---
title: "Who cites Olatunji Ruwase — page 3 — 2,562 citing papers"
description: "2,562 papers of the Elamur Research library cite the works of Olatunji Ruwase, found in their bibliographies · page 3 of 6 · 201–300; the most…"
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---
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# Who cites Olatunji Ruwase

2,743 citations of their works from 2,562 papers of our library (of the 149,439 whose bibliographies we read) · 537 with a page here, the most cited first · page 3 of 6 · 201–300 · [← Olatunji Ruwase](https://md.research.elamur.ai/free/en/authors/olatunji-ruwase/)

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201. [**How well do Large Language Models perform in Arithmetic tasks? arXiv:2304.02015**Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.*2023 · 93 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-well-large-language-models-perform/)
202. [**Small Language Models are the Future of Agentic AI arXiv:2506.02153**Peter Belcak, Greg Heinrich, Shizhe Diao, et al.*2025 · 92 citations*](https://md.research.elamur.ai/free/en/papers/belcak-2025-small-language-models-future-agentic/)
203. [**SeaLLMs — Large Language Models for Southeast Asia arXiv:2312.00738**Xuan-Phi Nguyen, Wenxuan Zhang, Xin Li, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2023-seallms-large-language-models-southeast/)
204. [**What's In My Big Data? arXiv:2310.20707**Yanai Elazar, Akshita Bhagia, Ian Magnusson, et al.*2023 · 92 citations*](https://md.research.elamur.ai/free/en/papers/elazar-2023-s-my-big-data/)
205. [**Accelerating Distributed MoE Training and Inference with Lina arXiv:2210.17223**Jiamin Li, Yimin Jiang, Yibo Zhu, et al.*2022 · 92 citations*](https://md.research.elamur.ai/free/en/papers/li-2022-accelerating-distributed-moe-training-inference/)
206. [**LLM Inference Unveiled: Survey and Roofline Model Insights arXiv 2024**Zhihang Yuan, Yuzhang Shang, Yang Zhou, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2024-llm-inference-unveiled-survey-roofline/)
207. **[Cross-Lingual Consistency of Factual Knowledge in Multilingual Language Models](https://md.research.elamur.ai/free/en/papers/qi-2023-cross-lingual-consistency-factual-knowledge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jirui Qi, Raquel Fernández, Arianna Bisazza*2023 · 90 citations*
208. **[How to Train Long-Context Language Models (Effectively)](https://md.research.elamur.ai/free/en/papers/gao-2025-how-train-long-context-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Alexander Wettig, Howard Yen, et al.*2025 · 89 citations*
209. [**Safety Assessment of Chinese Large Language Models arXiv:2304.10436**Hao Sun, Zhexin Zhang, Jiawen Deng, et al.*2023 · 89 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-safety-assessment-chinese-large-language/)
210. **[Task Contamination: Language Models May Not Be Few-Shot Anymore](https://md.research.elamur.ai/free/en/papers/li-2023-task-contamination-language-models-may/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Changmao Li, Jeffrey Flanigan*2023 · 89 citations*
211. **[BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack](https://md.research.elamur.ai/free/en/papers/kuratov-2024-babilong-testing-limits-llms-long/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuri Kuratov, Aydar Bulatov, Petr Anokhin, et al.*2024 · 88 citations*
212. **[The Language Barrier: Dissecting Safety Challenges of LLMs in Multilingual Contexts](https://md.research.elamur.ai/free/en/papers/shen-2024-language-barrier-dissecting-safety-challenges/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lingfeng Shen, Weiting Tan, Sihao Chen, et al.*2024 · 88 citations*
213. [**Liger Kernel: Efficient Triton Kernels for LLM Training arXiv:2410.10989**Pin-Lun Hsu, Yun Dai, Vignesh Kothapalli, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/hsu-2024-liger-kernel-efficient-triton-kernels/)
214. **[When Is Multilinguality a Curse? Language Modeling for 250 High- and Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/chang-2024-when-is-multilinguality-curse-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tyler A. Chang, Catherine Arnett, Zhuowen Tu, et al.*2024 · 87 citations*
215. [**REST: Retrieval-Based Speculative Decoding arXiv:2311.08252**Zhenyu He; Zexuan Zhong; Tianle Cai; Jason D. Lee;, Di He*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/he-2023-rest-retrieval-based-speculative-decoding/)
216. **[Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and Observations](https://md.research.elamur.ai/free/en/papers/chen-2024-breaking-language-barriers-multilingual-mathematical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nuo Chen, Zinan Zheng, Ning Wu, et al.*2024 · 86 citations*
217. **[BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer](https://md.research.elamur.ai/free/en/papers/asai-2024-buffet-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Akari Asai, Sneha Kudugunta, Xinyan Yu, et al.*2024 · 86 citations*
218. **[Multilingual Large Language Models Are Not (Yet) Code-Switchers](https://md.research.elamur.ai/free/en/papers/zhang-2023-multilingual-large-language-models-are/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ruochen Zhang, Samuel Cahyawijaya, Jan Christian Blaise Cruz, et al.*2023 · 86 citations*
219. **[SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2024-seaeval-multilingual-foundation-models-cross/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Zhengyuan Liu, Xin Huang, et al.*2024 · 85 citations*
220. [**BayLing: Bridging Cross-lingual Alignment and Instruction Following through Interactive Translation for Large Language Models arXiv:2306.10968**Shaolei Zhang, Qingkai Fang, Zhuocheng Zhang, et al.*2023 · 85 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-bayling-bridging-cross-lingual-alignment/)
221. [**Investigating the Translation Performance of a Large Multilingual Language Model: the Case of BLOOM arXiv:2303.01911**Rachel Bawden, François Yvon*2023 · 85 citations*](https://md.research.elamur.ai/free/en/papers/bawden-2023-investigating-translation-performance-large-multilingual/)
222. **[Extreme Compression of Large Language Models via Additive Quantization](https://md.research.elamur.ai/free/en/papers/egiazarian-2024-extreme-compression-large-language-models/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Vage Egiazarian, Andrei Panferov, Denis Kuznedelev, et al.*2024 · 84 citations*
223. **[Mitigating the Alignment Tax of RLHF](https://md.research.elamur.ai/free/en/papers/lin-2024-mitigating-alignment-tax-rlhf/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yong Lin, Hangyu Lin, Wei Xiong, et al.*2024 · 83 citations*
224. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
225. **[Style Over Substance: Evaluation Biases for Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2025-style-over-substance-evaluation-biases/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Minghao Wu, Alham Fikri Aji*2025 · 81 citations*
226. **[Chain-of-Dictionary Prompting Elicits Translation in Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2024-chain-dictionary-prompting-elicits-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hongyuan Lu, Haoran Yang, Haoyang Huang, et al.*2024 · 81 citations*
227. [**In-Context Unlearning: Language Models as Few Shot Unlearners arXiv:2310.07579**Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/pawelczyk-2023-context-unlearning-language-models-few/)
228. **[MasakhaNEWS: News Topic Classification for African languages](https://md.research.elamur.ai/free/en/papers/adelani-2023-masakhanews-news-topic-classification-african/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**David Ifeoluwa Adelani, Marek Masiak, Israel Abebe Azime, et al.*2023 · 81 citations*
229. [**LLaMA Beyond English: An Empirical Study on Language Capability Transfer arXiv:2401.01055**Jun Zhao, Zhihao Zhang, Luhui Gao, et al.*2024 · 78 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-llama-english-empirical-study-language/)
230. [**Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations arXiv:2303.18027**Jungo Kasai, Yuhei Kasai, Keisuke Sakaguchi, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kasai-2023-evaluating-gpt-4-chatgpt-japanese/)
231. **[KMMLU: Measuring Massive Multitask Language Understanding in Korean](https://md.research.elamur.ai/free/en/papers/son-2025-kmmlu-measuring-massive-multitask-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guijin Son, Hanwool Lee, Sungdong Kim, et al.*2025 · 76 citations*
232. [**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/)
233. [**G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language Model arXiv:2312.11370**Jiahui Gao, Renjie Pi, Jipeng Zhang, et al.*2023 · 76 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-g-llava-solving-geometric-problem/)
234. [**Multilingual Large Language Model: A Survey of Resources, Taxonomy and Frontiers arXiv:2404.04925**Libo Qin, Qiguang Chen, Yuhang Zhou, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-multilingual-large-language-model-survey/)
235. [**PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities**Settaluri Sravanthi, Meet Doshi, Pavan Tankala, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/sravanthi-2024-pub-pragmatics-understanding-benchmark-assessing/)
236. [**Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers arXiv:2408.06195**Zhenting Qi, Mingyuan Ma, Jiahang Xu, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/qi-2024-mutual-reasoning-makes-smaller-llms/)
237. [**Instruction Mining: Instruction Data Selection for Tuning Large Language Models arXiv:2307.06290**Yihan Cao, Yanbin Kang, Chi Wang, et al.*2023 · 74 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-instruction-mining-instruction-data-selection/)
238. [**Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation arXiv:2307.15337**Xuefei Ning, Zinan Lin, Zixuan Zhou, et al.*2023 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ning-2023-skeleton-thought-prompting-llms-efficient/)
239. **[IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models](https://md.research.elamur.ai/free/en/papers/adelani-2025-irokobench-new-benchmark-african-languages/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**David Ifeoluwa Adelani, Jessica Ojo, Israel Abebe Azime, et al.*2025 · 70 citations*
240. [**ClinicalGPT: Large Language Models Finetuned with Diverse Medical Data and Comprehensive Evaluation arXiv:2306.09968**Guangyu Wang, Guoxing Yang, Zongxin Du, et al.*2023 · 70 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-clinicalgpt-large-language-models-finetuned/)
241. **[Apertus: Democratizing Open and Compliant LLMs for Global Language Environments](https://md.research.elamur.ai/free/en/papers/cano-2026-apertus-democratizing-open-compliant-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.*2026 · 68 citations*
242. **[Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards](https://md.research.elamur.ai/free/en/papers/wang-2024-arithmetic-control-llms-diverse-user/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoxiang Wang, Yong Lin, Wei Xiong, et al.*2024 · 68 citations*
243. [**Phoenix: Democratizing ChatGPT across Languages arXiv:2304.10453**Zhihong Chen, Feng Jiang, Junying Chen, et al.*2023 · 68 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-phoenix-democratizing-chatgpt-across-languages/)
244. [**Seed1.5-VL Technical Report arXiv:2505.07062**Dong Guo, Faming Wu, Feida Zhu, et al.*2025 · 67 citations*](https://md.research.elamur.ai/free/en/papers/guo-2025-seed1-5-vl-technical/)
245. [**FLUX: Fast Software-based Communication Overlap On GPUs Through Kernel Fusion arXiv:2406.06858**Li-Wen Chang, Wenlei Bao, Qi Hou, et al.*2024 · 67 citations*](https://md.research.elamur.ai/free/en/papers/chang-2024-flux-fast-software-based-communication/)
246. **[OffsetBias: Leveraging Debiased Data for Tuning Evaluators](https://md.research.elamur.ai/free/en/papers/park-2024-offsetbias-leveraging-debiased-data-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junsoo Park, Seungyeon Jwa, Ren Meiying, et al.*2024 · 67 citations*
247. **[On Context Utilization in Summarization with Large Language Models](https://md.research.elamur.ai/free/en/papers/ravaut-2024-context-utilization-summarization-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mathieu Ravaut, Aixin Sun, Nancy Chen, et al.*2024 · 67 citations*
248. [**LongWriter: Unleashing 10,000+ Word Generation from Long Context LLMs arXiv:2408.07055**Yushi Bai, Jiajie Zhang, Xin Lv, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-longwriter-unleashing-10-000/)
249. **[Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset](https://md.research.elamur.ai/free/en/papers/su-2025-nemotron-cc-transforming-common-crawl/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dan Su, Kezhi Kong, Ying Lin, et al.*2025 · 65 citations*
250. **[On the Multilingual Ability of Decoder-based Pre-trained Language Models: Finding and Controlling Language-Specific Neurons](https://md.research.elamur.ai/free/en/papers/kojima-2024-multilingual-ability-decoder-based-pre/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Takeshi Kojima, Itsuki Okimura, Yusuke Iwasawa, et al.*2024 · 65 citations*
251. **[Small LLMs Are Weak Tool Learners: A Multi-LLM Agent](https://md.research.elamur.ai/free/en/papers/shen-2024-small-llms-are-weak-tool/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Weizhou Shen, Chenliang Li, Hongzhan Chen, et al.*2024 · 65 citations*
252. [**We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning? arXiv:2407.01284**Runqi Qiao, Qiuna Tan, Guanting Dong, et al.*2024 · 65 citations*](https://md.research.elamur.ai/free/en/papers/qiao-2024-math-large-multimodal-model-achieve/)
253. [**Goat: Fine-tuned LLaMA Outperforms GPT-4 on Arithmetic Tasks arXiv:2305.14201**Tiedong Liu, Bryan Kian Hsiang Low*2023 · 65 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-goat-fine-tuned-llama-outperforms/)
254. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
255. [**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/)
256. **[MARIO: MAth Reasoning with code Interpreter Output - A Reproducible Pipeline](https://md.research.elamur.ai/free/en/papers/liao-2024-mario-math-reasoning-code-interpreter/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Minpeng Liao, Chengxi Li, Wei Luo, et al.*2024 · 64 citations*
257. [**Fairness-guided Few-shot Prompting for Large Language Models arXiv:2303.13217**Huan Ma, Changqing Zhang, Yatao Bian, et al.*2023 · 64 citations*](https://md.research.elamur.ai/free/en/papers/ma-2023-fairness-guided-few-shot-prompting/)
258. [**ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models arXiv:2402.11684**Guiming Hardy Chen, Shunian Chen, Ruifei Zhang, et al.*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-allava-harnessing-gpt4v-synthesized-data/)
259. [**Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Cases arXiv:2303.14742**Yunjie Ji, Yong Deng, Yan Gong, et al.*2023 · 62 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-exploring-impact-instruction-data/)
260. **[Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2025-is-translation-all-you-need/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chaoqun Liu, Wenxuan Zhang, Yiran Zhao, et al.*2025 · 61 citations*
261. **[Unifying Multimodal Retrieval via Document Screenshot Embedding](https://md.research.elamur.ai/free/en/papers/ma-2024-unifying-multimodal-retrieval-document-screenshot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xueguang Ma, Sheng-Chieh Lin, Minghan Li, et al.*2024 · 61 citations*
262. [**In-context Pretraining: Language Modeling Beyond Document Boundaries arXiv:2310.10638**Weijia Shi, Sewon Min, Maria Lomeli, et al.*2023 · 61 citations*](https://md.research.elamur.ai/free/en/papers/shi-2023-context-pretraining-language-modeling-document/)
263. **[A Family of Pretrained Transformer Language Models for Russian](https://md.research.elamur.ai/free/en/papers/zmitrovich-2024-family-pretrained-transformer-language-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Dmitry Zmitrovich, Aleksandr Abramov, Andrey Kalmykov, et al.*2024 · 60 citations*
264. **[TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varieties](https://md.research.elamur.ai/free/en/papers/kadaoui-2023-tarjamat-evaluation-bard-chatgpt-machine/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Karima Kadaoui, Samar M. Magdy, Abdul Waheed, et al.*2023 · 60 citations*
265. **[BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models](https://md.research.elamur.ai/free/en/papers/dong-2024-bamboo-comprehensive-benchmark-evaluating-long/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zican Dong, Tianyi Tang, Junyi Li, et al.*2024 · 59 citations*
266. **[Instruction Pre-Training: Language Models are Supervised Multitask Learners](https://md.research.elamur.ai/free/en/papers/cheng-2024-instruction-pre-training-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Daixuan Cheng, Yuxian Gu, Shaohan Huang, et al.*2024 · 59 citations*
267. [**Samba: Simple Hybrid State Space Models for Efficient Unlimited Context Language Modeling arXiv:2406.07522**Liliang Ren, Yang Liu, Yadong Lu, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/ren-2024-samba-simple-hybrid-state-space/)
268. [**MaLA-500: Massive Language Adaptation of Large Language Models arXiv:2401.13303**Peiqin Lin, Shaoxiong Ji, Jorg Tiedemann, et al.*2024 · 58 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-mala-500-massive-language-adaptation/)
269. **[MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance](https://md.research.elamur.ai/free/en/papers/pi-2024-mllm-protector-ensuring-mllm-s/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Renjie Pi, Tianyang Han, Jianshu Zhang, et al.*2024 · 58 citations*
270. [**LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning arXiv:2308.03303**Longteng Zhang, Lin Zhang, Shaohuai Shi, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-lora-fa-efficient-effective-low/)
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272. **[SciAgent: Tool-augmented Language Models for Scientific Reasoning](https://md.research.elamur.ai/free/en/papers/ma-2024-sciagent-tool-augmented-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yubo Ma, Zhibin Gou, Junheng Hao, et al.*2024 · 55 citations*
273. **[SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages](https://md.research.elamur.ai/free/en/papers/lovenia-2024-seacrowd-multilingual-multimodal-data-hub/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Holy Lovenia, Rahmad Mahendra, Salsabil Maulana Akbar, et al.*2024 · 54 citations*
274. **[Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors](https://md.research.elamur.ai/free/en/papers/maurya-2025-unifying-ai-tutor-evaluation-evaluation/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kaushal Kumar Maurya, Kv Aditya Srivatsa, Kseniia Petukhova, et al.*2025 · 53 citations*
275. **[Why do language models perform worse for morphologically complex languages?](https://md.research.elamur.ai/free/en/papers/arnett-2025-why-do-language-models-perform/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Catherine Arnett, Benjamin Bergen*2025 · 53 citations*
276. [**On the application of Large Language Models for language teaching and assessment technology arXiv:2307.08393**Andrew Caines, Luca Benedetto, Shiva Taslimipoor, et al.*2023 · 51 citations*](https://md.research.elamur.ai/free/en/papers/caines-2023-application-large-language-models-language/)
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278. [**Prompting Multilingual Large Language Models to Generate Code-Mixed Texts: The Case of South East Asian Languages arXiv:2303.13592**Zheng-Xin Yong, Ruochen Zhang, Jessica Zosa Forde, et al.*2023 · 48 citations*](https://md.research.elamur.ai/free/en/papers/yong-2023-prompting-multilingual-large-language-models/)
279. [**Getting the most out of your tokenizer for pre-training and domain adaptation arXiv:2402.01035**Gautier Dagan, Gabriel Synnaeve, Baptiste Roziere*2024 · 47 citations*](https://md.research.elamur.ai/free/en/papers/dagan-2024-getting-most-out-tokenizer-pre/)
280. **[WorldCuisines: A Massive-Scale Benchmark for Multilingual and Multicultural Visual Question Answering on Global Cuisines](https://md.research.elamur.ai/free/en/papers/winata-2025-worldcuisines-massive-scale-benchmark-multilingual/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Genta Indra Winata, Frederikus Hudi, Patrick Amadeus Irawan, et al.*2025 · 46 citations*
281. [**Language models scale reliably with over-training and on downstream tasks arXiv:2403.08540**Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/gadre-2024-language-models-scale-reliably-over/)
282. [**Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies arXiv:2407.13623**Chaofan Tao, Qian Liu, Longxu Dou, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/tao-2024-scaling-laws-vocabulary-larger-models/)
283. [**Lost in Translation: Large Language Models in Non-English Content Analysis arXiv:2306.07377**Gabriel Nicholas, Aliya Bhatia*2023 · 45 citations*](https://md.research.elamur.ai/free/en/papers/nicholas-2023-lost-translation-large-language-models/)
284. [**Halo: Estimation and Reduction of Hallucinations in Open-Source Weak Large Language Models arXiv:2308.11764**Mohamed Elaraby, Mengyin Lu, Jacob Dunn, et al.*2023 · 43 citations*](https://md.research.elamur.ai/free/en/papers/elaraby-2023-halo-estimation-reduction-hallucinations-open/)
285. **[Breaking the Curse of Multilinguality with Cross-lingual Expert Language Models](https://md.research.elamur.ai/free/en/papers/blevins-2024-breaking-curse-multilinguality-cross-lingual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Terra Blevins, Tomasz Limisiewicz, Suchin Gururangan, et al.*2024 · 42 citations*
286. **[The ROOTS Search Tool: Data Transparency for LLMs](https://md.research.elamur.ai/free/en/papers/piktus-2023-roots-search-tool-data-transparency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aleksandra Piktus, Christopher Akiki, Paulo Villegas, et al.*2023 · 42 citations*
287. [**DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models arXiv:2507.09955**Luolin Xiong, Haofen Wang, Xi Chen, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2025-deepseek-paradigm-shifts-technical/)
288. [**Observational Scaling Laws and the Predictability of Language Model Performance arXiv:2405.10938**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/)
289. [**PanGu-{\Sigma}: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing arXiv:2303.10845**Xiaozhe Ren, Pingyi Zhou, Xinfan Meng, et al.*2023 · 40 citations*](https://md.research.elamur.ai/free/en/papers/ren-2023-pangu-sigma-trillion-parameter/)
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292. [**Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing arXiv:2305.16635**Jaehun Jung, Peter West, Liwei Jiang, et al.*2023 · 36 citations*](https://md.research.elamur.ai/free/en/papers/jung-2023-impossible-distillation-low-quality-model/)
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295. [**M3KE: A Massive Multi-Level Multi-Subject Knowledge Evaluation Benchmark for Chinese Large Language Models arXiv:2305.10263**Chuang Liu, Renren Jin, Yuqi Ren, et al.*2023 · 34 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-m3ke-massive-multi-level/)
296. [**Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge Evaluation arXiv:2306.05783**Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye, et al.*2023 · 34 citations*](https://md.research.elamur.ai/free/en/papers/gu-2023-xiezhi-ever-updating-benchmark/)
297. [**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/)
298. [**TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer arXiv:2307.14995**Zhen Qin, Dong Li, Weigao Sun, et al.*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-transnormerllm-faster-better-large/)
299. [**ERNIE-ViLG: Unified Generative Pre-training for Bidirectional Vision-Language Generation arXiv:2112.15283**Han Zhang, Weichong Yin, Yewei Fang, et al.*2021 · 33 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2021-ernie-vilg-unified-generative/)
300. [**DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs arXiv:2503.07067**Jongwoo Ko, Tianyi Chen, Sungnyun Kim, et al.*2025 · 32 citations*](https://md.research.elamur.ai/free/en/papers/ko-2025-distillm-2-contrastive-approach-boosts/)

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