---
title: "Who cites Nathan Cooper — 376 papers of our library"
description: "376 papers of the Elamur Research library cite the works of Nathan Cooper, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/nathan-cooper/cited-by/"
---
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# Who cites Nathan Cooper

376 citations of their works from 376 papers of our library (of the 149,439 whose bibliographies we read) · 81 with a page here, the most cited first · [← Nathan Cooper](https://md.research.elamur.ai/free/en/authors/nathan-cooper/)

1. [**The Llama 3 Herd of Models arXiv:2407.21783**Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.*2024 · 7,682 citations*](https://md.research.elamur.ai/free/en/papers/grattafiori-2024-llama-3-herd-models/)
2. [**A Survey on Large Language Models for Code Generation arXiv:2406.00515**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
3. [**Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs arXiv:2410.18451**Chris Yuhao Liu, Liang Zeng, Jiacai Liu, et al.*2024 · 112 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-skywork-reward-bag-tricks/)
4. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/)
5. [**mmBERT: A Modern Multilingual Encoder with Annealed Language Learning arXiv:2509.06888**Marc Marone, Orion Weller, William Fleshman, et al.*2025 · 59 citations*](https://md.research.elamur.ai/free/en/papers/marone-2025-mmbert-modern-multilingual-encoder-annealed/)
6. [**Hymba: A Hybrid-head Architecture for Small Language Models arXiv:2411.13676**Xin Dong, Yonggan Fu, Shizhe Diao, et al.*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-hymba-hybrid-head-architecture-small/)
7. **[Fishing for Magikarp: Automatically Detecting Under-trained Tokens in Large Language Models](https://md.research.elamur.ai/free/en/papers/land-2024-fishing-magikarp-automatically-detecting-under/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sander Land, Max Bartolo*2024 · 42 citations*
8. [**EuroBERT: Scaling Multilingual Encoders for European Languages arXiv:2503.05500**Nicolas Boizard, Hippolyte Gisserot-Boukhlef, Duarte M. Alves, et al.*2025 · 34 citations*](https://md.research.elamur.ai/free/en/papers/boizard-2025-eurobert-scaling-multilingual-encoders-european/)
9. **[LLM Agents Making Agent Tools](https://md.research.elamur.ai/free/en/papers/wolflein-2025-llm-agents-making-agent-tools/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Georg Wölflein, Dyke Ferber, Daniel Truhn, et al.*2025 · 27 citations*
10. **[A Survey of Large Language Models for Arabic Language and its Dialects](https://md.research.elamur.ai/free/en/papers/mashaabi-2024-survey-large-language-models-arabic/) [ACM Transactions on Asian and Low-Resource Language Information Processing](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-asian-and-low-resource-language-information-processing/)**Malak Mashaabi, Shahad Al-Khalifa, Hend Al-Khalifa*2024 · 24 citations*
11. **[AICD Bench: A Challenging Benchmark for AI-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/orel-2026-aicd-bench-challenging-benchmark-ai/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Daniil Orel, Dilshod Azizov, Indraneil Paul, et al.*2026 · 23 citations*
12. [**NeoBERT: A Next-Generation BERT arXiv:2502.19587**Lola Le Breton, Quentin Fournier, Mariam El Mezouar, et al.*2025 · 20 citations*](https://md.research.elamur.ai/free/en/papers/breton-2025-neobert-next-generation-bert/)
13. **[Resolving Discrepancies in Compute-Optimal Scaling of Language Models](https://md.research.elamur.ai/free/en/papers/porian-2024-resolving-discrepancies-compute-optimal-scaling/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Tomer Porian, Mitchell Wortsman, Jenia Jitsev, et al.*2024 · 19 citations*
14. [**Language Matters: How Do Multilingual Input and Reasoning Paths Affect Large Reasoning Models? arXiv:2505.17407**Zhi Rui Tam, Cheng-Kuang Wu, Yu Ying Chiu, et al.*2025 · 17 citations*](https://md.research.elamur.ai/free/en/papers/tam-2025-language-matters-multilingual-input-reasoning/)
15. **[DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense Retrievers](https://md.research.elamur.ai/free/en/papers/ma-2025-drama-diverse-augmentation-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xueguang Ma, Xi Victoria Lin, Barlas Oguz, et al.*2025 · 13 citations*
16. [**MiniPLM: Knowledge Distillation for Pre-Training Language Models arXiv:2410.17215**Yuxian Gu, Hao Zhou, Fandong Meng, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/gu-2024-miniplm-knowledge-distillation-pre-training/)
17. **[Diffusion vs. Autoregressive Language Models: A Text Embedding Perspective](https://md.research.elamur.ai/free/en/papers/zhang-2025-diffusion-vs-autoregressive-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Siyue Zhang, Yilun Zhao, Liyuan Geng, et al.*2025 · 10 citations*
18. [**Stable Code Technical Report arXiv:2404.01226**Nikhil Pinnaparaju, Reshinth Adithyan, Duy Phung, et al.*2024 · 9 citations*](https://md.research.elamur.ai/free/en/papers/pinnaparaju-2024-stable-code-technical-report/)
19. **[New Encoders for German Trained from Scratch: Comparing ModernGBERT with Converted LLM2Vec Models](https://md.research.elamur.ai/free/en/papers/wunderle-2026-new-encoders-german-trained-scratch/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Julia Wunderle, Anton Ehrmanntraut, Jan Pfister, et al.*2026 · 7 citations*
20. [**Arabic Stable LM: Adapting Stable LM 2 1.6B to Arabic arXiv:2412.04277**Zaid Alyafeai, Michael Pieler, Hannah Teufel, et al.*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/alyafeai-2024-arabic-stable-lm-adapting-stable/)
21. **[Contrastive Learning with Narrative Twins for Modeling Story Salience](https://md.research.elamur.ai/free/en/papers/sterner-2026-contrastive-learning-narrative-twins-modeling/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Igor Sterner, Alex Lascarides, Frank Keller*2026 · 5 citations*
22. **[AfriMTEB and AfriE5: Benchmarking and Adapting Text Embedding Models for African Languages](https://md.research.elamur.ai/free/en/papers/uemura-2026-afrimteb-afrie5-benchmarking-adapting-text/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Kosei Uemura, Miaoran Zhang, David Ifeoluwa Adelani*2026 · 4 citations*
23. **[dLLM: Simple Diffusion Language Modeling](https://md.research.elamur.ai/free/en/papers/zhou-2026-dllm-simple-diffusion-language-modeling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhanhui Zhou, Lingjie Chen, Hanghang Tong, et al.*2026 · 3 citations*
24. **[Pretraining and Benchmarking Modern Encoders for Latvian](https://md.research.elamur.ai/free/en/papers/znotins-2026-pretraining-benchmarking-modern-encoders-latvian/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Arturs Znotins*2026 · 3 citations*
25. **[Testing Low-Resource Language Support in LLMs Using Language Proficiency Exams: the Case of Luxembourgish](https://md.research.elamur.ai/free/en/papers/lothritz-2025-testing-low-resource-language-support/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cedric Lothritz, Jordi Cabot, Laura Bernardy*2025 · 3 citations*
26. **[Adaptive Text Anonymization: Learning Privacy-Utility Trade-offs via Prompt Optimization](https://md.research.elamur.ai/free/en/papers/loiseau-2026-adaptive-text-anonymization-learning-privacy/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Gabriel Loiseau, Damien Sileo, Damien Riquet, et al.*2026 · 2 citations*
27. **[AraModernBERT: Transtokenized Initialization and Long-Context Encoder Modeling for Arabic](https://md.research.elamur.ai/free/en/papers/elshehy-2026-aramodernbert-transtokenized-initialization-long-context/) [Workshop on NLP for Languages Using Arabic Script](https://md.research.elamur.ai/free/en/venues/abjadnlp/)**Omar Elshehy, Omer Nacar, Abdelbasset Djamai, et al.*2026 · 2 citations*
28. **[CCD: Mitigating Hallucinations in Radiology MLLMs via Clinical Contrastive Decoding](https://md.research.elamur.ai/free/en/papers/zhang-2026-ccd-mitigating-hallucinations-radiology-mllms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xi Zhang, Zaiqiao Meng, Jake Lever, et al.*2026 · 2 citations*
29. **[COMMUNITYNOTES: A Dataset for Exploring the Helpfulness of Fact-Checking Explanations](https://md.research.elamur.ai/free/en/papers/xing-2026-communitynotes-dataset-exploring-helpfulness-fact/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Xing, Preslav Nakov, Timothy Baldwin, et al.*2026 · 2 citations*
30. [**The Word and the Way: Strategies for Domain-Specific BERT Pre-Training in German Medical NLP arXiv:2606.03250 · BMC Med Inform Decis Mak 26, 296 (2026)**Henry He, Johann Frei, Raphael Schmitt*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/he-2026-word-way-strategies-domain-specific/)
31. [**CARMA: Comprehensive Automatically-annotated Reddit Mental Health Dataset for Arabic arXiv:2511.03102**Saad Mankarious, Ayah Zirikly*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/mankarious-2025-carma-comprehensive-automatically-annotated-reddit/)
32. **[Using Curriculum Masking Based on Child Language Development to Train a Large Language Model with Limited Training Data](https://md.research.elamur.ai/free/en/papers/lucas-2024-curriculum-masking-based-child-language/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Evan Lucas, Dylan Gaines, Tagore Rao Kosireddy, et al.*2024 · 2 citations*
33. **[CPTCoder: A Reliable LLM System for Medical Procedure Code Prediction](https://md.research.elamur.ai/free/en/papers/wang-2026-cptcoder-reliable-llm-system-medical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Benlu Wang, Ziyao Shangguan, Kyle Tegtmeyer, et al.*2026 · 1 citation*
34. **[DAMASHA: Detecting AI in Mixed Adversarial Texts via Segmentation with Human-interpretable Attribution](https://md.research.elamur.ai/free/en/papers/teja-2026-damasha-detecting-ai-mixed-adversarial/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**L. D. M. S. Sai Teja, N. Siva Gopala Krishna, Ufaq Khan, et al.*2026 · 1 citation*
35. **[eGrantha.ai@CHiPSAL 2026: Stochastic Image Captioning for Robust Hate Speech Detection in Low-Resource Nepali Memes](https://md.research.elamur.ai/free/en/papers/thapaliya-2026-egrantha-ai-chipsal-2026-stochastic/) [workshop on Challenges in Processing South Asian Languages](https://md.research.elamur.ai/free/en/venues/chipsal/)**Anish Thapaliya*2026 · 1 citation*
36. **[Farhan Nafis Rayhan at SemEval-2026 Task 13: Supervised Contrastive Learning Approach with Gated Multiclass Decomposition Ensemble Architecture for Code Authorship Identification](https://md.research.elamur.ai/free/en/papers/rayhan-2026-farhan-nafis-rayhan-semeval-2026/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Farhan Rayhan, Fariska Ruskanda*2026 · 1 citation*
37. **[Improving Latvian Morphosyntactic Parsing with Pretrained Encoders and Analyzer-Constrained Decoding](https://md.research.elamur.ai/free/en/papers/znotins-2026-improving-latvian-morphosyntactic-parsing-pretrained/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Arturs Znotins*2026 · 1 citation*
38. **[Improving the OOD Performance of Closed-Source LLMs on NLI Through Strategic Data Selection](https://md.research.elamur.ai/free/en/papers/stacey-2026-improving-ood-performance-closed-source/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Joe Stacey, Lisa Alazraki, Aran Ubhi, et al.*2026 · 1 citation*
39. **[In Generative AI We (Dis)Trust? Computational Analysis of Trust and Distrust in Reddit Discussions](https://md.research.elamur.ai/free/en/papers/pessianzadeh-2026-generative-ai-we-dis-trust/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Aria Pessianzadeh, Naima Sultana, Hildegarde Van den Bulck, et al.*2026 · 1 citation*
40. **[Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions](https://md.research.elamur.ai/free/en/papers/scivetti-2026-language-models-learn-constructional-semantics/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Wesley Scivetti, Ethan Gotlieb Wilcox, Nathan Schneider, et al.*2026 · 1 citation*
41. **[Modeling Annotator Disagreement with Demographic-Aware Experts and Synthetic Perspectives](https://md.research.elamur.ai/free/en/papers/xu-2026-modeling-annotator-disagreement-demographic-aware/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yinuo Xu, Veronica Derricks, Allison Earl, et al.*2026 · 1 citation*
42. **[NeoAraBERT: A Modern Foundation Model for Arabic Embeddings with Diacritics-Aware Tokenization and POS-Targeted Masking](https://md.research.elamur.ai/free/en/papers/chakra-2026-neoarabert-modern-foundation-model-arabic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chadi Abou Chakra, Hadi Khaled Hamoud, Osama Rakan Al Mraikhat, et al.*2026 · 1 citation*
43. **[Rhetorical Questions in LLM Representations: A Linear Probing Study](https://md.research.elamur.ai/free/en/papers/yao-2026-rhetorical-questions-llm-representations-linear/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Louie Hong Yao, Vishesh Anand, Yuan Zhuang, et al.*2026 · 1 citation*
44. **[SMARTER: A Data-efficient Framework to Improve Toxicity Detection with Explanation via Self-augmenting Large Language Models](https://md.research.elamur.ai/free/en/papers/nghiem-2026-smarter-data-efficient-framework-improve/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huy Nghiem, Advik Sachdeva, Hal Daumé Iii*2026 · 1 citation*
45. **[Team Macaroni at SemEval-2026 Task 10: PsyCoMark: Psycholinguistic Conspiracy Marker Extraction and Detection](https://md.research.elamur.ai/free/en/papers/rabehi-2026-team-macaroni-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Rofaida Rabehi, Nicolai Plenk, Miriam Han*2026 · 1 citation*
46. **[TransformerTrio at SemEval-2026 Task 13: Navigating Domain Shift and Representation Instability in Machine-Generated Code Detection](https://md.research.elamur.ai/free/en/papers/patel-2026-transformertrio-semeval-2026-task-13/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Avi Patel, Manthan Laddha, Pushti Sapovadiya, et al.*2026 · 1 citation*
47. **[UMUTeam at SemEval-2026 Task 10: Transformer Ensembles for Conspiratorial Span Extraction and Detection](https://md.research.elamur.ai/free/en/papers/navalon-2026-umuteam-semeval-2026-task-10/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Jorge Gómez-Navalón, Ronghao Pan, Tomás Bernal-Beltrán, et al.*2026 · 1 citation*
48. **[Enhancing the Automatic Classification of Metadiscourse in Low-Proficiency Learners' Spoken and Written English Texts Using XLNet](https://md.research.elamur.ai/free/en/papers/guan-2025-enhancing-automatic-classification-metadiscourse-low/) [Workshop on Computational Approaches to Discourse (CODI)](https://md.research.elamur.ai/free/en/venues/codi/)**Wenwen Guan, Marijn Alta, Jelke Bloem*2025 · 1 citation*
49. **[A Dialogue System for Second Language Learning with Dynamic Adaptation to In-Dialogue Difficulty Changes](https://md.research.elamur.ai/free/en/papers/morioka-2026-dialogue-system-second-language-learning/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Taku Morioka, Junya Takayama, Tomoyuki Kajiwara*2026*
50. **[A Multi-Agent Framework for High-Interaction Terminal Simulation](https://md.research.elamur.ai/free/en/papers/wei-2026-multi-agent-framework-high-interaction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kai Wei, Yuwen Cui, Kehan Shen, et al.*2026*
51. **[AI4PC-Howard University at SemEval-2026 Task 2: Fine-Tuning DistilBERT, DeBERTa and ModernBERT for Valence–Arousal Prediction and Change Estimation](https://md.research.elamur.ai/free/en/papers/shah-2026-ai4pc-howard-university-semeval-2026/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Araj Shah, Utsav Shah, Saurav Aryal*2026*
52. **[Automatic Annotation of Mental Health Recovery Narratives: A Benchmark Study](https://md.research.elamur.ai/free/en/papers/pandey-2026-automatic-annotation-mental-health-recovery/) [Workshop on Computational Linguistics and Clinical Psychology](https://md.research.elamur.ai/free/en/venues/clpsych/)**Shrankhla Pandey, Graham Murray, Ben Laws, et al.*2026*
53. **[Biomed-Enriched: Data-Efficient Biomedical Pretraining via Paragraph-Level Annotation](https://md.research.elamur.ai/free/en/papers/touchent-2026-biomed-enriched-data-efficient-biomedical/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rian Touchent, Nathan Godey, Éric Villemonte de la Clergerie*2026*
54. [**Controlling Implicit Shortcut Reliance in L2 Spoken English Auto-markers arXiv:2607.16085**Shilin Gao, Mark J. F. Gales, Kate M. Knill*2026*](https://md.research.elamur.ai/free/en/papers/gao-2026-controlling-implicit-shortcut-reliance-l2/)
55. **[DeepPavlov Strikes Back: A Toolkit for Improving LLM Reliability and Trustworthiness](https://md.research.elamur.ai/free/en/papers/nikolaev-2026-deeppavlov-strikes-back-toolkit-improving/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Evgenii Nikolaev, Timur Ionov, Anna Korzanova, et al.*2026*
56. **[HOTATE: A Japanese Dialogue Corpus Annotated with Responses of Private Thoughts and Public Statements](https://md.research.elamur.ai/free/en/papers/toda-2026-hotate-japanese-dialogue-corpus-annotated/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Yuko Toda, Daisuke Maekawa, Kota Manabe, et al.*2026*
57. **[HU at SemEval-2026 Task 6: A Hybrid Discriminative Modeling of Political Clarity and Evasion](https://md.research.elamur.ai/free/en/papers/munawar-2026-hu-semeval-2026-task-6/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Taha Munawar, Basil Khan, Arsal Jangda, et al.*2026*
58. **[HybridCodeAuthorship: A Benchmark Dataset for Line-Level Code Authorship Detection](https://md.research.elamur.ai/free/en/papers/patterson-2026-hybridcodeauthorship-benchmark-dataset-line-level/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Luke S. Patterson, Li Wang, Adam Faulkner*2026*
59. **[IDEAlign: Comparing Ideas of Large Language Models to Domain Experts](https://md.research.elamur.ai/free/en/papers/nam-2026-idealign-comparing-ideas-large-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**HyunJi Nam, Lucía Langlois, Jim Malamut, et al.*2026*
60. **[JabuticaBERT: Modern Portuguese Encoders from Scratch with RTD and Long-Context Training](https://md.research.elamur.ai/free/en/papers/porto-2026-jabuticabert-modern-portuguese-encoders-scratch/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Thiago Porto, Gabriel Gomes, Alexandre Bender, et al.*2026*
61. **[JFC-Recipe: A Dataset for Nutrient Estimation from Japanese User-Generated Cooking Recipes](https://md.research.elamur.ai/free/en/papers/shirai-2026-jfc-recipe-dataset-nutrient-estimation/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Keisuke Shirai, Yoko Yamakata, Hirotaka Kameko, et al.*2026*
62. [**KliniskVestBERT: BERT Model Specialised to Norwegian Clinical Texts arXiv:2606.01904**Christian Autenried, Cosimo Persia*2026*](https://md.research.elamur.ai/free/en/papers/autenried-2026-kliniskvestbert-bert-model-specialised-norwegian/)
63. **[Linguistic Initialization for Inductive Reasoning in Heterogeneous Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/pasquini-2026-linguistic-initialization-inductive-reasoning-heterogeneous/) [Knowledge Graphs and Large Language Models Workshop (KG-LLM) @ LREC26](https://md.research.elamur.ai/free/en/venues/kallm/)**Daniele Pasquini, Danilo Croce, Roberto Basili*2026*
64. **[ltzGLUE: Luxembourgish General Language Understanding Evaluation](https://md.research.elamur.ai/free/en/papers/plum-2026-ltzglue-luxembourgish-general-language-understanding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alistair Plum, Felicia Körner, Anne-Marie Lutgen, et al.*2026*
65. **[Measuring Idiomaticity in Text Embedding Models with epsilon-compositionality](https://md.research.elamur.ai/free/en/papers/wold-2026-measuring-idiomaticity-text-embedding-models/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sondre Wold, Étienne Simon, Erik Velldal, et al.*2026*
66. **[Mind Your Special Tokens! On the Importance of Dedicated Sequence-End Tokens in Vision-Language Embedding Models](https://md.research.elamur.ai/free/en/papers/musacchio-2026-mind-your-special-tokens-importance/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Elio Musacchio, Giovanni Semeraro, Goran Glavaš*2026*
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81. [**NeoDictaBERT: Pushing the Frontier of BERT models for Hebrew**Shaltiel Shmidman, Avi Shmidman, Moshe Koppel*2025*](https://md.research.elamur.ai/free/en/papers/shmidman-2025-neodictabert-pushing-frontier-bert-models/)

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