---
title: "Who cites Thomas Hartvigsen — 384 papers of our library"
description: "384 papers of the Elamur Research library cite the works of Thomas Hartvigsen, found in their bibliographies · page 1 of 2 · 1–100; the most…"
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---
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# Who cites Thomas Hartvigsen

387 citations of their works from 384 papers of our library (of the 149,439 whose bibliographies we read) · 108 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Thomas Hartvigsen](https://md.research.elamur.ai/free/en/authors/thomas-hartvigsen/)

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1. [**Llama 2: Open Foundation and Fine-Tuned Chat Models arXiv:2307.09288**Hugo Touvron, Louis Martin, Kevin Stone, et al.*2023 · 9,669 citations*](https://md.research.elamur.ai/free/en/papers/touvron-2023-llama-2-open-foundation-fine/)
2. [**The Llama 3 Herd of Models arXiv:2407.21783**Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.*2024 · 7,682 citations*](https://md.research.elamur.ai/free/en/papers/grattafiori-2024-llama-3-herd-models/)
3. [**Code Llama: Open Foundation Models for Code arXiv:2308.12950**Baptiste Rozière, Jonas Gehring, Fabian Gloeckle, et al.*2024 · 1,430 citations*](https://md.research.elamur.ai/free/en/papers/roziere-2024-code-llama-open-foundation-models/)
4. [**Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection arXiv:2310.11511**Akari Asai, Zeqiu Wu, Yizhong Wang, et al.*2023 · 677 citations*](https://md.research.elamur.ai/free/en/papers/asai-2023-self-rag-learning-retrieve-generate/)
5. **[AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models](https://md.research.elamur.ai/free/en/papers/zhong-2024-agieval-human-centric-benchmark-evaluating/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wanjun Zhong, Ruixiang Cui, Yiduo Guo, et al.*2024 · 575 citations*
6. [**Baichuan 2: Open Large-scale Language Models arXiv:2309.10305**Aiyuan Yang, Bin Xiao, Bingning Wang, et al.*2023 · 517 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-baichuan-2-open-large-scale/)
7. **[BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 409 citations*
8. [**Orca: Progressive Learning from Complex Explanation Traces of GPT-4 arXiv:2306.02707**Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, et al.*2023 · 369 citations*](https://md.research.elamur.ai/free/en/papers/mukherjee-2023-orca-progressive-learning-complex-explanation/)
9. [**Textbooks Are All You Need II: phi-1.5 technical report arXiv:2309.05463**Yuanzhi Li, Sébastien Bubeck, Ronen Eldan, et al.*2023 · 336 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-textbooks-all-need-ii-phi/)
10. [**Discovering Language Model Behaviors with Model-Written Evaluations arXiv:2212.09251**Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.*2022 · 328 citations*](https://md.research.elamur.ai/free/en/papers/perez-2022-discovering-language-model-behaviors-model/)
11. **[How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources](https://md.research.elamur.ai/free/en/papers/wang-2023-far-camels-go-exploring-state/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yizhong Wang, Hamish Ivison, Pradeep Dasigi, et al.*2023 · 317 citations*
12. [**MEDITRON-70B: Scaling Medical Pretraining for Large Language Models arXiv:2311.16079**Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.*2023 · 315 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-meditron-70b-scaling-medical-pretraining/)
13. [**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/)
14. [**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/)
15. [**Towards Measuring the Representation of Subjective Global Opinions in Language Models arXiv:2306.16388**Esin Durmus, Karina Nguyen, Thomas I. Liao, et al.*2023 · 270 citations*](https://md.research.elamur.ai/free/en/papers/durmus-2023-towards-measuring-representation-subjective-global/)
16. **[A Holistic Approach to Undesired Content Detection in the Real World](https://md.research.elamur.ai/free/en/papers/markov-2022-holistic-approach-undesired-content-detection/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Todor Markov, Chong Zhang, Sandhini Agarwal, et al.*2022 · 263 citations*
17. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
18. [**XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models arXiv:2308.01263**Paul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.*2023 · 244 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2023-xstest-test-suite-identifying-exaggerated/)
19. **[Synthetic Data Generation with Large Language Models for Text Classification: Potential and Limitations](https://md.research.elamur.ai/free/en/papers/li-2023-synthetic-data-generation-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhuoyan Li, Hangxiao Zhu, Zhuoran Lu, et al.*2023 · 242 citations*
20. **[Visual Adversarial Examples Jailbreak Aligned Large Language Models](https://md.research.elamur.ai/free/en/papers/qi-2023-visual-adversarial-examples-jailbreak-aligned/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Xiangyu Qi, Kaixuan Huang, Ashwinee Panda, et al.*2023 · 240 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. [**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/)
23. **[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*
24. [**Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2 arXiv:2311.10702**Hamish Ivison, Yizhong Wang, Valentina Pyatkin, et al.*2023 · 207 citations*](https://md.research.elamur.ai/free/en/papers/ivison-2023-camels-changing-climate-enhancing-lm/)
25. [**Multilingual Jailbreak Challenges in Large Language Models arXiv:2310.06474**Yue Deng, Wenxuan Zhang, Sinno Jialin Pan, et al.*2023 · 192 citations*](https://md.research.elamur.ai/free/en/papers/deng-2023-multilingual-jailbreak-challenges-large-language/)
26. [**Effective Long-Context Scaling of Foundation Models arXiv:2309.16039**Wenhan Xiong, Jingyu Liu, Igor Molybog, et al.*2023 · 184 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-effective-long-context-scaling-foundation/)
27. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
28. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
29. [**SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks arXiv:2310.03684**Alexander Robey, Eric Wong, Hamed Hassani, et al.*2023 · 164 citations*](https://md.research.elamur.ai/free/en/papers/robey-2023-smoothllm-defending-large-language-models/)
30. [**Orca 2: Teaching Small Language Models How to Reason arXiv:2311.11045**Arindam Mitra, Luciano Del Corro, Shweti Mahajan, et al.*2023 · 162 citations*](https://md.research.elamur.ai/free/en/papers/mitra-2023-orca-2-teaching-small-language/)
31. **[MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2023-mm-safetybench-benchmark-safety-evaluation/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Xin Liu, Yichen Zhu, Jindong Gu, et al.*2023 · 152 citations*
32. **[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*
33. **[Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions](https://md.research.elamur.ai/free/en/papers/chung-2023-increasing-diversity-while-maintaining-accuracy/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**John Chung, Ece Kamar, Saleema Amershi*2023 · 144 citations*
34. [**A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence Generation arXiv:2307.03987**Neeraj Varshney; Wenlin Yao; Hongming Zhang; Jianshu Chen;, Dong Yu*2023 · 143 citations*](https://md.research.elamur.ai/free/en/papers/varshney-2023-stitch-time-saves-nine-detecting/)
35. **[ToxicChat: Unveiling Hidden Challenges of Toxicity Detection in Real-World User-AI Conversation](https://md.research.elamur.ai/free/en/papers/lin-2023-toxicchat-unveiling-hidden-challenges-toxicity/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zi Lin, Zihan Wang, Yongqi Tong, et al.*2023 · 136 citations*
36. **[Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset](https://md.research.elamur.ai/free/en/papers/henderson-2022-pile-law-learning-responsible-data/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Peter Henderson, Mark S. Krass, Lucia Zheng, et al.*2022 · 133 citations*
37. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 130 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
38. [**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/)
39. **[SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-salad-bench-hierarchical-comprehensive-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lijun Li, Bowen Dong, Ruohui Wang, et al.*2024 · 119 citations*
40. [**Can LLM-Generated Misinformation Be Detected? arXiv:2309.13788**Canyu Chen, Kai Shu*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-llm-generated-misinformation-detected/)
41. [**A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity arXiv:2305.13169**Shayne Longpre, Gregory Yauney, Emily Reif, et al.*2023 · 104 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-pretrainer-s-guide-training-data/)
42. [**Shadow Alignment: The Ease of Subverting Safely-Aligned Language Models arXiv:2310.02949**Xianjun Yang, Xiao Wang, Qi Zhang, et al.*2023 · 103 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-shadow-alignment-ease-subverting-safely/)
43. **[Not All Countries Celebrate Thanksgiving: On the Cultural Dominance in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-not-all-countries-celebrate-thanksgiving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenxuan Wang, Wenxiang Jiao, Jingyuan Huang, et al.*2024 · 96 citations*
44. **[Do-Not-Answer: Evaluating Safeguards in LLMs](https://md.research.elamur.ai/free/en/papers/wang-2024-do-not-answer-evaluating-safeguards/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxia Wang, Haonan Li, Xudong Han, et al.*2024 · 93 citations*
45. [**Tuning Language Models by Proxy arXiv:2401.08565**Alisa Liu, Xiaochuang Han, Yizhong Wang, et al.*2024 · 79 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-tuning-language-models-proxy/)
46. [**Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMs arXiv:2308.13387**Yuxia Wang, Haonan Li, Xudong Han, et al.*2023 · 78 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-answer-dataset-evaluating-safeguards-llms/)
47. [**OR-Bench: An Over-Refusal Benchmark for Large Language Models arXiv:2405.20947**Justin Cui, Wei-Lin Chiang, Ion Stoica, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/cui-2024-bench-over-refusal-benchmark-large/)
48. **[Unveiling the Implicit Toxicity in Large Language Models](https://md.research.elamur.ai/free/en/papers/wen-2023-unveiling-implicit-toxicity-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiaxin Wen, Pei Ke, Hao Sun, et al.*2023 · 72 citations*
49. **[Sensitivity, Performance, Robustness: Deconstructing the Effect of Sociodemographic Prompting](https://md.research.elamur.ai/free/en/papers/beck-2024-sensitivity-performance-robustness-deconstructing-effect/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tilman Beck, Hendrik Schuff, Anne Lauscher, et al.*2024 · 69 citations*
50. [**Phi-4-reasoning Technical Report arXiv:2504.21318**Marah Abdin, Sahaj Agarwal, Ahmed Awadallah, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2025-phi-4-reasoning-technical-report/)
51. [**RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and Style arXiv:2410.16184**Yantao Liu, Zijun Yao, Rui Min, et al.*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-rm-bench-benchmarking-reward-models/)
52. **[Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback](https://md.research.elamur.ai/free/en/papers/ivison-2024-unpacking-dpo-ppo-disentangling-best/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hamish Ivison, Yizhong Wang, Jiacheng Liu, et al.*2024 · 50 citations*
53. **[FLIRT: Feedback Loop In-context Red Teaming](https://md.research.elamur.ai/free/en/papers/mehrabi-2024-flirt-feedback-loop-context-red/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ninareh Mehrabi, Palash Goyal, Christophe Dupuy, et al.*2024 · 42 citations*
54. [**SimpleSafetyTests: a Test Suite for Identifying Critical Safety Risks in Large Language Models arXiv:2311.08370**Bertie Vidgen, Nino Scherrer, Hannah Rose Kirk, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2023-simplesafetytests-test-suite-identifying-critical/)
55. **[Aligning Large Language Models with Human Preferences through Representation Engineering](https://md.research.elamur.ai/free/en/papers/liu-2024-aligning-large-language-models-human/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenhao Liu, Xiaohua Wang, Muling Wu, et al.*2024 · 37 citations*
56. [**SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety arXiv:2404.05399**Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-safetyprompts-systematic-review-open-datasets/)
57. [**Interpretable Unified Language Checking arXiv:2304.03728**Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-interpretable-unified-language-checking/)
58. **[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*
59. [**NeoBERT: A Next-Generation BERT arXiv:2502.19587**Lola Le Breton, Quentin Fournier, Mariam El Mezouar, et al.*2025 · 20 citations*](https://md.research.elamur.ai/free/en/papers/breton-2025-neobert-next-generation-bert/)
60. **[Unlocking General Long Chain-of-Thought Reasoning Capabilities of Large Language Models via Representation Engineering](https://md.research.elamur.ai/free/en/papers/tang-2025-unlocking-general-long-chain-thought/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Tang, Xiaolei Wang, Zhihao Lv, et al.*2025 · 19 citations*
61. [**An Empirical Study of Metrics to Measure Representational Harms in Pre-Trained Language Models arXiv:2301.09211**Saghar Hosseini, Hamid Palangi, Ahmed Hassan Awadallah*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-2023-empirical-study-metrics-measure-representational/)
62. **[A Survey on Efficient Large Language Model Training: From Data-centric Perspectives](https://md.research.elamur.ai/free/en/papers/luo-2025-survey-efficient-large-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyu Luo, Bohan Wu, Xiao Luo, et al.*2025 · 14 citations*
63. [**Phi-3 Safety Post-Training: Aligning Language Models with a "Break-Fix" Cycle arXiv:2407.13833**Emman Haider, Daniel Perez-Becker, Thomas Portet, et al.*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/haider-2024-phi-3-safety-post-training/)
64. **[from Benign import Toxic: Jailbreaking the Language Model via Adversarial Metaphors](https://md.research.elamur.ai/free/en/papers/yan-2025-benign-import-toxic-jailbreaking-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Yan, Sheng Sun, Zenghao Duan, et al.*2025 · 12 citations*
65. **[Feature Extraction and Steering for Enhanced Chain-of-Thought Reasoning in Language Models](https://md.research.elamur.ai/free/en/papers/li-2025-feature-extraction-steering-enhanced-chain/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zihao Li, Xu Wang, Yuzhe Yang, et al.*2025 · 11 citations*
66. **[Multi-Attribute Steering of Language Models via Targeted Intervention](https://md.research.elamur.ai/free/en/papers/nguyen-2025-multi-attribute-steering-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Duy Nguyen, Archiki Prasad, Elias Stengel-Eskin, et al.*2025 · 11 citations*
67. **[Pragmatic Inference Chain (PIC) Improving LLMs' Reasoning of Authentic Implicit Toxic Language](https://md.research.elamur.ai/free/en/papers/chen-2025-pragmatic-inference-chain-pic-improving/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xi Chen, Shuo Wang*2025 · 9 citations*
68. **[AraSafe: Benchmarking Safety in Arabic LLMs](https://md.research.elamur.ai/free/en/papers/mubarak-2025-arasafe-benchmarking-safety-arabic-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hamdy Mubarak, Abubakr Mohamed, Majd Hawasly*2025 · 6 citations*
69. **[GrAInS: Gradient-based Attribution for Inference-Time Steering of LLMs and VLMs](https://md.research.elamur.ai/free/en/papers/nguyen-2026-grains-gradient-based-attribution-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Duy Nguyen, Archiki Prasad, Elias Stengel-Eskin, et al.*2026 · 4 citations*
70. **[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*
71. **[A Survey of Machine Learning Models and Datasets for the Multi-label Classification of Textual Hate Speech in English](https://md.research.elamur.ai/free/en/papers/baumler-2025-survey-machine-learning-models-datasets/) [ACM Transactions on Knowledge Discovery from Data](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-knowledge-discovery-from-data/)**Julian Baumler, Louis Blocher, Lars-Joel Frey, et al.*2025 · 4 citations*
72. **[Model Misalignment and Language Change: Traces of AI-Associated Language in Unscripted Spoken English](https://md.research.elamur.ai/free/en/papers/anderson-2025-model-misalignment-language-change-traces/) [Proceedings of the AAAI/ACM Conference on AI Ethics and Society](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-acm-conference-on-ai-ethics-and-society/)**Bryce Anderson, Riley Galpin, Tom S. Juzek*2025 · 4 citations*
73. [**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/)
74. [**Toxic language detection: a systematic review of Arabic datasets arXiv:2312.07228**Imene Bensalem, Paolo Rosso, Hanane Zitouni*2023 · 4 citations*](https://md.research.elamur.ai/free/en/papers/bensalem-2023-toxic-language-detection-systematic-review/)
75. **[STReasoner: Empowering LLMs for Spatio-Temporal Reasoning in Time Series via Spatial-Aware Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/ni-2026-streasoner-empowering-llms-spatio-temporal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Juntong Ni, Shiyu Wang, Qi He, et al.*2026 · 3 citations*
76. **[Trans-EnV: A Framework for Evaluating the Linguistic Robustness of LLMs Against English Varieties](https://md.research.elamur.ai/free/en/papers/lee-2025-trans-env-framework-evaluating-linguistic/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiyoung Lee, Seungho Kim, Jieun Han, et al.*2025 · 3 citations*
77. **[A Survey on Combating Hate Speech through Detection and Prevention in English](https://md.research.elamur.ai/free/en/papers/kapil-2024-survey-combating-hate-speech-through/) [International Conference on Natural Language Processing (ICON)](https://md.research.elamur.ai/free/en/venues/icon/)**Prashant Kapil, Asif Ekbal*2024 · 3 citations*
78. **[Argument-Based Consistency in Toxicity Explanations of LLMs](https://md.research.elamur.ai/free/en/papers/mothilal-2026-argument-based-consistency-toxicity-explanations/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ramaravind Kommiya Mothilal, Joanna Roy, Syed Ishtiaque Ahmed, et al.*2026 · 2 citations*
79. **[KZ-SafetyPrompts: A Kazakh Safety Evaluation Prompt Dataset for Large Language Models](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-kz-safetyprompts-kazakh-safety-evaluation/) [SIGUL Joint Workshop with ELE, EURALI, and DCLRL: Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered Languages](https://md.research.elamur.ai/free/en/venues/sigul/)**Wajdi Zaghouani, Shimaa Amer Ibrahim, Aruzhan Muratbek, et al.*2026 · 2 citations*
80. **[Red-Bandit: Test-Time Adaptation for LLM Red-Teaming via Bandit-Guided LoRA Experts](https://md.research.elamur.ai/free/en/papers/ziakas-2026-red-bandit-test-time-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Christos Ziakas, Nicholas Loo, Nishita Jain, et al.*2026 · 2 citations*
81. **[AlbanianLLMSafety: A Safety Evaluation Dataset for Large Language Models in Albanian](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-albanianllmsafety-safety-evaluation-dataset-large/) [SIGUL Joint Workshop with ELE, EURALI, and DCLRL: Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered Languages](https://md.research.elamur.ai/free/en/venues/sigul/)**Wajdi Zaghouani, Kholoud Khalil Aldous, Isra Fejzullaj*2026 · 1 citation*
82. **[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*
83. [**ArabicDialectSafety: A Dialect-Aware Benchmark for Arabic Content Safety Classification arXiv:2608.01291 · EMNLP 2026 Findings**Wajdi Zaghouani, Md. Rafiul Biswas, Kholoud Khalil Aldous, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-arabicdialectsafety-dialect-aware-benchmark-arabic/)
84. [**The Hrunting of AI: Where and How to Improve English Dialectal Fairness arXiv:2603.15187**Wei Li, Adrian de Wynter*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/li-2026-hrunting-ai-where-improve-english/)
85. [**Safe at the Margins: A General Approach to Safety Alignment in Low-Resource English Languages — A Singlish Case Study arXiv:2502.12485**Isaac Lim, Shaun Khoo, Roy Ka-Wei Lee, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/lim-2025-safe-margins-general-approach-safety/)
86. **[A Layer-wise Analysis of Supervised Fine-Tuning](https://md.research.elamur.ai/free/en/papers/zhao-2026-layer-wise-analysis-supervised-fine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qinghua Zhao, Xueling Gong, Xinyu Chen, et al.*2026*
87. **[AnswerCarefully: Creating a Dataset for LLM Safety in Japanese](https://md.research.elamur.ai/free/en/papers/suzuki-2026-answercarefully-creating-dataset-llm-safety/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Hisami Suzuki, Satoru Katsumata, Takashi Kodama, et al.*2026*
88. **[Can LLMs Reason Like Doctors? Exploring the Limits of Large Language Models in Complex Medical Reasoning](https://md.research.elamur.ai/free/en/papers/merenda-2026-can-llms-reason-like-doctors/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Flavio Merenda, Jose Manuel Gomez-Perez, German Rigau*2026*
89. **[CausalDetox: Causal Head Selection and Intervention for Language Model Detoxification](https://md.research.elamur.ai/free/en/papers/wang-2026-causaldetox-causal-head-selection-intervention/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yian Wang, Yuen Chen, Agam Goyal, et al.*2026*
90. **[DART: Mitigating Harm Drift in Difference-Aware LLMs via Distill-Audit-Repair Training](https://md.research.elamur.ai/free/en/papers/pan-2026-dart-mitigating-harm-drift-difference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ziwen Pan, Zihan Liang, Jad Kabbara, et al.*2026*
91. **[Detoxification for LLM: From Dataset Itself](https://md.research.elamur.ai/free/en/papers/shao-2026-detoxification-llm-dataset-itself/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Shao, Yihang Wang, Gao yu Zhu, et al.*2026*
92. **[DIA-HARM: Dialectal Disparities in Harmful Content Detection Across 50 English Dialects](https://md.research.elamur.ai/free/en/papers/lucas-2026-dia-harm-dialectal-disparities-harmful/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jason S Lucas, Matt Murtagh White, Ali Al-Lawati, et al.*2026*
93. **[Evaluating LLMs for Detecting Demographic-Targeted Social Bias: A Comprehensive Benchmark Study](https://md.research.elamur.ai/free/en/papers/majumdar-2026-evaluating-llms-detecting-demographic-targeted/) [Workshop of Identity Aware AI](https://md.research.elamur.ai/free/en/venues/iaai/)**Ayan Majumdar, Feihao Chen, Jinghui Li, et al.*2026*
94. [**Evaluating the Usage of African-American Vernacular English in Large Language Models arXiv:2602.21485**Deja Dunlap, R. Thomas McCoy*2026*](https://md.research.elamur.ai/free/en/papers/dunlap-2026-evaluating-usage-african-american-vernacular/)
95. **[Explainable AI for Ethical Counter Speech Generation in Hate Speech Mitigation](https://md.research.elamur.ai/free/en/papers/ridoy-2026-explainable-ai-ethical-counter-speech/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ashiful Islam Ridoy, Mohammed Faisal, Yogesh Kumar, et al.*2026*
96. **[From Fake to Real: Mitigating Out-of-Distribution Bias in In-Context Learning via Feedback Supervision from Large Language Models](https://md.research.elamur.ai/free/en/papers/song-2026-fake-real-mitigating-out-distribution/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Song, Yingji Li, Jian Li, et al.*2026*
97. **[HatePrototypes: Interpretable and Transferable Representations for Implicit and Explicit Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/proskurina-2026-hateprototypes-interpretable-transferable-representations-implicit/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Irina Proskurina, Marc-Antoine Carpentier, Julien Velcin*2026*
98. **[Implicit Bias in Peer Review: Through the Lens of Language Abstraction](https://md.research.elamur.ai/free/en/papers/zhang-2026-implicit-bias-peer-review-through/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Xulang Zhang, Rui Mao, Erik Cambria*2026*
99. **[IndicSteer: Inference-Time Safety Steering for Indic LLMs](https://md.research.elamur.ai/free/en/papers/muhammad-2026-indicsteer-inference-time-safety-steering/) [Workshop on Stereotypes Across Cultures in Language Technologies](https://md.research.elamur.ai/free/en/venues/stereacult/)**Ruhaib Muhammad, Saahas Vijayalakshmi Rajaram, Suriya Priyan Durairaj*2026*
100. [**Individual and Combined Effects of English as a Second Language and Typos on LLM Performance arXiv:2604.04723**Serena Liu; Yutong Yang; Prisha Sheth; Weixuan Dong; Mingjiao Diao; Xinru Zhu; Nikhil Banga; Oscar Melendez; Arnav Sharma; Minda Zhao; Marina Lin;, Mengyu Wang*2026*](https://md.research.elamur.ai/free/en/papers/liu-2026-individual-combined-effects-english-second/)

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