---
title: "Who cites Phillip Rust — 455 papers of our library"
description: "455 papers of the Elamur Research library cite the works of Phillip Rust, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Phillip Rust

458 citations of their works from 455 papers of our library (of the 149,439 whose bibliographies we read) · 138 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Phillip Rust](https://md.research.elamur.ai/free/en/authors/phillip-rust/)

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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 Interplay of Variant, Size, and Task Type in Arabic Pre-trained Language Models arXiv:2103.06678**Go Inoue, Bashar Alhafni, Nurpeiis Baimukan, et al.*2021 · 365 citations*](https://md.research.elamur.ai/free/en/papers/inoue-2021-interplay-variant-size-task-type/)
3. **[The “Problem” of Human Label Variation: On Ground Truth in Data, Modeling and Evaluation](https://md.research.elamur.ai/free/en/papers/plank-2022-problem-human-label-variation-ground/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Barbara Plank*2022 · 364 citations*
4. [**A Review of Large Language Models and Autonomous Agents in Chemistry arXiv:2407.01603**Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2024-review-large-language-models-autonomous/)
5. [**MEGA: Multilingual Evaluation of Generative AI arXiv:2303.12528**Kabir Ahuja, Harshita Diddee, Rishav Hada, et al.*2023 · 285 citations*](https://md.research.elamur.ai/free/en/papers/ahuja-2023-mega-multilingual-evaluation-generative-ai/)
6. **[Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study](https://md.research.elamur.ai/free/en/papers/cao-2023-assessing-cross-cultural-alignment-between/) [Workshop on Cross-Cultural Considerations in NLP](https://md.research.elamur.ai/free/en/venues/c3nlp/)**Yong Cao, Li Zhou, Seolhwa Lee, et al.*2023 · 279 citations*
7. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2023-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J. Ryan, Alan Ritter, et al.*2023 · 273 citations*
8. **[XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond](https://md.research.elamur.ai/free/en/papers/barbieri-2022-xlm-t-multilingual-language-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Francesco Barbieri, Luis Espinosa Anke, Jose Camacho-Collados*2022 · 271 citations*
9. **[The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://md.research.elamur.ai/free/en/papers/bandarkar-2023-belebele-benchmark-parallel-reading-comprehension/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lucas Bandarkar, Davis Liang, Benjamin Muller, et al.*2023 · 262 citations*
10. **[Language Model Tokenizers Introduce Unfairness Between Languages](https://md.research.elamur.ai/free/en/papers/petrov-2023-language-model-tokenizers-introduce-unfairness/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Aleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, et al.*2023 · 206 citations*
11. [**mGPT: Few-Shot Learners Go Multilingual arXiv:2204.07580**Oleh Shliazhko, Alena Fenogenova, Maria Tikhonova, et al.*2022 · 203 citations*](https://md.research.elamur.ai/free/en/papers/shliazhko-2022-mgpt-few-shot-learners-go/)
12. [**Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP arXiv:2112.10508**Sabrina J. Mielke, Zaid Alyafeai, Elizabeth Salesky, et al.*2021 · 191 citations*](https://md.research.elamur.ai/free/en/papers/mielke-2021-between-words-characters-brief-history/)
13. **[UNKs Everywhere: Adapting Multilingual Language Models to New Scripts](https://md.research.elamur.ai/free/en/papers/pfeiffer-2021-unks-everywhere-adapting-multilingual-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jonas Pfeiffer, Ivan Vulić, Iryna Gurevych, et al.*2021 · 176 citations*
14. **[Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models](https://md.research.elamur.ai/free/en/papers/ahia-2023-do-all-languages-cost-same/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.*2023 · 174 citations*
15. **[Lifting the Curse of Multilinguality by Pre-training Modular Transformers](https://md.research.elamur.ai/free/en/papers/pfeiffer-2022-lifting-curse-multilinguality-pre-training/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jonas Pfeiffer, Naman Goyal, Xi Victoria Lin, et al.*2022 · 174 citations*
16. [**SantaCoder: don't reach for the stars! arXiv:2301.03988**Loubna Ben Allal, Raymond Li, Denis Kocetkov, et al.*2023 · 167 citations*](https://md.research.elamur.ai/free/en/papers/allal-2023-santacoder-don-t-reach-stars/)
17. **[Probing Pre-Trained Language Models for Cross-Cultural Differences in Values](https://md.research.elamur.ai/free/en/papers/arora-2023-probing-pre-trained-language-models/) [Workshop on Cross-Cultural Considerations in NLP](https://md.research.elamur.ai/free/en/venues/c3nlp/)**Arnav Arora, Lucie-aimée Kaffee, Isabelle Augenstein*2023 · 156 citations*
18. **[BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages](https://md.research.elamur.ai/free/en/papers/myung-2024-blend-benchmark-llms-everyday-knowledge/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Junho Myung, Nayeon Lee, Yi Zhou, et al.*2024 · 152 citations*
19. **[Language Model Behavior: A Comprehensive Survey](https://md.research.elamur.ai/free/en/papers/chang-2024-language-model-behavior-comprehensive-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Tyler A. Chang, Benjamin K. Bergen*2024 · 148 citations*
20. **[What to Pre-Train on? Efficient Intermediate Task Selection](https://md.research.elamur.ai/free/en/papers/poth-2021-what-pre-train-efficient-intermediate/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Clifton Poth, Jonas Pfeiffer, Andreas Rücklé, et al.*2021 · 132 citations*
21. **[MAD-G: Multilingual Adapter Generation for Efficient Cross-Lingual Transfer](https://md.research.elamur.ai/free/en/papers/ansell-2021-mad-g-multilingual-adapter-generation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alan Ansell, Edoardo Maria Ponti, Jonas Pfeiffer, et al.*2021 · 130 citations*
22. **[AceGPT, Localizing Large Language Models in Arabic](https://md.research.elamur.ai/free/en/papers/huang-2024-acegpt-localizing-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Huang Huang, Fei Yu, Jianqing Zhu, et al.*2024 · 127 citations*
23. **[XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models](https://md.research.elamur.ai/free/en/papers/liang-2023-xlm-v-overcoming-vocabulary-bottleneck/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Davis Liang, Hila Gonen, Yuning Mao, et al.*2023 · 120 citations*
24. [**Benchmarking Machine Translation with Cultural Awareness arXiv:2305.14328**Binwei Yao, Ming Jiang, Tara Bobinac, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-benchmarking-machine-translation-cultural-awareness/)
25. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
26. **[Tokenizer Choice For LLM Training: Negligible or Crucial?](https://md.research.elamur.ai/free/en/papers/ali-2024-tokenizer-choice-llm-training-negligible/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mehdi Ali, Michael Fromm, Klaudia Thellmann, et al.*2024 · 104 citations*
27. **[Towards Measuring and Modeling “Culture” in LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/adilazuarda-2024-measuring-modeling-culture-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Muhammad Farid Adilazuarda, Sagnik Mukherjee, Pradhyumna Lavania, et al.*2024 · 102 citations*
28. [**FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every Language arXiv:2506.20920**Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.*2025 · 99 citations*](https://md.research.elamur.ai/free/en/papers/penedo-2025-fineweb2-one-pipeline-scale-them/)
29. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2024-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J Ryan, Alan Ritter, et al.*2024 · 95 citations*
30. **[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*
31. **[CultureBank: An Online Community-Driven Knowledge Base Towards Culturally Aware Language Technologies](https://md.research.elamur.ai/free/en/papers/shi-2024-culturebank-online-community-driven-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weiyan Shi, Ryan Li, Yutong Zhang, et al.*2024 · 93 citations*
32. **[WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models](https://md.research.elamur.ai/free/en/papers/minixhofer-2022-wechsel-effective-initialization-subword-embeddings/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Benjamin Minixhofer, Fabian Paischer, Navid Rekabsaz*2022 · 91 citations*
33. **[Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art](https://md.research.elamur.ai/free/en/papers/liu-2025-culturally-aware-adapted-nlp-taxonomy/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Chen Cecilia Liu, Iryna Gurevych, Anna Korhonen*2025 · 90 citations*
34. **[Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable Survey](https://md.research.elamur.ai/free/en/papers/kumar-2023-language-generation-models-can-cause/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, et al.*2023 · 90 citations*
35. **[Benchmarking Vision Language Models for Cultural Understanding](https://md.research.elamur.ai/free/en/papers/nayak-2024-benchmarking-vision-language-models-cultural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shravan Nayak, Kanishk Jain, Rabiul Awal, et al.*2024 · 87 citations*
36. **[When Is Multilinguality a Curse? Language Modeling for 250 High- and Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/chang-2024-when-is-multilinguality-curse-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tyler A. Chang, Catherine Arnett, Zhuowen Tu, et al.*2024 · 87 citations*
37. **[MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks](https://md.research.elamur.ai/free/en/papers/ahuja-2024-megaverse-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, et al.*2024 · 74 citations*
38. **[FORK: A Bite-Sized Test Set for Probing Culinary Cultural Biases in Commonsense Reasoning Models](https://md.research.elamur.ai/free/en/papers/palta-2023-fork-bite-sized-test-set/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shramay Palta, Rachel Rudinger*2023 · 67 citations*
39. **[FOCUS: Effective Embedding Initialization for Monolingual Specialization of Multilingual Models](https://md.research.elamur.ai/free/en/papers/dobler-2023-focus-effective-embedding-initialization-monolingual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Konstantin Dobler, Gerard de Melo*2023 · 62 citations*
40. **[Culturally Aware Natural Language Inference](https://md.research.elamur.ai/free/en/papers/huang-2023-culturally-aware-natural-language-inference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jing Huang, Diyi Yang*2023 · 61 citations*
41. [**Massively Multi-Cultural Knowledge Acquisition & LM Benchmarking arXiv:2402.09369**Yi Fung, Ruining Zhao, Jae Doo, et al.*2024 · 56 citations*](https://md.research.elamur.ai/free/en/papers/fung-2024-massively-multi-cultural-knowledge-acquisition/)
42. **[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*
43. **[IndoCulture: Exploring Geographically Influenced Cultural Commonsense Reasoning Across Eleven Indonesian Provinces](https://md.research.elamur.ai/free/en/papers/koto-2024-indoculture-exploring-geographically-influenced-cultural/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Fajri Koto, Rahmad Mahendra, Nurul Aisyah, et al.*2024 · 53 citations*
44. **[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*
45. **[The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm](https://md.research.elamur.ai/free/en/papers/aakanksha-2024-multilingual-alignment-prism-aligning-global/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Aakanksha, Arash Ahmadian, Beyza Ermis, et al.*2024 · 49 citations*
46. [**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/)
47. [**Pre-training Data Quality and Quantity for a Low-Resource Language: New Corpus and BERT Models for Maltese Proceedings of the Third Workshop on Deep Learning for Low-Resource Natural Language Processing**Kurt Micallef, Albert Gatt, Marc Tanti, et al.*2022 · 41 citations*](https://md.research.elamur.ai/free/en/papers/micallef-2022-pre-training-data-quality-quantity/)
48. **[CulturalBench: A Robust, Diverse and Challenging Benchmark for Measuring LMs' Cultural Knowledge Through Human-AI Red-Teaming](https://md.research.elamur.ai/free/en/papers/chiu-2025-culturalbench-robust-diverse-challenging-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Ying Chiu, Liwei Jiang, Bill Yuchen Lin, et al.*2025 · 38 citations*
49. **[Should We Ban English NLP for a Year?](https://md.research.elamur.ai/free/en/papers/sogaard-2022-should-we-ban-english-nlp/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Anders Søgaard*2022 · 38 citations*
50. **[Culture is Not Trivia: Sociocultural Theory for Cultural NLP](https://md.research.elamur.ai/free/en/papers/zhou-2025-culture-is-not-trivia-sociocultural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Naitian Zhou, David Bamman, Isaac L. Bleaman*2025 · 33 citations*
51. [**BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models arXiv:2309.06085**Wei Qi Leong, Jian Gang Ngui, Yosephine Susanto, et al.*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/leong-2023-bhasa-holistic-southeast-asian-linguistic/)
52. **[Compositional Evaluation on Japanese Textual Entailment and Similarity](https://md.research.elamur.ai/free/en/papers/yanaka-2022-compositional-evaluation-japanese-textual-entailment/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Hitomi Yanaka, Koji Mineshima*2022 · 33 citations*
53. **[DOSA: A Dataset of Social Artifacts from Different Indian Geographical Subcultures](https://md.research.elamur.ai/free/en/papers/seth-2024-dosa-dataset-social-artifacts-different/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Agrima Seth, Sanchit Ahuja, Kalika Bali, et al.*2024 · 29 citations*
54. **[Languages Through the Looking Glass of BPE Compression](https://md.research.elamur.ai/free/en/papers/vasques-2023-languages-through-looking-glass-bpe/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Ximena Gutierrez-Vasques, Christian Bentz, Tanja Samardžić*2023 · 26 citations*
55. **[Middle-Layer Representation Alignment for Cross-Lingual Transfer in Fine-Tuned LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-middle-layer-representation-alignment-cross/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Danni Liu, Jan Niehues*2025 · 23 citations*
56. **[Modeling Cross-Cultural Pragmatic Inference with Codenames Duet](https://md.research.elamur.ai/free/en/papers/shaikh-2023-modeling-cross-cultural-pragmatic-inference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Omar Shaikh, Caleb Ziems, William Held, et al.*2023 · 23 citations*
57. [**Efficiently Adapting Pretrained Language Models To New Languages arXiv:2311.05741**Zoltan Csaki, Pian Pawakapan, Urmish Thakker, et al.*2023 · 21 citations*](https://md.research.elamur.ai/free/en/papers/csaki-2023-efficiently-adapting-pretrained-language-models/)
58. **[MAGNET: Improving the Multilingual Fairness of Language Models with Adaptive Gradient-Based Tokenization](https://md.research.elamur.ai/free/en/papers/ahia-2024-magnet-improving-multilingual-fairness-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.*2024 · 19 citations*
59. **[Multi 3 WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems](https://md.research.elamur.ai/free/en/papers/hu-2023-multi-3-woz-multilingual-multi/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Songbo Hu, Han Zhou, Mete Hergul, et al.*2023 · 17 citations*
60. **[Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys](https://md.research.elamur.ai/free/en/papers/cao-2024-bridging-cultural-nuances-dialogue-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yong Cao, Min Chen, Daniel Hershcovich*2024 · 16 citations*
61. **[Bridging Cultures in the Kitchen: A Framework and Benchmark for Cross-Cultural Recipe Retrieval](https://md.research.elamur.ai/free/en/papers/hu-2024-bridging-cultures-kitchen-framework-benchmark/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianyi Hu, Maria Maistro, Daniel Hershcovich*2024 · 16 citations*
62. **[LLäMmlein: Transparent, Compact and Competitive German-Only Language Models from Scratch](https://md.research.elamur.ai/free/en/papers/pfister-2025-llammlein-transparent-compact-competitive-german/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jan Pfister, Julia Wunderle, Andreas Hotho*2025 · 15 citations*
63. **[Less, but Better: Efficient Multilingual Expansion for LLMs via Layer-wise Mixture-of-Experts](https://md.research.elamur.ai/free/en/papers/zhang-2025-less-but-better-efficient-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xue Zhang, Yunlong Liang, Fandong Meng, et al.*2025 · 13 citations*
64. **[Bridging Background Knowledge Gaps in Translation with Automatic Explicitation](https://md.research.elamur.ai/free/en/papers/han-2023-bridging-background-knowledge-gaps-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**HyoJung Han, Jordan Boyd-Graber, Marine Carpuat*2023 · 13 citations*
65. **[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*
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