---
title: "Who cites Cyprien de Masson — page 5 — 1,364 citing papers"
description: "1,364 papers of the Elamur Research library cite the works of Cyprien de Masson d'Autume, found in their bibliographies · page 5 of 5…"
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# Who cites Cyprien de Masson d'Autume

1,404 citations of their works from 1,364 papers of our library (of the 149,439 whose bibliographies we read) · 438 with a page here, the most cited first · page 5 of 5 · 401–438 · [← Cyprien de Masson d'Autume](https://md.research.elamur.ai/free/en/authors/cyprien-de-masson-d-autume/)

[← prev](https://md.research.elamur.ai/free/en/authors/cyprien-de-masson-d-autume/cited-by/page/4/) [1](https://md.research.elamur.ai/free/en/authors/cyprien-de-masson-d-autume/cited-by/) … [4](https://md.research.elamur.ai/free/en/authors/cyprien-de-masson-d-autume/cited-by/page/4/) **5**

401. **[ArabicWeb-Edu: Educational Quality Data for Arabic LLM Training](https://md.research.elamur.ai/free/en/papers/hawasly-2025-arabicweb-edu-educational-quality-data/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Majd Hawasly, Tasnim Mohiuddin, Hamdy Mubarak, et al.*2025 · 1 citation*
402. [**Mix, MinHash, and Match: Cross-Source Agreement for Multilingual Pretraining Datasets arXiv:2512.18834**Sultan Alrashed, Francesco Orabona*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/alrashed-2025-mix-minhash-match-cross-source/)
403. **[Deep Learning Based Code Generation Methods: Literature Review (基于深度学习的代码生成方法研究进展)](https://md.research.elamur.ai/free/en/papers/yang-2023-deep-learning-code/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Zezhou Yang (杨泽洲), Sirong Chen (陈思榕), Cuiyun Gao (高翠芸), et al.*2023 · 1 citation*
404. **[A Survey of Reinforcement Learning for Large Language Models under Data Scarcity: Challenges and Solutions](https://md.research.elamur.ai/free/en/papers/yu-2026-survey-reinforcement-learning-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhiyin Yu, Yuchen Mou, Juncheng Yan, et al.*2026*
405. **[Agent-Ops: A Multi-Agent Orchestration Framework for End-to-End SOP Automation in E-Commerce Operations](https://md.research.elamur.ai/free/en/papers/singh-2026-agent-ops-multi-agent-orchestration/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Apoorva Singh, Sanjay Agrawal, Sayanta Adhikari, et al.*2026*
406. **[AlgBench: To What Extent Do Large Reasoning Models Understand Algorithms?](https://md.research.elamur.ai/free/en/papers/sun-2026-algbench-what-extent-do-large/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Henan Sun, Kaichi Yu, Yuyao Wang, et al.*2026*
407. **[AlphaQT-Bench: Diagnosing the Gap between Financial Code Generation and Quantitative Reasoning in LLMs](https://md.research.elamur.ai/free/en/papers/luo-2026-alphaqt-bench-diagnosing-gap-between/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sichun Luo, Yi Huang, Shichang Meng, et al.*2026*
408. **[code-transformed: The Influence of Large Language Models on Code](https://md.research.elamur.ai/free/en/papers/xu-2026-code-transformed-influence-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuliang Xu, Siming Huang, Mingmeng Geng, et al.*2026*
409. **[CodeRM-NT: Reward Model for Code RL without Unit Tests](https://md.research.elamur.ai/free/en/papers/xia-2026-coderm-nt-reward-model-code/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiao Xia, Dan Zhang, Tianrui Sun*2026*
410. **[Contract-Coding: Towards Repo-Level Generation via Structured Symbolic Paradigm](https://md.research.elamur.ai/free/en/papers/yilin-2026-contract-coding-repo-level-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yilin, Lujin Zhao, Yijie Shi*2026*
411. **[Deriving Character Logic from Storyline as Codified Decision Trees](https://md.research.elamur.ai/free/en/papers/peng-2026-deriving-character-logic-storyline-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Letian Peng, Kun Zhou, Longfei Yun, et al.*2026*
412. **[Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model Factuality](https://md.research.elamur.ai/free/en/papers/zhang-2026-follow-path-reasoning-over-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mike Zhang, Johannes Bjerva, Russa Biswas*2026*
413. [**HEBATRON: A Hebrew-Specialized Open-Weight Mixture-of-Experts Language Model**Noam Kayzer, Dan Revital, Ori Bar Joseph, et al.*2026*](https://md.research.elamur.ai/free/en/papers/kayzer-2026-hebatron-hebrew-specialized-open-weight/)
414. **[HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs](https://md.research.elamur.ai/free/en/papers/peng-2026-hss-synth-humanities-social-sciences/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ru Peng, Tianyu Zhao, Xijun Gu, et al.*2026*
415. **[LLMs are Brittle to Simple Code Transformations: Introducing CETBench – A Benchmark for Code-Equivalence Checking](https://md.research.elamur.ai/free/en/papers/oza-2026-llms-are-brittle-simple-code/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Neeva Oza, Ishaan Govil, Parul Gupta, et al.*2026*
416. **[MaskTab: Scalable Masked Tabular Pretraining with Scaling Laws and Distillation for Industrial Classification](https://md.research.elamur.ai/free/en/papers/zheng-2026-masktab-scalable-masked-tabular-pretraining/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bo Zheng, Yudong Chen, Zihua Xiong, et al.*2026*
417. **[MavenCoder: Competitive Code Generation via Model Adaptive Planning Strategies and Multi-Perspective Verification Enhancement](https://md.research.elamur.ai/free/en/papers/xu-2026-mavencoder-competitive-code-generation-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**ZhenChun Xu, Yi Cai, Dajun Zheng, et al.*2026*
418. **[Merge and Conquer: Instructing Multilingual Models by Adding Target Language Weights](https://md.research.elamur.ai/free/en/papers/valero-2026-merge-conquer-instructing-multilingual-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Eneko Valero, Maria Ribalta i Albado, Oscar Sainz, et al.*2026*
419. **[Multimodal LLMs Do Not Compose Skills Optimally across Modalities](https://md.research.elamur.ai/free/en/papers/ontalvilla-2026-multimodal-llms-do-not-compose/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Paula Ontalvilla, Aitor Ormazabal, Gorka Azkune*2026*
420. **[MUTANT: A Recipe for Multilingual Tokenizer Design](https://md.research.elamur.ai/free/en/papers/rana-2026-mutant-recipe-multilingual-tokenizer-design/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Souvik Rana, Ashish Kulkarni, Arul Menezes, et al.*2026*
421. **[MzansiText and MzansiLM: An Open Corpus and Decoder-Only Language Model for South African Languages](https://md.research.elamur.ai/free/en/papers/lombard-2026-mzansitext-mzansilm-open-corpus-decoder/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Anri M. Lombard, Simbarashe Mawere, Temi Aina, et al.*2026*
422. **[On the Cultural Anachronism and Temporal Reasoning in Vision Language Models](https://md.research.elamur.ai/free/en/papers/ranjan-2026-cultural-anachronism-temporal-reasoning-vision/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mukul Ranjan, Prince Jha, Khushboo Kumari, et al.*2026*
423. **[Parallel-SFT: Improving Zero-Shot Cross-Programming-Language Transfer for Code RL](https://md.research.elamur.ai/free/en/papers/wu-2026-parallel-sft-improving-zero-shot/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhaofeng Wu, Shiqi Wang, Boya Peng, et al.*2026*
424. **[Parallelism and Generation Order in Masked Diffusion Language Models: Limits Today, Potential Tomorrow](https://md.research.elamur.ai/free/en/papers/zhong-2026-parallelism-generation-order-masked-diffusion/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yangyang Zhong, Yanmei Gu, Zhengqing Zang, et al.*2026*
425. **[PaT: Planning-after-Trial for Efficient Test-Time Code Generation](https://md.research.elamur.ai/free/en/papers/yoon-2026-pat-planning-after-trial-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youngsik Yoon, Sungjae Lee, Seockbean Song, et al.*2026*
426. [**Repetition over Diversity: High-Signal Data Filtering for Sample-Efficient German Language Modeling arXiv:2604.28075**Ansar Aynetdinov, Patrick Haller, Alan Akbik*2026*](https://md.research.elamur.ai/free/en/papers/aynetdinov-2026-repetition-over-diversity-high-signal/)
427. **[R³: End-to-End Reasoning-based Planning for Multi-step Retrosynthesis via Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/wang-2026-r-3-end-end-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**YiFei Wang, Qizhi Pei, Jiangtao Feng, et al.*2026*
428. **[ScaleBox: Enabling High-Fidelity and Scalable Code Verification for Large Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-scalebox-enabling-high-fidelity-scalable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiasheng Zheng, Xin Zheng, Boxi Cao, et al.*2026*
429. **[SELECting over Tokens: Curating Pre-training Data at Scale via Token Classification](https://md.research.elamur.ai/free/en/papers/tong-2026-selecting-over-tokens-curating-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xin Tong, Weidong Zhang, Jiaang Li, et al.*2026*
430. [**The Validity of Coreference-based Evaluations of Natural Language Understanding arXiv:2602.16200**Ian Porada*2026*](https://md.research.elamur.ai/free/en/papers/porada-2026-validity-coreference-based-evaluations-natural/)
431. **[Toward Consistent World Models with Multi-Token Prediction and Latent Semantic Enhancement](https://md.research.elamur.ai/free/en/papers/zhong-2026-consistent-world-models-multi-token/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qimin Zhong, Hao Liao, Haiming Qin, et al.*2026*
432. **[Tree-Notebook: A Context-Aware Agent with Tree Search and Entropy-Aware Data Shadow for Interactive Data Science](https://md.research.elamur.ai/free/en/papers/qiu-2026-tree-notebook-context-aware-agent/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junkun Qiu, Min Huang, Qinghai Miao*2026*
433. **[Vector Calligrapher: Generating Scalable Vector Graphics via Structured Linguistic Supervision](https://md.research.elamur.ai/free/en/papers/zhou-2026-vector-calligrapher-generating-scalable-vector/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bo Zhou, Xikang Chen, Yan Gong, et al.*2026*
434. **[Verifier-Free RL for LLMs via Intrinsic Gradient-Norm Reward](https://md.research.elamur.ai/free/en/papers/wen-2026-verifier-free-rl-llms-intrinsic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xuexiang Wen, Hang Yu, Linchao Zhu, et al.*2026*
435. **[Survey on Code Generation with LLM-based Agents (基于大语言模型智能体的代码生成综述)](https://md.research.elamur.ai/free/en/papers/dong-2025-code-generation-llm/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yihong Dong (董益宏), Xue Jiang (姜雪), Jiaru Qian (钱家如), et al.*2025*
436. **[Survey on Key Technologies for Large Language Model Pre-training Systems (大语言模型预训练系统关键技术综述)](https://md.research.elamur.ai/free/en/papers/gao-2025-key-technologies-large/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yanjie Gao (高彦杰), Yueguo Chen (陈跃国)*2025*
437. [**Wasm: A Pipeline for Constructing Structured Arabic Interleaved Multimodal Corpora arXiv:2511.07080**Khalil Hennara; Ahmad Bastati; Muhammad Hreden; Mohamed Motasim Hamed; Zeina Aldallal; Sara Chrouf;, Safwan AlModhayan*2025*](https://md.research.elamur.ai/free/en/papers/hennara-2025-wasm-pipeline-constructing-structured-arabic/)
438. [**On the importance of Data Scale in Pretraining Arabic Language Models arXiv:2401.07760**Abbas Ghaddar, Philippe Langlais, Mehdi Rezagholizadeh, et al.*2024*](https://md.research.elamur.ai/free/en/papers/ghaddar-2024-importance-data-scale-pretraining-arabic/)

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