---
title: "Who cites Gautier Dagan — 140 papers of our library"
description: "140 papers of the Elamur Research library cite the works of Gautier Dagan, found in their bibliographies; the most cited first."
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---
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# Who cites Gautier Dagan

140 citations of their works from 140 papers of our library (of the 149,439 whose bibliographies we read) · 38 with a page here, the most cited first · [← Gautier Dagan](https://md.research.elamur.ai/free/en/authors/gautier-dagan/)

1. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
2. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
3. [**Crosslingual Generalization through Multitask Finetuning arXiv:2211.01786**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 703 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/)
4. **[DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models](https://md.research.elamur.ai/free/en/papers/wang-2023-decodingtrust-comprehensive-assessment-trustworthiness-gpt/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Boxin Wang, Weixin Chen, Hengzhi Pei, et al.*2023 · 259 citations*
5. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model arXiv:2402.07827**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 253 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/)
6. [**Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicity arXiv:2301.12867**Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al.*2023 · 249 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2023-red-teaming-chatgpt-jailbreaking-bias/)
7. **[Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/singh-2024-aya-dataset-open-access-collection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shivalika Singh, Freddie Vargus, Daniel D'souza, et al.*2024 · 207 citations*
8. [**BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions arXiv:2406.15877**Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.*2024 · 176 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2024-bigcodebench-benchmarking-code-generation-diverse/)
9. [**Generative Representational Instruction Tuning arXiv:2402.09906**Niklas Muennighoff, Hongjin Su, Liang Wang, et al.*2024 · 172 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2024-generative-representational-instruction-tuning/)
10. **[Measure and Improve Robustness in NLP Models: A Survey](https://md.research.elamur.ai/free/en/papers/wang-2022-measure-improve-robustness-nlp-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xuezhi Wang, Haohan Wang, Diyi Yang*2022 · 148 citations*
11. [**Understanding the planning of LLM agents: A survey arXiv:2402.02716**Xu Huang, Weiwen Liu, Xiaolong Chen, et al.*2024 · 128 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-understanding-planning-llm-agents-survey/)
12. [**Fanar: An Arabic-Centric Multimodal Generative AI Platform arXiv:2501.13944**Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.*2025 · 127 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2025-fanar-arabic-centric-multimodal-generative/)
13. [**Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future arXiv:2309.15402**Zheng Chu, Jingchang Chen, Qianglong Chen, et al.*2023 · 125 citations*](https://md.research.elamur.ai/free/en/papers/chu-2023-navigate-through-enigmatic-labyrinth-survey/)
14. [**UI-TARS: Pioneering Automated GUI Interaction with Native Agents arXiv:2501.12326**Yujia Qin, Yining Ye, Junjie Fang, et al.*2025 · 112 citations*](https://md.research.elamur.ai/free/en/papers/qin-2025-ui-tars-pioneering-automated/)
15. [**MMTEB: Massive Multilingual Text Embedding Benchmark arXiv:2502.13595**Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.*2025 · 103 citations*](https://md.research.elamur.ai/free/en/papers/enevoldsen-2025-mmteb-massive-multilingual-text-embedding/)
16. [**FireAct: Toward Language Agent Fine-tuning arXiv:2310.05915**Baian Chen, Chang Shu, Ehsan Shareghi, et al.*2023 · 101 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-fireact-toward-language-agent-fine/)
17. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
18. **[NLPositionality: Characterizing Design Biases of Datasets and Models](https://md.research.elamur.ai/free/en/papers/santy-2023-nlpositionality-characterizing-design-biases-datasets/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sebastin Santy, Jenny Liang, Ronan Le Bras, et al.*2023 · 95 citations*
19. **[Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling](https://md.research.elamur.ai/free/en/papers/maini-2024-rephrasing-web-recipe-compute-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pratyush Maini, Skyler Seto, Richard Bai, et al.*2024 · 90 citations*
20. [**Multi-lingual Evaluation of Code Generation Models arXiv:2210.14868**Ben Athiwaratkun, Sanjay Krishna Gouda, Zijian Wang, et al.*2022 · 86 citations*](https://md.research.elamur.ai/free/en/papers/athiwaratkun-2022-multi-lingual-evaluation-code-generation/)
21. **[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*
22. **[PlanGenLLMs: A Modern Survey of LLM Planning Capabilities](https://md.research.elamur.ai/free/en/papers/wei-2025-plangenllms-modern-survey-llm-planning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hui Wei, Zihao Zhang, Shenghua He, et al.*2025 · 55 citations*
23. **[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*
24. [**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/)
25. **[Parity-Aware Byte-Pair Encoding: Improving Cross-lingual Fairness in Tokenization](https://md.research.elamur.ai/free/en/papers/foroutan-2026-parity-aware-byte-pair-encoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Negar Foroutan, Clara Meister, Debjit Paul, et al.*2026 · 12 citations*
26. **[How Can We Effectively Expand the Vocabulary of LLMs with 0.01GB of Target Language Text?](https://md.research.elamur.ai/free/en/papers/yamaguchi-2026-how-can-we-effectively-expand/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Atsuki Yamaguchi, Aline Villavicencio, Nikolaos Aletras*2026 · 11 citations*
27. **[Egalitarian Language Representation in Language Models: It All Begins with Tokenizers](https://md.research.elamur.ai/free/en/papers/velayuthan-2025-egalitarian-language-representation-language-models/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Menan Velayuthan, Kengatharaiyer Sarveswaran*2025 · 11 citations*
28. **[Retrofitting Large Language Models with Dynamic Tokenization](https://md.research.elamur.ai/free/en/papers/feher-2025-retrofitting-large-language-models-dynamic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Darius Feher, Ivan Vulić, Benjamin Minixhofer*2025 · 11 citations*
29. [**CLEVA: Chinese Language Models EVAluation Platform arXiv:2308.04813**Yanyang Li, Jianqiao Zhao, Duo Zheng, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-cleva-chinese-language-models/)
30. **[Planning with Multi-Constraints via Collaborative Language Agents](https://md.research.elamur.ai/free/en/papers/zhang-2025-planning-multi-constraints-collaborative-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Cong Zhang, Xin Deik Goh, Dexun Li, et al.*2025 · 10 citations*
31. [**Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles arXiv:2410.09303**Buu Phan, Brandon Amos, Itai Gat, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/phan-2024-exact-byte-level-probabilities-tokenized/)
32. **[Teaching Old Tokenizers New Words: Efficient Tokenizer Adaptation for Pretrained Models](https://md.research.elamur.ai/free/en/papers/purason-2026-teaching-old-tokenizers-new-words/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Taido Purason, Pavel Chizhov, Ivan P. Yamshchikov, et al.*2026 · 4 citations*
33. **[FLEXITOKENS: Flexible Tokenization for Evolving Language Models](https://md.research.elamur.ai/free/en/papers/owodunni-2026-flexitokens-flexible-tokenization-evolving-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Abraham Toluwase Owodunni, Orevaoghene Ahia, Sachin Kumar*2026 · 3 citations*
34. **[Vocab Diet: Reshaping the Vocabulary of LLMs via Vector Arithmetic](https://md.research.elamur.ai/free/en/papers/reif-2026-vocab-diet-reshaping-vocabulary-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuval Reif, Guy Kaplan, Roy Schwartz*2026 · 1 citation*
35. **[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*
36. **[RAMP: Risk-Aware Multi-Turn Planning for Jailbreak Red-Teaming](https://md.research.elamur.ai/free/en/papers/liu-2026-ramp-risk-aware-multi-turn/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yize Liu, Yunyun Hou, Aina Sui*2026*
37. **[The Impact of Tokenization Algorithms on Hungarian Language Model Performance](https://md.research.elamur.ai/free/en/papers/osvath-2026-impact-tokenization-algorithms-hungarian-language/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mátyás Osváth, Máté Norbert Molnár, Roland Gunics, et al.*2026*
38. **[TReX: Tokenizer Regression for Optimal Data Mixture](https://md.research.elamur.ai/free/en/papers/won-2026-trex-tokenizer-regression-optimal-data/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Inho Won, Hangyeol Yoo, Minkyung Cho, et al.*2026*

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

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