---
title: "Who cites Miruna-Adriana — page 3 — 1,693 citing papers"
description: "1,693 papers of the Elamur Research library cite the works of Miruna-Adriana Clinciu, found in their bibliographies · page 3 of 5 · 201–300…"
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---
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# Who cites Miruna-Adriana Clinciu

1,756 citations of their works from 1,693 papers of our library (of the 149,439 whose bibliographies we read) · 406 with a page here, the most cited first · page 3 of 5 · 201–300 · [← Miruna-Adriana Clinciu](https://md.research.elamur.ai/free/en/authors/miruna-adriana-clinciu/)

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201. [**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/)
202. [**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/)
203. **[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*
204. [**AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model arXiv:2208.01448**Saleh Soltan, Shankar Ananthakrishnan, Jack FitzGerald, et al.*2022 · 84 citations*](https://md.research.elamur.ai/free/en/papers/soltan-2022-alexatm-20b-few-shot-learning/)
205. **[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*
206. **[ORCA: A Challenging Benchmark for Arabic Language Understanding](https://md.research.elamur.ai/free/en/papers/elmadany-2023-orca-challenging-benchmark-arabic-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**AbdelRahim Elmadany, ElMoatez Billah Nagoudi, Muhammad Abdul-Mageed*2023 · 83 citations*
207. [**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/)
208. **[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*
209. **[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*
210. [**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/)
211. **[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*
212. [**Humans or LLMs as the Judge? A Study on Judgement Biases arXiv:2402.10669**Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.*2024 · 78 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-humans-llms-judge-study-judgement/)
213. [**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/)
214. [**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/)
215. **[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*
216. [**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/)
217. [**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/)
218. [**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/)
219. [**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/)
220. [**Benchmarking Benchmark Leakage in Large Language Models arXiv:2404.18824**Ruijie Xu, Zengzhi Wang, Run-Ze Fan, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/)
221. **[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*
222. [**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/)
223. **[Conditional Generation with a Question-Answering Blueprint](https://md.research.elamur.ai/free/en/papers/narayan-2023-conditional-generation-question-answering-blueprint/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Shashi Narayan, Joshua Maynez, Reinald Kim Amplayo, et al.*2023 · 70 citations*
224. **[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*
225. **[AraDiCE: Benchmarks for Dialectal and Cultural Capabilities in LLMs](https://md.research.elamur.ai/free/en/papers/mousi-2025-aradice-benchmarks-dialectal-cultural-capabilities/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Basel Mousi, Nadir Durrani, Fatema Ahmad, et al.*2025 · 68 citations*
226. **[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*
227. [**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/)
228. **[Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of Privacy](https://md.research.elamur.ai/free/en/papers/ippolito-2023-preventing-generation-verbatim-memorization-language/) [International Natural Language Generation Conference (INLG)](https://md.research.elamur.ai/free/en/venues/inlg/)**Daphne Ippolito, Florian Tramer, Milad Nasr, et al.*2023 · 68 citations*
229. **[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*
230. **[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*
231. [**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/)
232. [**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/)
233. [**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/)
234. [**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/)
235. **[SatLM: Satisfiability-Aided Language Models Using Declarative Prompting](https://md.research.elamur.ai/free/en/papers/ye-2023-satlm-satisfiability-aided-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xi Ye, Qiaochu Chen, Isil Dillig, et al.*2023 · 62 citations*
236. **[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*
237. [**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/)
238. **[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*
239. **[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*
240. **[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*
241. **[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*
242. **[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*
243. [**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/)
244. **[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*
245. **[Democratizing LLMs for Low-Resource Languages by Leveraging their English Dominant Abilities with Linguistically-Diverse Prompts](https://md.research.elamur.ai/free/en/papers/nguyen-2024-democratizing-llms-low-resource-languages/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuan-Phi Nguyen, Mahani Aljunied, Shafiq Joty, et al.*2024 · 55 citations*
246. **[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*
247. **[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*
248. [**TellMeWhy: A Dataset for Answering Why-Questions in Narratives**Yash Kumar Lal, Nathanael Chambers, Raymond Mooney, et al.*2021 · 53 citations*](https://md.research.elamur.ai/free/en/papers/lal-2021-tellmewhy-dataset-answering-why-questions/)
249. [**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/)
250. **[Cultural Adaptation of Recipes](https://md.research.elamur.ai/free/en/papers/cao-2024-cultural-adaptation-recipes/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yong Cao, Yova Kementchedjhieva, Ruixiang Cui, et al.*2024 · 50 citations*
251. [**Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer**Eleftheria Briakou, Sweta Agrawal, Joel Tetreault, et al.*2021 · 49 citations*](https://md.research.elamur.ai/free/en/papers/briakou-2021-evaluating-evaluation-metrics-style-transfer/)
252. [**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/)
253. [**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/)
254. [**Weisfeiler-Leman in the Bamboo: Novel AMR Graph Metrics and a Benchmark for AMR Graph Similarity**Juri Opitz, Angel Daza, Anette Frank*2021 · 47 citations*](https://md.research.elamur.ai/free/en/papers/opitz-2021-weisfeiler-leman-bamboo-novel-amr/)
255. [**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/)
256. [**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/)
257. [**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/)
258. [**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/)
259. **[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*
260. **[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*
261. [**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/)
262. **[SLING: Sino Linguistic Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/song-2022-sling-sino-linguistic-evaluation-large/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yixiao Song, Kalpesh Krishna, Rajesh Bhatt, et al.*2022 · 41 citations*
263. [**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/)
264. [**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/)
265. **[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*
266. **[Towards Effective Disambiguation for Machine Translation with Large Language Models](https://md.research.elamur.ai/free/en/papers/iyer-2023-effective-disambiguation-machine-translation-large/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Vivek Iyer, Pinzhen Chen, Alexandra Birch*2023 · 38 citations*
267. [**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/)
268. **[Dolphin: A Challenging and Diverse Benchmark for Arabic NLG](https://md.research.elamur.ai/free/en/papers/nagoudi-2023-dolphin-challenging-diverse-benchmark-arabic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**El Moatez Billah Nagoudi, AbdelRahim Elmadany, Ahmed Oumar El-Shangiti, et al.*2023 · 35 citations*
269. [**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/)
270. [**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/)
271. [**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/)
272. [**Augmented Large Language Models with Parametric Knowledge Guiding arXiv:2305.04757**Ziyang Luo, Can Xu, Pu Zhao, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-augmented-large-language-models-parametric/)
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274. [**The Life Cycle of Knowledge in Big Language Models: A Survey arXiv:2303.07616 · Machine Intelligence Research. vol. 21, no. 2, pp. 217-238, 2024**Boxi Cao, Hongyu Lin, Xianpei Han, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-life-cycle-knowledge-big-language/)
275. [**ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline arXiv:2404.02893**Yifan Xu, Xiao Liu, Xinghan Liu, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-chatglm-math-improving-math/)
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277. [**Nemotron-4 15B Technical Report arXiv:2402.16819**Jupinder Parmar, Shrimai Prabhumoye, Joseph Jennings, et al.*2024 · 30 citations*](https://md.research.elamur.ai/free/en/papers/parmar-2024-nemotron-4-15b-technical-report/)
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284. [**A Technical Report for Polyglot-Ko: Open-Source Large-Scale Korean Language Models arXiv:2306.02254**Hyunwoong Ko, Kichang Yang, Minho Ryu, et al.*2023 · 28 citations*](https://md.research.elamur.ai/free/en/papers/ko-2023-technical-report-polyglot-ko-open/)
285. [**Pushing the Limits of ChatGPT on NLP Tasks arXiv:2306.09719**Xiaofei Sun, Linfeng Dong, Xiaoya Li, et al.*2023 · 28 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-pushing-limits-chatgpt-nlp-tasks/)
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288. [**Exploring the Relationship between LLM Hallucinations and Prompt Linguistic Nuances: Readability, Formality, and Concreteness arXiv:2309.11064**Vipula Rawte, Prachi Priya, S.M Towhidul Islam Tonmoy, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/rawte-2023-exploring-relationship-between-llm-hallucinations/)
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290. [**PlaSma: Making Small Language Models Better Procedural Knowledge Models for (Counterfactual) Planning arXiv:2305.19472**Faeze Brahman, Chandra Bhagavatula, Valentina Pyatkin, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/brahman-2023-plasma-making-small-language-models/)
291. [**Sentiment Analysis through LLM Negotiations arXiv:2311.01876**Xiaofei Sun, Xiaoya Li, Shengyu Zhang, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-sentiment-analysis-through-llm-negotiations/)
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293. [**TeleChat Technical Report arXiv:2401.03804**Zhongjiang He, Zihan Wang, Xinzhang Liu, et al.*2024 · 24 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-telechat-technical-report/)
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295. [**Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model arXiv:2404.04167**Xinrun Du; Zhouliang Yu; Songyang Gao; Ding Pan; Yuyang Cheng; Ziyang Ma; Ruibin Yuan; Xingwei Qu; Jiaheng Liu; Tianyu Zheng; Xinchen Luo; Guorui Zhou; Wenhu Chen;, Ge Zhang*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/du-2024-chinese-tiny-llm-pretraining/)
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