---
title: "Who cites Étienne Goffinet"
description: "336 papers of the Elamur Research library cite the works of Étienne Goffinet, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/etienne-goffinet/cited-by/"
---
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# Who cites Étienne Goffinet

337 citations of their works from 336 papers of our library (of the 140,884 whose bibliographies we read) · 31 with a page here, the most cited first · [← Étienne Goffinet](https://md.research.elamur.ai/free/en/authors/etienne-goffinet/)

1. [**LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models**Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.*2024 · 1,035 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2024-llamafactory-unified-efficient-fine-tuning/)
2. [**BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 406 citations*](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/)
3. [**InternLM2 Technical Report**Zheng Cai, Maosong Cao, Haojiong Chen, et al.*2024 · 299 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-internlm2-technical-report/)
4. [**MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies**Shengding Hu, Yuge Tu, Xu Han, et al.*2024 · 258 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-minicpm-unveiling-potential-small-language/)
5. [**RedPajama: an Open Dataset for Training Large Language Models**Maurice Weber, Daniel Fu, Quentin Anthony, et al.*2024 · 247 citations*](https://md.research.elamur.ai/free/en/papers/weber-2024-redpajama-open-dataset-training-large/)
6. [**Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset**Ke Wang, Junting Pan, Weikang Shi, et al.*2024 · 198 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-measuring-multimodal-mathematical-reasoning-math/)
7. [**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/)
8. [**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/)
9. [**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/)
10. [**QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks**Albert Tseng, Jerry Chee, Qingyao Sun, et al.*2024 · 116 citations*](https://md.research.elamur.ai/free/en/papers/tseng-2024-quip-even-better-llm-quantization/)
11. [**DistiLLM: Towards Streamlined Distillation for Large Language Models**Jongwoo Ko, Sungnyun Kim, Tianyi Chen, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/ko-2024-distillm-towards-streamlined-distillation-large/)
12. [**Getting the most out of your tokenizer for pre-training and domain adaptation**Gautier Dagan, Gabriel Synnaeve, Baptiste Roziere*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dagan-2024-getting-most-out-tokenizer-pre/)
13. [**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/)
14. [**Towards Cross-Tokenizer Distillation: the Universal Logit Distillation Loss for LLMs**Nicolas Boizard, Kevin El Haddad, Celine Hudelot, et al.*2024 · 34 citations*](https://md.research.elamur.ai/free/en/papers/boizard-2024-towards-cross-tokenizer-distillation-universal/)
15. [**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/)
16. [**Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models — The Story Goes On**Liang Zeng, Liangjun Zhong, Liang Zhao, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-skywork-math-data-scaling-laws/)
17. [**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/)
18. [**HAMiSoN-Generative at ClimateActivism 2024: Stance Detection using generative large language models**Jesus M. Fraile-Hernandez, Anselmo Peñas*2024 · 4 citations*](https://md.research.elamur.ai/free/en/papers/hernandez-2024-hamison-generative-climateactivism-2024-stance/)
19. [**No Context Needed: Contextual Quandary In Idiomatic Reasoning With Pre-Trained Language Models**Kellen Tan Cheng, Suma Bhat*2024 · 3 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2024-no-context-needed-contextual-quandary/)
20. [**Arabic Sentence Segmentation Across Genres and Punctuation Conditions**Mohammed Elkholy, Khalid N. Elmadani, Nizar Habash, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/elkholy-2026-arabic-sentence-segmentation-across-genres/)
21. [**Can Dialects Be Steered Like Languages? Sparse Neurons and Distributed Directions in Arabic LLMs**Kareem Elozeiri, Mervat Abassy, Omar Kallas, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/elozeiri-2026-dialects-steered-like-languages-sparse/)
22. [**Large Language Models for Citation Function Classification**Daniel Vodička, Pavel Kral, Christophe Cerisara, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/vodicka-2026-large-language-models-citation-function/)
23. [**Spotlights and Blindspots: Evaluating Machine-Generated Text Detection**Kevin Stowe, Kailash Patil*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/stowe-2026-spotlights-blindspots-evaluating-machine-generated/)
24. [**Are Arabic Benchmarks Reliable? QIMMA's Quality-First Approach to LLM Evaluation**Leen AlQadi, Ahmed Alzubaidi, Mohammed Alyafeai, et al.*2026*](https://md.research.elamur.ai/free/en/papers/alqadi-2026-arabic-benchmarks-reliable-qimma-s/)
25. [**Beyond Cultural Knowledge: Evaluating Arabic Cultural Appropriateness of Large Language Models**Enes Altinisik, Hamdy Mubarak, Masoomali Fatehkia, et al.*2026*](https://md.research.elamur.ai/free/en/papers/altinisik-2026-cultural-knowledge-evaluating-arabic-cultural/)
26. [**GhostWriter: Hidden AI-Generated Texts over Multiple Languages, Domains and Generators**Manuel Schaaf, Kevin Bönisch, Alexander Mehler*2026*](https://md.research.elamur.ai/free/en/papers/schaaf-2026-ghostwriter-hidden-ai-generated-texts/)
27. [**Grounding Arabic LLMs in the Doha Historical Dictionary: Retrieval-Augmented Understanding of Quran and Hadith**Somaya Eltanbouly, Samer Rashwani*2026*](https://md.research.elamur.ai/free/en/papers/eltanbouly-2026-grounding-arabic-llms-doha-historical/)
28. [**SalamahBench: Dialect and Category Level Safety Evaluation of Arabic Language Models**Omar Abdelnasser, Fatemah Alharbi, Khaled Khasawneh, et al.*2026*](https://md.research.elamur.ai/free/en/papers/abdelnasser-2026-salamahbench-dialect-category-level-safety/)
29. [**Some Dialects Are More Equal Than Others: Non-Prestigious Arabic Dialectal Bias in LLMs**Mai Mohamed Eida, Ryan Dolan, Paul de Nijs, et al.*2026*](https://md.research.elamur.ai/free/en/papers/eida-2026-some-dialects-more-equal-than/)
30. [**When Similar Means Different: Evaluating LLMs on Arabic–Hebrew Cognates**Junhong Liang, Noor Abo Mokh, Bashar Alhafni*2026*](https://md.research.elamur.ai/free/en/papers/liang-2026-similar-means-different-evaluating-llms/)
31. [**YallaMorph: A Benchmark for Evaluating Arabic Morphological Generation in Large Language Models**Mahmoud Reda, Salam Khalifa, Reham Marzouk, et al.*2026*](https://md.research.elamur.ai/free/en/papers/reda-2026-yallamorph-benchmark-evaluating-arabic-morphological/)

305 more citing papers of our library have no page here yet.

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