---
title: "Who cites Aidan Clark — page 2"
description: "4,354 papers of the Elamur Research library cite the works of Aidan Clark, found in their bibliographies · page 2 of 3 · 101–200; the most cited first."
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---
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# Who cites Aidan Clark

4,729 citations of their works from 4,354 papers of our library (of the 140,884 whose bibliographies we read) · 272 with a page here, the most cited first · page 2 of 3 · 101–200 · [← Aidan Clark](https://md.research.elamur.ai/free/en/authors/aidan-clark/)

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101. [**OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents**Hugo Laurençon, Lucile Saulnier, Leo Tronchon, et al.*2023 · 183 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-obelics-open-web-scale-filtered/)
102. [**Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation**Shivalika Singh, Angelika Romanou, Clémentine Fourrier, et al.*2025 · 179 citations*](https://md.research.elamur.ai/free/en/papers/singh-2025-global-mmlu-understanding-addressing-cultural/)
103. [**Knowledge Conflicts for LLMs: A Survey**Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.*2024 · 179 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-knowledge-conflicts-llms-survey/)
104. [**Effective Long-Context Scaling of Foundation Models**Wenhan Xiong, Jingyu Liu, Igor Molybog, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-effective-long-context-scaling-foundation/)
105. [**Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 174 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/)
106. [**Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs**Shengbang Tong, Ellis Brown, Penghao Wu, et al.*2024 · 173 citations*](https://md.research.elamur.ai/free/en/papers/tong-2024-cambrian-1-fully-open-vision/)
107. [**SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language Model**Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.*2025 · 171 citations*](https://md.research.elamur.ai/free/en/papers/allal-2025-smollm2-smol-goes-big-data/)
108. [**OpenChat: Advancing Open-source Language Models with Mixed-Quality Data**Guan Wang, Sijie Cheng, Xianyuan Zhan, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-openchat-advancing-open-source-language/)
109. [**Learning to Compress Prompts with Gist Tokens**Jesse Mu, Xiang Lisa Li, Noah Goodman*2023 · 170 citations*](https://md.research.elamur.ai/free/en/papers/mu-2023-learning-compress-prompts-gist-tokens/)
110. [**SqueezeLLM: Dense-and-Sparse Quantization**Sehoon Kim, Coleman Hooper, Amir Gholami, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-squeezellm-dense-sparse-quantization/)
111. [**ShortGPT: Layers in Large Language Models are More Redundant Than You Expect**Xin Men, Mingyu Xu, Qingyu Zhang, et al.*2024 · 167 citations*](https://md.research.elamur.ai/free/en/papers/men-2024-shortgpt-layers-large-language-models/)
112. [**Binding Language Models in Symbolic Languages**Zhoujun Cheng, Tianbao Xie, Peng Shi, et al.*2022 · 165 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2022-binding-language-models-symbolic-languages/)
113. [**Large Language Diffusion Models**Shen Nie, Fengqi Zhu, Zebin You, et al.*2025 · 164 citations*](https://md.research.elamur.ai/free/en/papers/nie-2025-large-language-diffusion-models/)
114. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 159 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/)
115. [**GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models**Aohan Zeng, Xin Lv, Qinkai Zheng, et al.*2025 · 157 citations*](https://md.research.elamur.ai/free/en/papers/team-2025-4-glm-4-5-agentic/)
116. [**DataComp-LM: In search of the next generation of training sets for language models**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 156 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/)
117. [**The Lessons of Developing Process Reward Models in Mathematical Reasoning**Zhenru Zhang, Chujie Zheng, Yangzhen Wu, et al.*2025 · 155 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-lessons-developing-process-reward-models/)
118. [**HunyuanVideo: A Systematic Framework For Large Video Generative Models**Weijie Kong, Qi Tian, Zijian Zhang, et al.*2024 · 155 citations*](https://md.research.elamur.ai/free/en/papers/kong-2024-hunyuanvideo-systematic-framework-large/)
119. [**Moshi: a speech-text foundation model for real-time dialogue**Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.*2024 · 154 citations*](https://md.research.elamur.ai/free/en/papers/defossez-2024-moshi-speech-text-foundation-model/)
120. [**TheoremQA: A Theorem-driven Question Answering Dataset**Wenhu Chen, Ming Yin, Max Ku, et al.*2023 · 154 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-theoremqa-theorem-driven-question-answering/)
121. [**Leveraging Large Language Models for Multiple Choice Question Answering**Joshua Robinson, Christopher Michael Rytting, David Wingate*2022 · 154 citations*](https://md.research.elamur.ai/free/en/papers/robinson-2022-leveraging-large-language-models-multiple/)
122. [**Locally Typical Sampling**Clara Meister, Tiago Pimentel, Gian Wiher, et al.*2023 · 152 citations*](https://md.research.elamur.ai/free/en/papers/meister-2023-locally-typical-sampling/)
123. [**SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training**Tianzhe Chu, Yuexiang Zhai, Jihan Yang, et al.*2025 · 151 citations*](https://md.research.elamur.ai/free/en/papers/chu-2025-sft-memorizes-rl-generalizes-comparative/)
124. [**AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators**Xingwei He, Zhenghao Lin, Yeyun Gong, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-annollm-making-large-language-models/)
125. [**SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild**Weihao Zeng, Yuzhen Huang, Qian Liu, et al.*2025 · 148 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2025-simplerl-zoo-investigating-taming-zero/)
126. [**Process Reinforcement through Implicit Rewards**Ganqu Cui, Lifan Yuan, Zefan Wang, et al.*2025 · 147 citations*](https://md.research.elamur.ai/free/en/papers/cui-2025-process-reinforcement-through-implicit-rewards/)
127. [**rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking**Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.*2025 · 146 citations*](https://md.research.elamur.ai/free/en/papers/guan-2025-rstar-math-small-llms-can/)
128. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 145 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
129. [**How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition**Guanting Dong, Hongyi Yuan, Keming Lu, et al.*2024 · 145 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-how-abilities-large-language-models/)
130. [**The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset**Hugo Laurençon, Lucile Saulnier, Thomas Wang, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-bigscience-roots-corpus-1-6tb/)
131. [**Is GPT-3 a Good Data Annotator?**Bosheng Ding, Chengwei Qin, Linlin Liu, et al.*2022 · 144 citations*](https://md.research.elamur.ai/free/en/papers/ding-2022-gpt-3-good-data-annotator/)
132. [**Symbolic Chain-of-Thought Distillation: Small Models Can Also “Think” Step-by-Step**Liunian Harold Li, Jack Hessel, Youngjae Yu, et al.*2023 · 139 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-symbolic-chain-thought-distillation-small/)
133. [**DeepInception: Hypnotize Large Language Model to Be Jailbreaker**Xuan Li, Zhanke Zhou, Jianing Zhu, et al.*2023 · 138 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-deepinception-hypnotize-large-language-model/)
134. [**R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning**Huatong Song, Jinhao Jiang, Yingqian Min, et al.*2025 · 137 citations*](https://md.research.elamur.ai/free/en/papers/song-2025-r1-searcher-incentivizing-search/)
135. [**Efficient Training of Language Models to Fill in the Middle**Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.*2022 · 137 citations*](https://md.research.elamur.ai/free/en/papers/bavarian-2022-efficient-training-language-models-fill/)
136. [**Agent Laboratory: Using LLM Agents as Research Assistants**Samuel Schmidgall, Yusheng Su, Ze Wang, et al.*2025 · 136 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agent-laboratory-using-llm/)
137. [**Understanding the Effects of RLHF on LLM Generalisation and Diversity**Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, et al.*2023 · 131 citations*](https://md.research.elamur.ai/free/en/papers/kirk-2023-understanding-effects-rlhf-llm-generalisation/)
138. [**Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback**Yao Fu, Hao Peng, Tushar Khot, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-improving-language-model-negotiation-self/)
139. [**Deductive Verification of Chain-of-Thought Reasoning**Zhan Ling, Yunhao Fang, Xuanlin Li, et al.*2023 · 128 citations*](https://md.research.elamur.ai/free/en/papers/ling-2023-deductive-verification-chain-thought-reasoning/)
140. [**Large Language Model Alignment: A Survey**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/)
141. [**Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory**Prateek Chhikara, Dev Khant, Saket Aryan, et al.*2025 · 122 citations*](https://md.research.elamur.ai/free/en/papers/chhikara-2025-mem0-building-production-ready-ai/)
142. [**The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search**Yutaro Yamada, Robert Tjarko Lange, Cong Lu, et al.*2025 · 121 citations*](https://md.research.elamur.ai/free/en/papers/yamada-2025-ai-scientist-v2-workshop/)
143. [**DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition**Z. Z. Ren, Zhihong Shao, Junxiao Song, et al.*2025 · 120 citations*](https://md.research.elamur.ai/free/en/papers/ren-2025-deepseek-prover-v2-advancing-formal/)
144. [**L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning**Pranjal Aggarwal, Sean Welleck*2025 · 119 citations*](https://md.research.elamur.ai/free/en/papers/aggarwal-2025-l1-controlling-long-reasoning-model/)
145. [**DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence**DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.*2026 · 117 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2026-deepseek-v4-highly-efficient/)
146. [**ProcessBench: Identifying Process Errors in Mathematical Reasoning**Chujie Zheng, Zhenru Zhang, Beichen Zhang, et al.*2025 · 116 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2025-processbench-identifying-process-errors-mathematical/)
147. [**HealthBench: Evaluating Large Language Models Towards Improved Human Health**Rahul K. Arora, Jason Wei, Rebecca Soskin Hicks, et al.*2025 · 115 citations*](https://md.research.elamur.ai/free/en/papers/arora-2025-healthbench-evaluating-large-language-models/)
148. [**Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models**Yangzhen Wu, Zhiqing Sun, Shanda Li, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-inference-scaling-laws-empirical-analysis/)
149. [**ALLaM: Large Language Models for Arabic and English**M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/bari-2024-allam-large-language-models-arabic/)
150. [**Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs**Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.*2025 · 110 citations*](https://md.research.elamur.ai/free/en/papers/gandhi-2025-cognitive-behaviors-that-enable-self/)
151. [**Olmo 3**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 109 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
152. [**Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification**Aojun Zhou, Ke Wang, Zimu Lu, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-solving-challenging-math-word-problems/)
153. [**DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments**Yuxiang Zheng, Dayuan Fu, Xiangkun Hu, et al.*2025 · 108 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2025-deepresearcher-scaling-deep-research-reinforcement/)
154. [**Data Engineering for Scaling Language Models to 128K Context**Yao Fu, Rameswar Panda, Xinyao Niu, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-data-engineering-scaling-language-models/)
155. [**TokenSkip: Controllable Chain-of-Thought Compression in LLMs**Heming Xia, Chak Tou Leong, Wenjie Wang, et al.*2025 · 105 citations*](https://md.research.elamur.ai/free/en/papers/xia-2025-tokenskip-controllable-chain-thought-compression/)
156. [**Tokenizer Choice For LLM Training: Negligible or Crucial?**Mehdi Ali, Michael Fromm, Klaudia Thellmann, et al.*2024 · 102 citations*](https://md.research.elamur.ai/free/en/papers/ali-2024-tokenizer-choice-llm-training-negligible/)
157. [**UI-TARS: Pioneering Automated GUI Interaction with Native Agents**Yujia Qin, Yining Ye, Junjie Fang, et al.*2025 · 101 citations*](https://md.research.elamur.ai/free/en/papers/qin-2025-ui-tars-pioneering-automated/)
158. [**Inverse Scaling: When Bigger Isn't Better**Ian R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.*2023 · 99 citations*](https://md.research.elamur.ai/free/en/papers/mckenzie-2023-inverse-scaling-bigger-isn-t/)
159. [**SemDeDup: Data-efficient learning at web-scale through semantic deduplication**Amro Abbas, Kushal Tirumala, Dániel Simig, et al.*2023 · 94 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2023-semdedup-data-efficient-learning-web/)
160. [**Skywork: A More Open Bilingual Foundation Model**Tianwen Wei, Liang Zhao, Lichang Zhang, et al.*2023 · 91 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-skywork-more-open-bilingual/)
161. [**Language Modeling Is Compression**Gregoire Deletang, Anian Ruoss, Paul-Ambroise Duquenne, et al.*2023 · 89 citations*](https://md.research.elamur.ai/free/en/papers/deletang-2023-language-modeling-compression/)
162. [**D4: Improving LLM Pretraining via Document De-Duplication and Diversification**Kushal Tirumala, Daniel Simig, Armen Aghajanyan, et al.*2023 · 79 citations*](https://md.research.elamur.ai/free/en/papers/tirumala-2023-d4-improving-llm-pretraining-document/)
163. [**Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2023 · 79 citations*](https://md.research.elamur.ai/free/en/papers/tay-2023-scaling-laws-vs-model-architectures/)
164. [**Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in Chinchilla**Tom Lieberum, Matthew Rahtz, Janos Kramar, et al.*2023 · 51 citations*](https://md.research.elamur.ai/free/en/papers/lieberum-2023-circuit-analysis-interpretability-scale-evidence/)
165. [**Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws**Nikhil Sardana, Jacob Portes, Sasha Doubov, et al.*2024 · 47 citations*](https://md.research.elamur.ai/free/en/papers/sardana-2024-chinchilla-optimal-accounting-inference-language/)
166. [**Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies**Chaofan Tao, Qian Liu, Longxu Dou, et al.*2024 · 42 citations*](https://md.research.elamur.ai/free/en/papers/tao-2024-scaling-laws-vocabulary-larger-models/)
167. [**Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling**Runze Liu, Junqi Gao, Jian Zhao, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-1b-llm-surpass-405b-llm/)
168. [**Transcending Scaling Laws with 0.1% Extra Compute**Yi Tay, Jason Wei, Hyung Won Chung, et al.*2022 · 40 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-transcending-scaling-laws-0-1/)
169. [**Scaling Laws for Generative Mixed-Modal Language Models**Armen Aghajanyan, Lili Yu, Alexis Conneau, et al.*2023 · 39 citations*](https://md.research.elamur.ai/free/en/papers/aghajanyan-2023-scaling-laws-generative-mixed-modal/)
170. [**SemEval-2025 Task 1: AdMIRe - Advancing Multimodal Idiomaticity Representation**Thomas Pickard, Aline Villavicencio, Maggie Mi, et al.*2025 · 30 citations*](https://md.research.elamur.ai/free/en/papers/pickard-2025-semeval-2025-task-1-admire/)
171. [**Observational Scaling Laws and the Predictability of Language Model Performance**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 28 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/)
172. [**Taqyim: Evaluating Arabic NLP Tasks Using ChatGPT Models**Zaid Alyafeai, Maged S. Alshaibani, Badr AlKhamissi, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/alyafeai-2023-taqyim-evaluating-arabic-nlp-tasks/)
173. [**Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations**Alexander Hägele, Elie Bakouch, Atli Kosson, et al.*2024 · 24 citations*](https://md.research.elamur.ai/free/en/papers/hagele-2024-scaling-laws-compute-optimal-training/)
174. [**Distillation Scaling Laws**Dan Busbridge, Amitis Shidani, Floris Weers, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/busbridge-2025-distillation-scaling-laws/)
175. [**The Moral Foundations Reddit Corpus**Jackson P. Trager, Alireza S. Ziabari, Elnaz Rahmati, et al.*2026 · 22 citations*](https://md.research.elamur.ai/free/en/papers/trager-2026-moral-foundations-reddit-corpus/)
176. [**Do Large Language Models Understand Word Senses?**Domenico Meconi, Simone Stirpe, Federico Martelli*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/meconi-2025-llms-word-senses/)
177. [**New Trends for Modern Machine Translation with Large Reasoning Models**Sinuo Liu, Chenyang Lyu, Minghao Wu, et al.*2026 · 16 citations*](https://md.research.elamur.ai/free/en/papers/liu-2026-new-trends-modern-machine-translation/)
178. [**METAL: A Multi-Agent Framework for Chart Generation with Test-Time Scaling**Bingxuan Li, Yiwei Wang, Jiuxiang Gu, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-metal-multi-agent-framework-chart/)
179. [**Jais 2: A Family of Arabic-Centric Open Large Language Models**Mohamed Anwar, Abed Alhakim Freihat, George Ibrahim, et al.*2026 · 14 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2026-jais-2-family-arabic-centric/)
180. [**TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla**Nishat Raihan, Antonios Anastasopoulos, Marcos Zampieri*2026 · 13 citations*](https://md.research.elamur.ai/free/en/papers/raihan-2026-tigercoder-novel-suite-llms-code/)
181. [**When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning**Nishad Singhi, Hritik Bansal, Arian Hosseini, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/singhi-2025-solve-verify-compute-optimal-problem/)
182. [**Chinchilla Scaling: A replication attempt**Tamay Besiroglu, Ege Erdil, Matthew Barnett, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/besiroglu-2024-chinchilla-scaling-replication-attempt/)
183. [**GrammaMT: Improving Machine Translation with Grammar-Informed In-Context Learning**Rita Ramos, Everlyn Asiko Chimoto, Maartje Ter Hoeve, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2025-grammamt-improving-machine-translation-grammar/)
184. [**Multilingual Sequence-to-Sequence Models for Hebrew NLP**Matan Eyal, Hila Noga, Roee Aharoni, et al.*2023 · 9 citations*](https://md.research.elamur.ai/free/en/papers/eyal-2023-multilingual-sequence-sequence-models-hebrew/)
185. [**Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Understanding**Abbas Ghaddar, Yimeng Wu, Sunyam Bagga, et al.*2022 · 9 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2022-revisiting-pre-trained-language-models-their/)
186. [**Sacred or Synthetic? Evaluating LLM Reliability and Abstention for Religious Questions**Farah Atif, Nursultan Askarbekuly, Kareem Darwish, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/atif-2025-sacred-synthetic-evaluating-llm-reliability/)
187. [**FAME: Fictional Actors for Multilingual Erasure**Claudio Savelli, Moreno La Quatra, Alkis Koudounas, et al.*2026 · 7 citations*](https://md.research.elamur.ai/free/en/papers/savelli-2026-fame-fictional-actors-multilingual-erasure/)
188. [**Towards more Human-like Language Models based on Contextualizer Pretraining Strategy**Chenghao Xiao, G Thomas Hudson, Noura Al Moubayed*2023 · 7 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2023-more-human-like-language-models/)
189. [**Beyond Literal Mapping: Benchmarking and Improving Non-Literal Translation Evaluation**Yanzhi Tian, Cunxiang Wang, Zeming Liu, et al.*2026 · 5 citations*](https://md.research.elamur.ai/free/en/papers/tian-2026-beyond-literal-mapping-benchmarking-improving/)
190. [**Mechanisms vs. Outcomes: Probing for Syntax Fails to Explain Performance on Targeted Syntactic Evaluations**Ananth Agarwal, Jasper Jian, Christopher D Manning, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2025-mechanisms-vs-outcomes-probing-syntax/)
191. [**ARB: A Comprehensive Arabic Multimodal Reasoning Benchmark**Sara Ghaboura, Shubham Patle, Ketan More, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/ghaboura-2026-arb-comprehensive-arabic-multimodal-reasoning/)
192. [**Do Diacritics Matter? Evaluating the Impact of Arabic Diacritics on Tokenization and LLM Benchmarks**Go Inoue, Bashar Alhafni, Nizar Habash, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/inoue-2026-do-diacritics-matter-evaluating-impact/)
193. [**Scaling Laws for Code: A More Data-Hungry Regime**Xianzhen Luo, Wenzhen Zheng, Qingfu Zhu, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/luo-2026-scaling-laws-code-more-data/)
194. [**A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings**Fitsum Gaim, Hoyun Song, Huije Lee, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/gaim-2025-multi-task-benchmark-abusive-language/)
195. [**Baseer: A Vision-Language Model for Arabic Document-to-Markdown OCR**Khalil Hennara, Muhammad Hreden, Mohamed Motasim Hamed, et al.*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/hennara-2025-baseer-vision-language-model-arabic/)
196. [**A Critical Study of Automatic Evaluation in Sign Language Translation**Shakib Yazdani, Yasser HAMIDULLAH, Cristina España-Bonet, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/yazdani-2026-critical-study-automatic-evaluation-sign/)
197. [**Dicta-LM 3.0: Advancing The Frontier of Hebrew Sovereign LLMs**Shaltiel Shmidman, Avi Shmidman, Amir DN Cohen, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2026-dicta-lm-3-0-advancing/)
198. [**Prompting Instruction-tuned LLMs for Semantic Similarity Values**Xander Akiko Snelder, Yunchong Huang, Jelke Bloem*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/snelder-2026-prompting-instruction-tuned-llms-semantic/)
199. [**When Flores Bloomz Wrong: Cross-Direction Contamination in Machine Translation Evaluation**David Tan, Pinzhen Chen, Josef van Genabith, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/tan-2026-when-flores-bloomz-wrong-cross/)
200. [**Who Watches the Watchmen? Humans Disagree With Translation Metrics on Unseen Domains**Finn Schmidt, Jan Philip Wahle, Terry Ruas, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/schmidt-2026-who-watches-watchmen-humans-disagree/)

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