---
title: "Who cites Laurent Orseau — 67 papers of our library"
description: "67 papers of the Elamur Research library cite the works of Laurent Orseau, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/laurent-orseau/cited-by/"
---
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# Who cites Laurent Orseau

67 citations of their works from 67 papers of our library (of the 149,439 whose bibliographies we read) · 29 with a page here, the most cited first · [← Laurent Orseau](https://md.research.elamur.ai/free/en/authors/laurent-orseau/)

1. **[Survey of Hallucination in Natural Language Generation](https://md.research.elamur.ai/free/en/papers/ji-2022-survey-hallucination-natural-language-generation/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Ziwei Ji, Nayeon Lee, Rita Frieske, et al.*2022 · 5,974 citations*
2. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
3. **[LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2023-llmlingua-compressing-prompts-accelerated-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, et al.*2023 · 338 citations*
4. **[Large Language Models Are Zero-Shot Time Series Forecasters](https://md.research.elamur.ai/free/en/papers/gruver-2023-large-language-models-zero-shot/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Nate Gruver, Marc Finzi, Shikai Qiu, et al.*2023 · 268 citations*
5. [**Will we run out of data? Limits of LLM scaling based on human-generated data arXiv:2211.04325**Pablo Villalobos, Anson Ho, Jaime Sevilla, et al.*2022 · 198 citations*](https://md.research.elamur.ai/free/en/papers/villalobos-2022-will-run-out-data-limits/)
6. **[Large Language Diffusion Models](https://md.research.elamur.ai/free/en/papers/nie-2025-large-language-diffusion-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shen Nie, Fengqi Zhu, Zebin You, et al.*2025 · 178 citations*
7. [**Scaling Synthetic Data Creation with 1,000,000,000 Personas arXiv:2406.20094**Tao Ge, Xin Chan, Xiaoyang Wang, et al.*2024 · 171 citations*](https://md.research.elamur.ai/free/en/papers/ge-2024-scaling-synthetic-data-creation-1/)
8. [**LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression arXiv:2310.06839**Huiqiang Jiang, Qianhui Wu, Xufang Luo, et al.*2023 · 158 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2023-longllmlingua-accelerating-enhancing-llms-long/)
9. [**Hallucination of Multimodal Large Language Models: A Survey arXiv:2404.18930**Zechen Bai, Pichao Wang, Tianjun Xiao, et al.*2024 · 120 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-hallucination-multimodal-large-language-models/)
10. [**In-context Autoencoder for Context Compression in a Large Language Model arXiv:2307.06945**Tao Ge, Jing Hu, Lei Wang, et al.*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/ge-2023-context-autoencoder-context-compression-large/)
11. [**Skywork: A More Open Bilingual Foundation Model arXiv:2310.19341**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/)
12. [**Layer by Layer: Uncovering Hidden Representations in Language Models arXiv:2502.02013**Oscar Skean, Md Rifat Arefin, Dan Zhao, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/skean-2025-layer-layer-uncovering-hidden-representations/)
13. [**Language Models Can Teach Themselves to Program Better arXiv:2207.14502**Patrick Haluptzok, Matthew Bowers, Adam Tauman Kalai*2023 · 54 citations*](https://md.research.elamur.ai/free/en/papers/haluptzok-2023-language-models-can-teach-themselves/)
14. **[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*
15. [**A Survey on Deep Learning for Theorem Proving arXiv:2404.09939**Zhaoyu Li, Jialiang Sun, Logan Murphy, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-survey-deep-learning-theorem-proving/)
16. [**Evaluating Frontier Models for Dangerous Capabilities arXiv:2403.13793**Mary Phuong, Matthew Aitchison, Elliot Catt, et al.*2024 · 36 citations*](https://md.research.elamur.ai/free/en/papers/phuong-2024-evaluating-frontier-models-dangerous-capabilities/)
17. [**RWKV-7 "Goose" with Expressive Dynamic State Evolution arXiv:2503.14456**Bo Peng, Ruichong Zhang, Daniel Goldstein, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/peng-2025-rwkv-7-goose-expressive-dynamic/)
18. [**Entropy Law: The Story Behind Data Compression and LLM Performance arXiv:2407.06645**Mingjia Yin, Chuhan Wu, Yufei Wang, et al.*2024 · 22 citations*](https://md.research.elamur.ai/free/en/papers/yin-2024-entropy-law-story-behind-data/)
19. [**MoRAL: MoE Augmented LoRA for LLMs' Lifelong Learning arXiv:2402.11260**Shu Yang; Muhammad Asif Ali; Cheng-Long Wang; Lijie Hu;, Di Wang*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/yang-2024-moral-moe-augmented-lora-llms/)
20. [**The Vector Grounding Problem arXiv:2304.01481**Dimitri Coelho Mollo, Raphael Milliere*2023 · 20 citations*](https://md.research.elamur.ai/free/en/papers/mollo-2023-vector-grounding-problem/)
21. **[Pre-training Distillation for Large Language Models: A Design Space Exploration](https://md.research.elamur.ai/free/en/papers/peng-2025-pre-training-distillation-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hao Peng, Xin Lv, Yushi Bai, et al.*2025 · 14 citations*
22. [**Open-Endedness is Essential for Artificial Superhuman Intelligence arXiv:2406.04268**Edward Hughes, Michael Dennis, Jack Parker-Holder, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/hughes-2024-open-endedness-essential-artificial-superhuman/)
23. [**How Much Can RAG Help the Reasoning of LLM? arXiv:2410.02338**Jingyu Liu, Jiaen Lin, Yong Liu*2024 · 13 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-much-rag-help-reasoning-llm/)
24. **[CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challenges](https://md.research.elamur.ai/free/en/papers/wang-2026-creativebench-benchmarking-enhancing-machine-creativity/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zihan Wang, Lam Nguyen, Zhengyang Zhao, et al.*2026 · 6 citations*
25. **[Aligning Large Language Models via Fully Self-Synthetic Data](https://md.research.elamur.ai/free/en/papers/yin-2026-aligning-large-language-models-fully/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangjian Yin, Zhepei Wei, Xinyu Zhu, et al.*2026 · 2 citations*
26. **[From AR to Diffusion: Efficiently Adapting Large Language Models with Strictly Causal and Elastic Horizons](https://md.research.elamur.ai/free/en/papers/ma-2026-ar-diffusion-efficiently-adapting-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangyu Ma, Teng Xiao, Zuchao Li, et al.*2026*
27. [**Letters hide the truth from our eyes: English homophones have meaningfully different phonetic realizations arXiv:2608.26749**Yu-Hsiang Tseng, Mirjam T. C. Ernestus, Louis F. M. ten Bosch, et al.*2026*](https://md.research.elamur.ai/free/en/papers/tseng-2026-letters-hide-truth-eyes-english/)
28. **[Shuttle Between Symbolic Instructions and Neural Parameters of Large Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-shuttle-between-symbolic-instructions-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wangtao Sun, Haotian Xu, Huanxuan Liao, et al.*2026*
29. [**Shakespeare, Entropy and Educated Monkeys arXiv:2512.11880**Ioannis Kontoyiannis*2025*](https://md.research.elamur.ai/free/en/papers/kontoyiannis-2025-shakespeare-entropy-educated-monkeys/)

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

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