---
title: "Who cites Joe Barrow — 536 papers of our library"
description: "536 papers of the Elamur Research library cite the works of Joe Barrow, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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# Who cites Joe Barrow

539 citations of their works from 536 papers of our library (of the 149,439 whose bibliographies we read) · 115 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Joe Barrow](https://md.research.elamur.ai/free/en/authors/joe-barrow/)

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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. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2023-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J. Ryan, Alan Ritter, et al.*2023 · 273 citations*
4. [**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/)
5. **[Can You Unpack That? Learning to Rewrite Questions-in-Context](https://md.research.elamur.ai/free/en/papers/elgohary-2019-can-you-unpack-that-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ahmed Elgohary, Denis Peskov, Jordan Boyd-Graber*2019 · 245 citations*
6. [**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/)
7. [**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/)
8. [**Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations arXiv:2310.06387**Zeming Wei, Yifei Wang, Ang Li, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-jailbreak-guard-aligned-language-models/)
9. **[SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware Decoding](https://md.research.elamur.ai/free/en/papers/xu-2024-safedecoding-defending-against-jailbreak-attacks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 127 citations*
10. **[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*
11. **[Defending Against Alignment-Breaking Attacks via Robustly Aligned LLM](https://md.research.elamur.ai/free/en/papers/cao-2024-defending-against-alignment-breaking-attacks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bochuan Cao, Yuanpu Cao, Lu Lin, et al.*2024 · 109 citations*
12. [**WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild arXiv:2406.04770**Bill Yuchen Lin, Yuntian Deng, Khyathi Chandu, et al.*2024 · 105 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-wildbench-benchmarking-llms-challenging-tasks/)
13. **[Towards Measuring and Modeling “Culture” in LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/adilazuarda-2024-measuring-modeling-culture-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Muhammad Farid Adilazuarda, Sagnik Mukherjee, Pradhyumna Lavania, et al.*2024 · 102 citations*
14. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2024-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J Ryan, Alan Ritter, et al.*2024 · 95 citations*
15. **[PKU-SafeRLHF: Towards Multi-Level Safety Alignment for LLMs with Human Preference](https://md.research.elamur.ai/free/en/papers/ji-2025-pku-saferlhf-multi-level-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaming Ji, Donghai Hong, Borong Zhang, et al.*2025 · 83 citations*
16. **[Judging the Judges: A Systematic Study of Position Bias in LLM-as-a-Judge](https://md.research.elamur.ai/free/en/papers/shi-2025-judging-judges-systematic-study-position/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Lin Shi, Chiyu Ma, Wenhua Liang, et al.*2025 · 71 citations*
17. **[Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2024-self-alignment-factuality-mitigating-hallucinations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoying Zhang, Baolin Peng, Ye Tian, et al.*2024 · 69 citations*
18. **[Bias in Large Language Models: Origin, Evaluation, and Mitigation](https://md.research.elamur.ai/free/en/papers/guo-2024-bias-large-language-models-origin/) [Electronics](https://md.research.elamur.ai/free/en/venues/electronics/)**Yufei Guo, Muzhe Guo, Juntao Su, et al.*2024 · 58 citations*
19. **[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*
20. **[In Prospect and Retrospect: Reflective Memory Management for Long-term Personalized Dialogue Agents](https://md.research.elamur.ai/free/en/papers/tan-2025-prospect-retrospect-reflective-memory-management/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Tan, Jun Yan, I-Hung Hsu, et al.*2025 · 46 citations*
21. **[Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perception](https://md.research.elamur.ai/free/en/papers/lin-2025-investigating-bias-llm-based-bias/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Luyang Lin, Lingzhi Wang, Jinsong Guo, et al.*2025 · 44 citations*
22. [**On the Diversity of Synthetic Data and its Impact on Training Large Language Models arXiv:2410.15226**Hao Chen, Abdul Waheed, Xiang Li, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-diversity-synthetic-data-impact-training/)
23. **[Benchmarking Linguistic Diversity of Large Language Models](https://md.research.elamur.ai/free/en/papers/guo-2025-benchmarking-linguistic-diversity-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yanzhu Guo, Guokan Shang, Chloé Clavel*2025 · 32 citations*
24. **[LLMs + Persona-Plug = Personalized LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-llms-persona-plug-personalized-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiongnan Liu, Yutao Zhu, Shuting Wang, et al.*2025 · 31 citations*
25. **[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*
26. **[The Hidden Risks of Large Reasoning Models: A Safety Assessment of R1](https://md.research.elamur.ai/free/en/papers/zhou-2025-hidden-risks-large-reasoning-models/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Kaiwen Zhou, Chengzhi Liu, Xuandong Zhao, et al.*2025 · 30 citations*
27. **[Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions](https://md.research.elamur.ai/free/en/papers/suh-2025-language-model-fine-tuning-scaled/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joseph Suh, Erfan Jahanparast, Suhong Moon, et al.*2025 · 28 citations*
28. **[MultiPICo: Multilingual Perspectivist Irony Corpus](https://md.research.elamur.ai/free/en/papers/casola-2024-multipico-multilingual-perspectivist-irony-corpus/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Silvia Casola, Simona Frenda, Soda Marem Lo, et al.*2024 · 28 citations*
29. **[Defense Against Prompt Injection Attack by Leveraging Attack Techniques](https://md.research.elamur.ai/free/en/papers/chen-2025-defense-against-prompt-injection-attack/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yulin Chen, Haoran Li, Zihao Zheng, et al.*2025 · 24 citations*
30. **[Personalized Generation In Large Model Era: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2025-personalized-generation-large-model-era/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiyan Xu, Jinghao Zhang, Alireza Salemi, et al.*2025 · 24 citations*
31. **[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*
32. **[From Selection to Generation: A Survey of LLM-based Active Learning](https://md.research.elamur.ai/free/en/papers/xia-2025-selection-generation-survey-llm-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie, et al.*2025 · 22 citations*
33. **[Conformity in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2025-conformity-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaochen Zhu, Caiqi Zhang, Tom Stafford, et al.*2025 · 18 citations*
34. **[LLMs know their vulnerabilities: Uncover Safety Gaps through Natural Distribution Shifts](https://md.research.elamur.ai/free/en/papers/ren-2025-llms-know-their-vulnerabilities-uncover/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qibing Ren, Hao Li, Dongrui Liu, et al.*2025 · 18 citations*
35. **[VerIF: Verification Engineering for Reinforcement Learning in Instruction Following](https://md.research.elamur.ai/free/en/papers/peng-2025-verif-verification-engineering-reinforcement-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.*2025 · 18 citations*
36. **[Revisiting Jailbreaking for Large Language Models: A Representation Engineering Perspective](https://md.research.elamur.ai/free/en/papers/li-2025-revisiting-jailbreaking-large-language-models/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tianlong Li, Zhenghua Wang, Wenhao Liu, et al.*2025 · 17 citations*
37. **[BasqBBQ: A QA Benchmark for Assessing Social Biases in LLMs for Basque, a Low-Resource Language](https://md.research.elamur.ai/free/en/papers/zulaika-2025-basqbbq-qa-benchmark-assessing-social/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Muitze Zulaika, Xabier Saralegi*2025 · 15 citations*
38. **[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*
39. **[When One LLM Drools, Multi-LLM Collaboration Rules](https://md.research.elamur.ai/free/en/papers/feng-2026-when-one-llm-drools-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangbin Feng, Wenxuan Ding, Alisa Liu, et al.*2026 · 14 citations*
40. **[Personalized Text Generation with Contrastive Activation Steering](https://md.research.elamur.ai/free/en/papers/zhang-2025-personalized-text-generation-contrastive-activation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinghao Zhang, Yuting Liu, Wenjie Wang, et al.*2025 · 13 citations*
41. **[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*
42. **[Latent Inter-User Difference Modeling for LLM Personalization](https://md.research.elamur.ai/free/en/papers/qiu-2025-latent-inter-user-difference-modeling/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yilun Qiu, Tianhao Shi, Xiaoyan Zhao, et al.*2025 · 12 citations*
43. **[Whose Boat Does it Float? Improving Personalization in Preference Tuning via Inferred User Personas](https://md.research.elamur.ai/free/en/papers/balepur-2025-whose-boat-does-it-float/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Vishakh Padmakumar, Fumeng Yang, et al.*2025 · 12 citations*
44. **[Grounding Multilingual Multimodal LLMs With Cultural Knowledge](https://md.research.elamur.ai/free/en/papers/nyandwi-2025-grounding-multilingual-multimodal-llms-cultural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jean De Dieu Nyandwi, Yueqi Song, Simran Khanuja, et al.*2025 · 11 citations*
45. **[Automated Progressive Red Teaming](https://md.research.elamur.ai/free/en/papers/jiang-2025-automated-progressive-red-teaming/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Bojian Jiang, Yi Jing, Tong Wu, et al.*2025 · 10 citations*
46. **[CIC-NLP at GenAI Detection Task 1: Leveraging DistilBERT for Detecting Machine-Generated Text in English](https://md.research.elamur.ai/free/en/papers/abiola-2025-cic-nlp-genai-detection-task-2025-genaidetect-1-29/) [1stWorkshop on GenAI Content Detection (GenAIDetect)](https://md.research.elamur.ai/free/en/venues/genaidetect/)**Tolulope Olalekan Abiola, Tewodros Achamaleh Bizuneh, Oluwatobi Joseph Abiola, et al.*2025 · 9 citations*
47. [**Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment arXiv:2501.13080**Melissa Kazemi Rad, Huy Nghiem, Andy Luo, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/rad-2025-refining-input-guardrails-enhancing-llm/)
48. **[Justice in Judgment: Unveiling (Hidden) Bias in LLM-assisted Peer Reviews](https://md.research.elamur.ai/free/en/papers/vasu-2026-justice-judgment-unveiling-hidden-bias/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sai Suresh Macharla Vasu, Ivaxi Sheth, Hui-Po Wang, et al.*2026 · 8 citations*
49. **[AI use in American newspapers is widespread, uneven, and rarely disclosed](https://md.research.elamur.ai/free/en/papers/russell-2026-ai-use-american-newspapers-is/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jenna Russell, Marzena Karpinska, Destiny Akinode, et al.*2026 · 7 citations*
50. **[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*
51. **[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*
52. **[Democratic or Authoritarian? Probing a New Dimension of Political Biases in Large Language Models](https://md.research.elamur.ai/free/en/papers/piedrahita-2026-democratic-or-authoritarian-probing-new/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**David Guzman Piedrahita, Irene Strauss, Rada Mihalcea, et al.*2026 · 3 citations*
53. **[Gender Disambiguation in Machine Translation: Diagnostic Evaluation in Decoder-Only Architectures](https://md.research.elamur.ai/free/en/papers/manna-2026-gender-disambiguation-machine-translation-diagnostic/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Chiara Manna, Hosein Mohebbi, Afra Alishahi, et al.*2026 · 3 citations*
54. **[How Quantization Shapes Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/marcuzzi-2026-how-quantization-shapes-bias-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Federico Marcuzzi, Xuefei Ning, Roy Schwartz, et al.*2026 · 3 citations*
55. **[Are LLMs Reliable Rankers? Rank Manipulation via Two-Stage Token Optimization](https://md.research.elamur.ai/free/en/papers/xing-2026-are-llms-reliable-rankers-rank/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tiancheng Xing, Jerry Li, Yixuan Du, et al.*2026 · 2 citations*
56. **[Attacker's Noise Can Manipulate Your Audio-based LLM in the Real World](https://md.research.elamur.ai/free/en/papers/sadasivan-2026-attacker-s-noise-can-manipulate/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Vinu Sankar Sadasivan, Soheil Feizi, Rajiv Mathews, et al.*2026 · 2 citations*
57. **[From Belief Entrenchment to Robust Reasoning in LLM Agents](https://md.research.elamur.ai/free/en/papers/oh-2026-belief-entrenchment-robust-reasoning-llm/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jihwan Oh, Minchan Jeong, Jongwoo Ko, et al.*2026 · 2 citations*
58. **[Instant Personalized Large Language Model Adaptation via Hypernetwork](https://md.research.elamur.ai/free/en/papers/tan-2026-instant-personalized-large-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhaoxuan Tan, Zixuan Zhang, Haoyang Wen, et al.*2026 · 2 citations*
59. **[Preconditioned Test-Time Adaptation for Out-of-Distribution Debiasing in Narrative Generation](https://md.research.elamur.ai/free/en/papers/shen-2026-preconditioned-test-time-adaptation-out/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanwen Shen, Ting Ying, Jiajie Lu, et al.*2026 · 2 citations*
60. **[Safe-SAIL: Towards a Fine-grained Safety Landscape of Large Language Models via Sparse Autoencoder Interpretation Framework](https://md.research.elamur.ai/free/en/papers/weng-2026-safe-sail-fine-grained-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiaqi Weng, Han Zheng, Hanyu Zhang, et al.*2026 · 2 citations*
61. **[A Survey on LLM-based Conversational User Simulation](https://md.research.elamur.ai/free/en/papers/ni-2026-survey-llm-based-conversational-user/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bo Ni, Yu Wang, Leyao Wang, et al.*2026 · 1 citation*
62. **[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*
63. **[Be Your Own Red Teamer: Safety Alignment via Self-Play and Reflective Experience Replay](https://md.research.elamur.ai/free/en/papers/wang-2026-be-your-own-red-teamer/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hao Wang, Yanting Wang, Hao Li, et al.*2026 · 1 citation*
64. **[CrowS-Pairs-NL: A Benchmark to Evaluate Dutch Stereotype Bias in LLMs](https://md.research.elamur.ai/free/en/papers/weide-2026-crows-pairs-nl-benchmark-evaluate/) [Workshop on Stereotypes Across Cultures in Language Technologies](https://md.research.elamur.ai/free/en/venues/stereacult/)**Jens van der Weide, Dong Nguyen, Marianne Schaaphok, et al.*2026 · 1 citation*
65. **[German General Social Survey Personas: A Survey-Derived Persona Prompt Collection for Population-Aligned LLM Studies](https://md.research.elamur.ai/free/en/papers/rupprecht-2026-german-general-social-survey-personas/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jens Rupprecht, Leon Froehling, Claudia Wagner, et al.*2026 · 1 citation*
66. **[Knowing-but-Doing: Diagnosing and Defending Role-Play-Driven LLMs Jailbreaks via Moral Disengagement](https://md.research.elamur.ai/free/en/papers/qin-2026-knowing-but-doing-diagnosing-defending/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haiming Qin, Jianxun Lian, Qimin Zhong, et al.*2026 · 1 citation*
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69. **[Ready to Translate, Not to Represent? Bias and Performance Gaps in Multilingual LLMs Across Language Families and Domains](https://md.research.elamur.ai/free/en/papers/sayeedi-2026-ready-translate-not-represent-bias/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md. Faiyaz Abdullah Sayeedi, Subhey Sadi Rahman, Md. Mahbub Alam, et al.*2026 · 1 citation*
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73. **[VocabTailor: Dynamic Vocabulary Selection for Downstream Tasks in Small Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-vocabtailor-dynamic-vocabulary-selection-downstream/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hanling Zhang, Yayu Zhou, Tongcheng Fang, et al.*2026 · 1 citation*
74. **[When LLMs Annotate: Reliability Challenges in Low-Resource NLI](https://md.research.elamur.ai/free/en/papers/panahi-2026-when-llms-annotate-reliability-challenges/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Solmaz Panahi, John Kelleher, Vasudevan Nedumpozhimana*2026 · 1 citation*
75. **[Whose Facts Win? LLM Source Preferences under Knowledge Conflicts](https://md.research.elamur.ai/free/en/papers/schuster-2026-whose-facts-win-llm-source/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jakob Schuster, Vagrant Gautam, Katja Markert*2026 · 1 citation*
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80. **[Bias Dynamics in BabyLMs: Towards a Compute-Efficient Sandbox for Democratising Pre-Training Debiasing](https://md.research.elamur.ai/free/en/papers/trhlik-2026-bias-dynamics-babylms-compute-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Filip Trhlík, Andrew Caines, Paula Buttery*2026*
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82. **[Breaking the Benchmark: Revealing LLM Bias via Minimal Contextual Augmentation](https://md.research.elamur.ai/free/en/papers/miandoab-2026-breaking-benchmark-revealing-llm-bias/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kaveh Eskandari Miandoab, Mahammed Kamruzzaman, Arshia Gharooni, et al.*2026*
83. **[Colorism in Multimodal AI: An Empirical Exploration of Socioeconomic Linguistic Bias in Text-to-Image Generation](https://md.research.elamur.ai/free/en/papers/maurya-2026-colorism-multimodal-ai-empirical-exploration/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Raj Gaurav Maurya, Vaibhav Shukla, Sreedath Panat*2026*
84. **[Counterspeech Generation using Small Language Models](https://md.research.elamur.ai/free/en/papers/muhammad-2026-counterspeech-generation-small-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Abubakar Sadiq Muhammad, Simona Frenda, Gavin Abercrombie*2026*
85. **[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*
86. **[Detection of Adversarial Prompts with Model Predictive Entropy](https://md.research.elamur.ai/free/en/papers/rubenbauer-2026-detection-adversarial-prompts-model-predictive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Franziska Rubenbauer, Sebastian Steindl, Patrick Levi, et al.*2026*
87. **[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*
88. **[Evaluating the Impact of Source Diversity for RAG in Historical Research](https://md.research.elamur.ai/free/en/papers/mahadeshwar-2026-evaluating-impact-source-diversity-rag/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ruhi Mahadeshwar, Andreas van Cranenburgh, Tommaso Caselli, et al.*2026*
89. [**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/)
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91. **[From a River in Gilead to the Inference Distributions of Large Language Models: Covert Dialect Bias and Linguistic Profiling at Scale](https://md.research.elamur.ai/free/en/papers/abdullah-2026-river-gilead-inference-distributions-large/) [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/)**Chowdhury Mohammad Abdullah, Rita Orji*2026*
92. **[Gender Disparities in LLM-Based Intimate Partner Violence Detection](https://md.research.elamur.ai/free/en/papers/prama-2026-gender-disparities-llm-based-intimate/) [Workshop on Natural Language Processing and Computational Social Science](https://md.research.elamur.ai/free/en/venues/nlpcss/)**Tabia Tanzin Prama, Mikaela Irene Fudolig, Abigail M. Crocker, et al.*2026*
93. **[GPT-NL Public Corpus: A Permissively Licensed, Dutch-First Dataset for LLM Pre-training](https://md.research.elamur.ai/free/en/papers/oort-2026-gpt-nl-public-corpus-permissively/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Jesse J. Van Oort, Frank Brinkkemper, Erik de Graaf, et al.*2026*
94. **[How Far Can Bias Go? Tracing Bias from Pre-Training Data to Alignment](https://md.research.elamur.ai/free/en/papers/thaler-2026-how-far-can-bias-go/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Marion Thaler, Abdullatif Köksal, Alina Leidinger, et al.*2026*
95. **[Investigating Gender Stereotypes in Large Language Models via Social Determinants of Health](https://md.research.elamur.ai/free/en/papers/ngo-2026-investigating-gender-stereotypes-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Trung Hieu Ngo, Adrien Bazoge, Solen Quiniou, et al.*2026*
96. [**JudgeMeNot: Personalizing Large Language Models to Emulate Judicial Reasoning in Hebrew**Itay Razumenko, Arnon Sturm, Nir Grinberg*2026*](https://md.research.elamur.ai/free/en/papers/razumenko-2026-judgemenot-personalizing-large-language-models/)
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98. **[On the Cultural Anachronism and Temporal Reasoning in Vision Language Models](https://md.research.elamur.ai/free/en/papers/ranjan-2026-cultural-anachronism-temporal-reasoning-vision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mukul Ranjan, Prince Jha, Khushboo Kumari, et al.*2026*
99. **[Optimizer Choice and Calibration for QARiB on Arabic-Script Social Media Offensive Language Detection](https://md.research.elamur.ai/free/en/papers/elshokry-2026-optimizer-choice-calibration-qarib-arabic/) [Workshop on NLP for Languages Using Arabic Script](https://md.research.elamur.ai/free/en/venues/abjadnlp/)**Auda Elshokry, Mohammed Alhanjouri*2026*
100. **[OrthoEdit: Principled and Stable Knowledge Editing via Orthogonal Subspace Projection](https://md.research.elamur.ai/free/en/papers/qiao-2026-orthoedit-principled-stable-knowledge-editing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Shanbao Qiao, Xuebing Liu, Akshat Gupta, et al.*2026*

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