08385**Do Xuan Long, Kenji Kawaguchi, Min-Yen Kan, et al.*2023 · 12 citations*](https://md.research.elamur.ai/free/en/papers/long-2023-aligning-large-language-models-human/)
75. **[SSR-Zero: Simple Self-Rewarding Reinforcement Learning for Machine Translation](https://md.research.elamur.ai/free/en/papers/yang-2026-ssr-zero-simple-self-rewarding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenjie Yang, Mao Zheng, Mingyang Song, et al.*2026 · 10 citations*
76. **[Multiple LLM Agents Debate for Equitable Cultural Alignment](https://md.research.elamur.ai/free/en/papers/ki-2025-multiple-llm-agents-debate-equitable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dayeon Ki, Rachel Rudinger, Tianyi Zhou, et al.*2025 · 10 citations*
77. **[Too Late to Train, Too Early To Use? A Study on Necessity and Viability of Low-Resource Bengali LLMs](https://md.research.elamur.ai/free/en/papers/mahfuz-2025-too-late-train-too-early/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tamzeed Mahfuz, Satak Kumar Dey, Ruwad Naswan, et al.*2025 · 10 citations*
78. **[MTR-Bench: A Comprehensive Benchmark for Multi-Turn Reasoning Evaluation](https://md.research.elamur.ai/free/en/papers/li-2026-mtr-bench-comprehensive-benchmark-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyuan Li, Keqin Bao, Yubo Ma, et al.*2026 · 9 citations*
79. **[Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model](https://md.research.elamur.ai/free/en/papers/geigle-2025-centurio-drivers-multilingual-ability-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gregor Geigle, Florian Schneider, Carolin Holtermann, et al.*2025 · 9 citations*
80. **[Steering into New Embedding Spaces: Analyzing Cross-Lingual Alignment Induced by Model Interventions in Multilingual Language Models](https://md.research.elamur.ai/free/en/papers/sundar-2025-steering-into-new-embedding-spaces/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anirudh Sundar, Sinead Williamson, Katherine Metcalf, et al.*2025 · 9 citations*
81. **[The Translation Barrier Hypothesis: Multilingual Generation with Large Language Models Suffers from Implicit Translation Failure](https://md.research.elamur.ai/free/en/papers/bafna-2025-translation-barrier-hypothesis-multilingual-generation/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Niyati Bafna, Tianjian Li, Kenton Murray, et al.*2025 · 7 citations*
82. **[WiCkeD: A Simple Method to Make Multiple Choice Benchmarks More Challenging](https://md.research.elamur.ai/free/en/papers/elhady-2025-wicked-simple-method-make-multiple/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ahmed Elhady, Eneko Agirre, Mikel Artetxe*2025 · 7 citations*
83. **[Evaluating RAG Pipelines for Arabic Lexical Information Retrieval: A Comparative Study of Embedding and Generation Models](https://md.research.elamur.ai/free/en/papers/rasheed-2025-evaluating-rag-pipelines-arabic-lexical/) [Workshop on NLP for Languages Using Arabic Script](https://md.research.elamur.ai/free/en/venues/abjadnlp/)**Raghad Al-Rasheed, Abdullah Al Muaddi, Hawra Aljasim, et al.*2025 · 6 citations*
84. **[CoNLL#: Fine-grained Error Analysis and a Corrected Test Set for CoNLL-03 English](https://md.research.elamur.ai/free/en/papers/rueda-2024-conll-fine-grained-error-analysis/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Andrew Rueda, Elena Alvarez-Mellado, Constantine Lignos*2024 · 6 citations*
85. **[Automatic Reviewers Fail to Detect Faulty Reasoning in Research Papers: A New Counterfactual Evaluation Framework](https://md.research.elamur.ai/free/en/papers/dycke-2026-automatic-reviewers-fail-detect-faulty/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nils Dycke, Iryna Gurevych*2026 · 5 citations*
86. **[Detecting Training Data of Large Language Models via Expectation Maximization](https://md.research.elamur.ai/free/en/papers/kim-2026-detecting-training-data-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Gyuwan Kim, Yang Li, Evangelia Spiliopoulou, et al.*2026 · 5 citations*
87. **[Paramanu: Compact and Competitive Monolingual Language Models for Low-Resource Morphologically Rich Indian Languages](https://md.research.elamur.ai/free/en/papers/niyogi-2026-paramanu-compact-competitive-monolingual-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mitodru Niyogi, Eric Gaussier, Arnab Bhattacharya*2026 · 5 citations*
88. **[LLMs can Perform Multi-Dimensional Analytic Writing Assessments: A Case Study of L2 Graduate-Level Academic English Writing](https://md.research.elamur.ai/free/en/papers/wang-2025-llms-can-perform-multi-dimensional/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhengxiang Wang, Veronika Makarova, Zhi Li, et al.*2025 · 5 citations*
89. **[Spotlight Your Instructions: Instruction-following with Dynamic Attention Steering](https://md.research.elamur.ai/free/en/papers/venkateswaran-2026-spotlight-your-instructions-instruction-following/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Praveen Venkateswaran, Danish Contractor*2026 · 4 citations*
90. **[VN-MTEB: Vietnamese Massive Text Embedding Benchmark](https://md.research.elamur.ai/free/en/papers/pham-2026-vn-mteb-vietnamese-massive-text/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Loc Pham, Tung Luu, Thu Vo, et al.*2026 · 4 citations*
91. **[MELABenchv1: Benchmarking Large Language Models against Smaller Fine-Tuned Models for Low-Resource Maltese NLP](https://md.research.elamur.ai/free/en/papers/micallef-2025-melabenchv1-benchmarking-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kurt Micallef, Claudia Borg*2025 · 4 citations*
92. **[EngiBench: A Benchmark for Evaluating Large Language Models on Engineering Problem Solving](https://md.research.elamur.ai/free/en/papers/zhou-2026-engibench-benchmark-evaluating-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiyuan Zhou, Xinlei Wang, Yirui He, et al.*2026 · 3 citations*
93. [**Sadeed: Advancing Arabic Diacritization Through Small Language Model arXiv:2504.21635**Zeina Aldallal, Sara Chrouf, Khalil Hennara, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/aldallal-2025-sadeed-advancing-arabic-diacritization-through/)
94. **[Testing Low-Resource Language Support in LLMs Using Language Proficiency Exams: the Case of Luxembourgish](https://md.research.elamur.ai/free/en/papers/lothritz-2025-testing-low-resource-language-support/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cedric Lothritz, Jordi Cabot, Laura Bernardy*2025 · 3 citations*
95. **[Improving Romanian LLM Pretraining Data using Diversity and Quality Filtering](https://md.research.elamur.ai/free/en/papers/negoita-2026-improving-romanian-llm-pretraining-data/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Vlad-Andrei Negoiță, Mihai Masala, Traian Rebedea*2026 · 2 citations*
96. **[LiveFact: A Dynamic, Time-Aware Benchmark for LLM-Driven Fake News Detection](https://md.research.elamur.ai/free/en/papers/xu-2026-livefact-dynamic-time-aware-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cheng Xu, Changhong Jin, Yingjie Niu, et al.*2026 · 2 citations*
97. **[MERLIN: A Testbed for Multilingual Multimodal Entity Recognition and Linking](https://md.research.elamur.ai/free/en/papers/ramamoorthy-2026-merlin-testbed-multilingual-multimodal-entity/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Sathyanarayanan Ramamoorthy, Vishwa Shah, Simran Khanuja, et al.*2026 · 2 citations*
98. **[Aligned Probing: Relating Toxic Behavior and Model Internals](https://md.research.elamur.ai/free/en/papers/waldis-2026-aligned-probing-relating-toxic-behavior/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Andreas Waldis, Vagrant Gautam, Anne Lauscher, et al.*2026 · 1 citation*
99. **[Can you map it to English? The Role of Cross-Lingual Alignment in the Multilingual Performance of LLMs](https://md.research.elamur.ai/free/en/papers/ravisankar-2026-can-you-map-it-english/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kartik Ravisankar, HyoJung Han, Sarah Wiegreffe, et al.*2026 · 1 citation*
100. **[Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language Models](https://md.research.elamur.ai/free/en/papers/yin-2026-decentralized-arena-democratic-scalable-automatic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yanbin Yin, Kun Zhou, Zhen Wang, et al.*2026 · 1 citation*

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

- [← back to](https://md.research.elamur.ai/free/en/authors/jon-ander-campos/) — Jon Ander Campos