---
title: "Who cites Atoosa Kasirzadeh — page 2 — 458 citing papers"
description: "458 papers of the Elamur Research library cite the works of Atoosa Kasirzadeh, found in their bibliographies · page 2 of 2 · 101–140; the most…"
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# Who cites Atoosa Kasirzadeh

464 citations of their works from 458 papers of our library (of the 149,439 whose bibliographies we read) · 140 with a page here, the most cited first · page 2 of 2 · 101–140 · [← Atoosa Kasirzadeh](https://md.research.elamur.ai/free/en/authors/atoosa-kasirzadeh/)

[← prev](https://md.research.elamur.ai/free/en/authors/atoosa-kasirzadeh/cited-by/) [1](https://md.research.elamur.ai/free/en/authors/atoosa-kasirzadeh/cited-by/) **2**

101. **[JASMINE: Arabic GPT Models for Few-Shot Learning](https://md.research.elamur.ai/free/en/papers/nagoudi-2023-jasmine-arabic-gpt-models-few/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, AbdelRahim Elmadany, et al.*2023 · 38 citations*
102. [**A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence arXiv:2507.21046**Huan-ang Gao, Jiayi Geng, Wenyue Hua, et al.*2025 · 36 citations*](https://md.research.elamur.ai/free/en/papers/gao-2025-survey-self-evolving-agents-where/)
103. [**Through the Lens of Core Competency: Survey on Evaluation of Large Language Models arXiv:2308.07902**Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/zhuang-2023-through-lens-core-competency-survey/)
104. [**Feedback Loops With Language Models Drive In-Context Reward Hacking arXiv:2402.06627**Alexander Pan, Erik Jones, Meena Jagadeesan, et al.*2024 · 26 citations*](https://md.research.elamur.ai/free/en/papers/pan-2024-feedback-loops-language-models-drive/)
105. **[The State of Multilingual LLM Safety Research: From Measuring The Language Gap To Mitigating It](https://md.research.elamur.ai/free/en/papers/yong-2025-state-multilingual-llm-safety-research/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zheng Xin Yong, Beyza Ermis, Marzieh Fadaee, et al.*2025 · 25 citations*
106. [**Language Model Alignment in Multilingual Trolley Problems arXiv:2407.02273**Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-language-model-alignment-multilingual-trolley/)
107. **[Intention Analysis Makes LLMs A Good Jailbreak Defender](https://md.research.elamur.ai/free/en/papers/zhang-2025-intention-analysis-makes-llms-good/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Yuqi Zhang, Liang Ding, Lefei Zhang, et al.*2025 · 21 citations*
108. [**Astraios: Parameter-Efficient Instruction Tuning Code Large Language Models arXiv:2401.00788**Terry Yue Zhuo, Armel Zebaze, Nitchakarn Suppattarachai, et al.*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-astraios-parameter-efficient-instruction-tuning/)
109. **[Humans Learn Language from Situated Communicative Interactions. What about Machines?](https://md.research.elamur.ai/free/en/papers/beuls-2024-humans-learn-language-situated-communicative/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Katrien Beuls, Paul Van Eecke*2024 · 21 citations*
110. **[AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing](https://md.research.elamur.ai/free/en/papers/alghamdi-2023-aramus-pushing-limits-data-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Asaad Alghamdi, Xinyu Duan, Wei Jiang, et al.*2023 · 21 citations*
111. **[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*
112. **[AAVENUE: Detecting LLM Biases on NLU Tasks in AAVE via a Novel Benchmark](https://md.research.elamur.ai/free/en/papers/gupta-2024-aavenue-detecting-llm-biases-nlu/) [Workshop on NLP for Positive Impact](https://md.research.elamur.ai/free/en/venues/nlp4pi/)**Abhay Gupta, Ece Yurtseven, Philip Meng, et al.*2024 · 17 citations*
113. **[Beyond Prompt Engineering: Robust Behavior Control in LLMs via Steering Target Atoms](https://md.research.elamur.ai/free/en/papers/wang-2025-beyond-prompt-engineering-robust-behavior/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengru Wang, Ziwen Xu, Shengyu Mao, et al.*2025 · 14 citations*
114. [**Psychometric Alignment: Capturing Human Knowledge Distributions via Language Models arXiv:2407.15645**Joy He-Yueya, Wanjing Anya Ma, Kanishk Gandhi, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/he-yueya-2024-psychometric-alignment-capturing-human-knowledge/)
115. [**AI for Auto-Research: Roadmap & User Guide arXiv:2605.18661**Lingdong Kong, Xian Sun, Wei Chow, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/kong-2026-ai-auto-research-roadmap-user/)
116. **[False Sense of Security: Why Probing-based Malicious Input Detection Fails to Generalize](https://md.research.elamur.ai/free/en/papers/wang-2026-false-sense-security-why-probing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng Wang, Zeming Wei, Qin Liu, et al.*2026 · 5 citations*
117. **[HiddenGuard: Fine-Grained Safe Generation with Specialized Representation Router](https://md.research.elamur.ai/free/en/papers/mei-2026-hiddenguard-fine-grained-safe-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.*2026 · 4 citations*
118. [**SciIntegrity-Bench: A Benchmark for Evaluating Academic Integrity in AI Scientist Systems arXiv:2605.10246**Zonglin Yang, Xingtong Liu, Xinyan Xu*2026 · 4 citations*](https://md.research.elamur.ai/free/en/papers/yang-2026-sciintegrity-bench-benchmark-evaluating/)
119. **[Are BabyLMs Deaf to Gricean Maxims? A Pragmatic Evaluation of Sample-efficient Language Models](https://md.research.elamur.ai/free/en/papers/askari-2025-are-babylms-deaf-gricean-maxims/) [BabyLM Workshop](https://md.research.elamur.ai/free/en/venues/babylm/)**Raha Askari, Sina Zarrieß, Özge Alacam, et al.*2025 · 4 citations*
120. **[Jailbreaking Attacks vs. Content Safety Filters: How Far Are We in the LLM Safety Arms Race?](https://md.research.elamur.ai/free/en/papers/xin-2026-jailbreaking-attacks-vs-content-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuan Xin, Dingfan Chen, Linyi Yang, et al.*2026 · 3 citations*
121. **[Unraveling LLM Jailbreaks Through Safety Knowledge Neurons](https://md.research.elamur.ai/free/en/papers/zhao-2026-unraveling-llm-jailbreaks-through-safety/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Chongwen Zhao, Yutong Ke, Kaizhu Huang*2026 · 3 citations*
122. **[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*
123. [**Position: Correct Answer, Wrong Mechanism — When AI Scientists Defend General Claims Their Own Data Contradicts arXiv:2606.23175**Steven Young Eulig*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/eulig-2026-position-correct-answer-wrong/)
124. **[A Simple and Efficient Learning-Style Prompting for LLM Jailbreaking](https://md.research.elamur.ai/free/en/papers/luo-2026-simple-efficient-learning-style-prompting/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuan Luo, Yue Wang, Zefeng He, et al.*2026*
125. **[AI Safety Lost in Translation: Evaluating the Effectiveness of English-Italian Cross-Lingual LLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/wu-2026-ai-safety-lost-translation-evaluating/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Alessio Wu, Martim Brandao*2026*
126. **[Calibrating Inference Time Alignment with Sequence-level Risk Accumulation](https://md.research.elamur.ai/free/en/papers/tan-2026-calibrating-inference-time-alignment-sequence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shanwen Tan, Ziyang Dong, Wei Ju, et al.*2026*
127. **[CodeGuard: Improving LLM Guardrails in CS Education](https://md.research.elamur.ai/free/en/papers/raihan-2026-codeguard-improving-llm-guardrails-cs/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nishat Raihan, Noah Erdachew, Jayoti Devi, et al.*2026*
128. **[Deactivating Refusal Triggers: Understanding and Mitigating Overrefusal in Safety Alignment](https://md.research.elamur.ai/free/en/papers/xue-2026-deactivating-refusal-triggers-understanding-mitigating/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Zhiyu Xue, Zimo Qi, Guangliang Liu, et al.*2026*
129. **[Do Language Models Think Consistently? A Study of Value Preferences Across Varying Response Lengths](https://md.research.elamur.ai/free/en/papers/nair-2026-do-language-models-think-consistently/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Inderjeet Jayakumar Nair, Lu Wang*2026*
130. **[DRInQ: Evaluating Conversational Implicature with Controlled Context Variation](https://md.research.elamur.ai/free/en/papers/arai-2026-drinq-evaluating-conversational-implicature-controlled/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hirona Jacqueline Arai, Xiang Ren*2026*
131. **[Grammar Search for Multi-Agent Systems](https://md.research.elamur.ai/free/en/papers/singh-2026-grammar-search-multi-agent-systems/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mayank Singh, Vikas Yadav, Shiva Krishna Reddy Malay, et al.*2026*
132. **[How Controllable Are Large Language Models? A Unified Evaluation across Behavioral Granularities](https://md.research.elamur.ai/free/en/papers/xu-2026-how-controllable-are-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziwen Xu, Kewei Xu, Haoming Xu, et al.*2026*
133. **[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*
134. **[MERIT Feedback Elicits Better Bargaining in LLM Negotiators](https://md.research.elamur.ai/free/en/papers/oh-2026-merit-feedback-elicits-better-bargaining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jihwan Oh, Murad Aghazada, Yooju Shin, et al.*2026*
135. **[Reference Attack: A New Cross-Modal Jailbreaking Attack against Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-reference-attack-new-cross-modal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yulong Wang, Yifei Fu, Jiayi Gao*2026*
136. [**SalamahBench: Dialect and Category Level Safety Evaluation of Arabic Language Models arXiv:2603.04410**Omar Abdelnasser, Fatemah Alharbi, Khaled Khasawneh, et al.*2026*](https://md.research.elamur.ai/free/en/papers/abdelnasser-2026-salamahbench-dialect-category-level-safety/)
137. **[Taken into consideration: evaluating esteem biases by race, gender and region in large language models in Brazilian Portuguese (Levados em Consideração: Uma Avaliação de Vieses de Estima por Raça, Gênero e Região em Grandes Modelos de Linguagem em Português Brasileiro)](https://md.research.elamur.ai/free/en/papers/melo-2026-levados-em-consideracao-uma-avaliacao/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**João Lucas Lima de Melo, Marlo Souza*2026*
138. **[Toward Dialect-Aware Safety Evaluation for Arabic Large Language Models](https://md.research.elamur.ai/free/en/papers/zaghouani-2026-dialect-aware-safety-evaluation-arabic/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Wajdi Zaghouani*2026*
139. **[When Efficiency Meets Safety: A Benchmark Security Analysis of KV Cache Compression in Large Language Models](https://md.research.elamur.ai/free/en/papers/ma-2026-when-efficiency-meets-safety-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoxiao Ma, Kuofeng Gao, Zeyi Lu, et al.*2026*
140. [**ALHD: A Large-Scale and Multigenre Benchmark Dataset for Arabic LLM-Generated Text Detection arXiv:2510.03502**Ali Khairallah, Arkaitz Zubiaga*2025*](https://md.research.elamur.ai/free/en/papers/khairallah-2025-alhd-large-scale-multigenre-benchmark/)

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