---
title: "Who cites Hany Hassan Awadalla"
description: "1,471 papers of the Elamur Research library cite the works of Hany Hassan Awadalla, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/hany-hassan-awadalla/cited-by/"
---
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# Who cites Hany Hassan Awadalla

1,507 citations of their works from 1,471 papers of our library (of the 140,884 whose bibliographies we read) · 94 with a page here, the most cited first · [← Hany Hassan Awadalla](https://md.research.elamur.ai/free/en/authors/hany-hassan-awadalla/)

1. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,847 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/)
2. [**LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models**Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.*2024 · 1,035 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2024-llamafactory-unified-efficient-fine-tuning/)
3. [**MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark**Yubo Wang, Xueguang Ma, Ge Zhang, et al.*2024 · 731 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-mmlu-pro-more-robust-challenging/)
4. [**Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate**Tian Liang, Zhiwei He, Wenxiang Jiao, et al.*2023 · 643 citations*](https://md.research.elamur.ai/free/en/papers/liang-2023-encouraging-divergent-thinking-large-language/)
5. [**Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis**Wenhao Zhu, Hongyi Liu, Qingxiu Dong, et al.*2024 · 503 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2024-multilingual-machine-translation-large-language/)
6. [**Phi-4 Technical Report**Marah Abdin, Jyoti Aneja, Harkirat Behl, et al.*2024 · 489 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-4-technical-report/)
7. [**ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.*2023 · 418 citations*](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/)
8. [**The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale**Guilherme Penedo, Hynek Kydlíček, Loubna Ben allal, et al.*2024 · 404 citations*](https://md.research.elamur.ai/free/en/papers/penedo-2024-fineweb-datasets-decanting-web-finest/)
9. [**RULER: What's the Real Context Size of Your Long-Context Language Models?**Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.*2024 · 386 citations*](https://md.research.elamur.ai/free/en/papers/hsieh-2024-ruler-s-real-context-size/)
10. [**A Survey on Large Language Models for Code Generation**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 366 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/)
11. [**Document-Level Machine Translation with Large Language Models**Longyue Wang, Chenyang Lyu, Tianbo Ji, et al.*2023 · 295 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-document-level-machine-translation-large/)
12. [**MEGA: Multilingual Evaluation of Generative AI**Kabir Ahuja, Harshita Diddee, Rishav Hada, et al.*2023 · 281 citations*](https://md.research.elamur.ai/free/en/papers/ahuja-2023-mega-multilingual-evaluation-generative-ai/)
13. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 276 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/)
14. [**MiniCPM-V: A GPT-4V Level MLLM on Your Phone**Yuan Yao, Tianyu Yu, Ao Zhang, et al.*2024 · 267 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-minicpm-v-gpt-4v/)
15. [**GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models**Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.*2024 · 262 citations*](https://md.research.elamur.ai/free/en/papers/mirzadeh-2024-gsm-symbolic-understanding-limitations-mathematical/)
16. [**Large Language Models for Data Annotation and Synthesis: A Survey**Zhen Tan, Dawei Li, Song Wang, et al.*2024 · 259 citations*](https://md.research.elamur.ai/free/en/papers/tan-2024-large-language-models-data-annotation/)
17. [**QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs**Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, et al.*2024 · 252 citations*](https://md.research.elamur.ai/free/en/papers/ashkboos-2024-quarot-outlier-free-4-bit/)
18. [**Hallucinations in Large Multilingual Translation Models**Nuno M. Guerreiro, Duarte M. Alves, Jonas Waldendorf, et al.*2023 · 244 citations*](https://md.research.elamur.ai/free/en/papers/guerreiro-2023-hallucinations-large-multilingual-translation-models/)
19. [**Tower: An Open Multilingual Large Language Model for Translation-Related Tasks**Duarte M. Alves, Jose Pombal, Nuno M. Guerreiro, et al.*2024 · 226 citations*](https://md.research.elamur.ai/free/en/papers/alves-2024-tower-open-multilingual-large-language/)
20. [**Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting**Haoyang Huang, Tianyi Tang, Dongdong Zhang, et al.*2023 · 223 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-all-languages-created-equal-llms/)
21. [**Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation**Haoran Xu, Amr Sharaf, Yunmo Chen, et al.*2024 · 207 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-contrastive-preference-optimization-pushing-boundaries/)
22. [**Exploring Human-Like Translation Strategy with Large Language Models**Zhiwei He, Tian Liang, Wenxiang Jiao, et al.*2024 · 207 citations*](https://md.research.elamur.ai/free/en/papers/he-2024-exploring-human-like-translation-strategy/)
23. [**A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 198 citations*](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/)
24. [**MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention**Huiqiang Jiang, Yucheng Li, Chengruidong Zhang, et al.*2024 · 197 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2024-minference-1-0-accelerating-pre/)
25. [**From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline**Tianle Li, Wei-Lin Chiang, Evan Frick, et al.*2024 · 191 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-crowdsourced-data-high-quality-benchmarks/)
26. [**Towards Making the Most of ChatGPT for Machine Translation**Keqin Peng, Liang Ding, Qihuang Zhong, et al.*2023 · 190 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-making-most-chatgpt-machine-translation/)
27. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 187 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/)
28. [**Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models**Matt Deitke, Christopher Clark, Sangho Lee, et al.*2024 · 184 citations*](https://md.research.elamur.ai/free/en/papers/deitke-2024-molmo-pixmo-open-weights-open/)
29. [**Findings of the WMT24 General Machine Translation Shared Task: The LLM Era Is Here but MT Is Not Solved Yet**Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, et al.*2024 · 177 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2024-findings-wmt24-general-machine-translation/)
30. [**Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 174 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/)
31. [**SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language Model**Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.*2025 · 171 citations*](https://md.research.elamur.ai/free/en/papers/allal-2025-smollm2-smol-goes-big-data/)
32. [**Low-Resource Languages Jailbreak GPT-4**Zheng-Xin Yong, Cristina Menghini, Stephen H. Bach*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/yong-2023-low-resource-languages-jailbreak-gpt/)
33. [**Scaling Synthetic Data Creation with 1,000,000,000 Personas**Tao Ge, Xin Chan, Xiaoyang Wang, et al.*2024 · 160 citations*](https://md.research.elamur.ai/free/en/papers/ge-2024-scaling-synthetic-data-creation-1/)
34. [**When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMs**Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/kamoi-2024-when-can-llms-actually-correct/)
35. [**DataComp-LM: In search of the next generation of training sets for language models**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 156 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/)
36. [**Large Language Models Effectively Leverage Document-level Context for Literary Translation, but Critical Errors Persist**Marzena Karpinska, Mohit Iyyer*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/karpinska-2023-large-language-models-effectively-leverage/)
37. [**ChatGPT MT: Competitive for High- (but Not Low-) Resource Languages**Nathaniel Robinson, Perez Ogayo, David R. Mortensen, et al.*2023 · 151 citations*](https://md.research.elamur.ai/free/en/papers/robinson-2023-chatgpt-mt-competitive-high-but/)
38. [**rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking**Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.*2025 · 146 citations*](https://md.research.elamur.ai/free/en/papers/guan-2025-rstar-math-small-llms-can/)
39. [**Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs**Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.*2025 · 145 citations*](https://md.research.elamur.ai/free/en/papers/microsoft-2025-phi-4-mini-technical-report/)
40. [**Magpie: Alignment Data Synthesis from Scratch by Prompting Aligned LLMs with Nothing**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 144 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-magpie-alignment-data-synthesis-scratch/)
41. [**DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding**Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-deepseek-vl2-mixture-experts/)
42. [**Error Analysis Prompting Enables Human-Like Translation Evaluation in Large Language Models**Qingyu Lu, Baopu Qiu, Liang Ding, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-error-analysis-prompting-enables-human/)
43. [**To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning**Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.*2024 · 133 citations*](https://md.research.elamur.ai/free/en/papers/sprague-2024-cot-cot-chain-thought-helps/)
44. [**Cross-lingual Prompting: Improving Zero-shot Chain-of-Thought Reasoning across Languages**Libo Qin, Qiguang Chen, Fuxuan Wei, et al.*2023 · 122 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-cross-lingual-prompting-improving-zero/)
45. [**OpenThoughts: Data Recipes for Reasoning Models**Etash Guha, Ryan Marten, Sedrick Keh, et al.*2025 · 113 citations*](https://md.research.elamur.ai/free/en/papers/guha-2025-openthoughts-data-recipes-reasoning-models/)
46. [**Benchmarking Machine Translation with Cultural Awareness**Binwei Yao, Ming Jiang, Tara Bobinac, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-benchmarking-machine-translation-cultural-awareness/)
47. [**Iterative Translation Refinement with Large Language Models**Pinzhen Chen, Zhicheng Guo, Barry Haddow, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-iterative-translation-refinement-large-language/)
48. [**TARJAMAT: Evaluation of Bard and ChatGPT on Machine Translation of Ten Arabic Varieties**Karima Kadaoui, Samar M. Magdy, Abdul Waheed, et al.*2023 · 60 citations*](https://md.research.elamur.ai/free/en/papers/kadaoui-2023-tarjamat-evaluation-bard-chatgpt-machine/)
49. [**Counting the Bugs in ChatGPT's Wugs: A Multilingual Investigation into the Morphological Capabilities of a Large Language Model**Leonie Weissweiler, Valentin Hofmann, Anjali Kantharuban*2023 · 47 citations*](https://md.research.elamur.ai/free/en/papers/weissweiler-2023-chatgpt-wugs-morphology/)
50. [**Towards Effective Disambiguation for Machine Translation with Large Language Models**Vivek Iyer, Pinzhen Chen, Alexandra Birch*2023 · 38 citations*](https://md.research.elamur.ai/free/en/papers/iyer-2023-effective-disambiguation-machine-translation-large/)
51. [**Taqyim: Evaluating Arabic NLP Tasks Using ChatGPT Models**Zaid Alyafeai, Maged S. Alshaibani, Badr AlKhamissi, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/alyafeai-2023-taqyim-evaluating-arabic-nlp-tasks/)
52. [**Distillation Scaling Laws**Dan Busbridge, Amitis Shidani, Floris Weers, et al.*2025 · 23 citations*](https://md.research.elamur.ai/free/en/papers/busbridge-2025-distillation-scaling-laws/)
53. [**MQM-APE: Toward High-Quality Error Annotation Predictors with Automatic Post-Editing in LLM Translation Evaluators**Qingyu Lu, Liang Ding, Kanjian Zhang, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/lu-2025-mqm-ape-high-quality-error/)
54. [**LLM-Assisted Rule Based Machine Translation for Low/No-Resource Languages**Jared Coleman, Bhaskar Krishnamachari, Ruben Rosales, et al.*2024 · 20 citations*](https://md.research.elamur.ai/free/en/papers/coleman-2024-llm-assisted-rule-based-machine/)
55. [**Benchmarking LLMs for Translating Classical Chinese Poetry: Evaluating Adequacy, Fluency, and Elegance**Andong Chen, Lianzhang Lou, Kehai Chen, et al.*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-benchmarking-llms-translating-classical-chinese/)
56. [**DiBiMT: A Gold Evaluation Benchmark for Studying Lexical Ambiguity in Machine Translation**Federico Martelli, Stefano Perrella, Niccolò Campolungo, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/martelli-2025-dibimt-gold-evaluation-benchmark-studying/)
57. [**GrammaMT: Improving Machine Translation with Grammar-Informed In-Context Learning**Rita Ramos, Everlyn Asiko Chimoto, Maartje Ter Hoeve, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2025-grammamt-improving-machine-translation-grammar/)
58. [**ThatiAR: Subjectivity Detection in Arabic News Sentences**Reem Suwaileh, Maram Hasanain, Fatema Hubail, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/suwaileh-2024-thatiar-subjectivity-detection-arabic-news/)
59. [**OASIS: A Multilingual and Multimodal Dataset for Culturally Grounded Spoken Visual QA**Firoj Alam, Ali Ezzat Shahroor, Md. Arid Hasan, et al.*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/alam-2025-oasis-multilingual-multimodal-dataset-culturally/)
60. [**ivrit.ai: A Comprehensive Dataset of Hebrew Speech for AI Research and Development**Yanir Marmor, Kinneret Misgav, Yair Lifshitz*2023 · 6 citations*](https://md.research.elamur.ai/free/en/papers/marmor-2023-ivrit-ai-comprehensive-dataset-hebrew/)
61. [**Kuwain 1.5B: An Arabic SLM via Language Injection**Khalil Hennara, Sara Chrouf, Mohamed Motaism Hamed, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/hennara-2025-kuwain-1-5b-arabic-slm/)
62. [**Gender Disambiguation in Machine Translation: Diagnostic Evaluation in Decoder-Only Architectures**Chiara Manna, Hosein Mohebbi, Afra Alishahi, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/manna-2026-gender-disambiguation-machine-translation-diagnostic/)
63. [**Can ChatGPT capture swearing nuances? Evidence from translating Arabic oaths**Mohammed Q. Shormani*2024 · 3 citations*](https://md.research.elamur.ai/free/en/papers/shormani-2024-chatgpt-capture-swearing-nuances-evidence/)
64. [**Domain Adaptation for Arabic Machine Translation: The Case of Financial Texts**Emad A. Alghamdi, Jezia Zakraoui, Fares A. Abanmy*2023 · 3 citations*](https://md.research.elamur.ai/free/en/papers/alghamdi-2023-domain-adaptation-arabic-machine-translation/)
65. [**Culture-Aware Machine Translation in Large Language Models: Benchmarking and Investigation**Zekun Yuan, Yangfan Ye, Xiaocheng Feng, et al.*2026 · 2 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2026-culture-aware-machine-translation-large/)
66. [**Language and Planning in Robotic Navigation: A Multilingual Evaluation of State-of-the-Art Models**Malak Mansour, Ahmed Aly, Bahey Tharwat, et al.*2025 · 2 citations*](https://md.research.elamur.ai/free/en/papers/mansour-2025-language-planning-robotic-navigation-multilingual/)
67. [**AHA-Memes: A Fine-Grained Multimodal Benchmark for Understanding Hate in Arabic Memes**Mohamed Bayan Kmainasi, Ali Ezzat Shahroor, Abul Hasnat, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/kmainasi-2026-aha-memes-fine-grained-multimodal/)
68. [**BSC's Submission to the Instruction Following Track of IWSLT 2026**Oriol Pareras, Joan Llado, Pol Buitrago, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/pareras-2026-bsc-s-submission-instruction-following/)
69. [**Context Volume Drives Performance: Tackling Domain Shift in Extremely Low-Resource Translation via RAG**David Samuel Setiawan, Raphaël Merx, Jey Han Lau*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/setiawan-2026-context-volume-drives-performance-tackling/)
70. [**FBK's Long-form SpeechLLMs for IWSLT 2026 Instruction Following**Zhihang Xie, Marco Gaido, Sara Papi, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/xie-2026-fbk-s-long-form-speechllms/)
71. [**Improving Dialect Robustness in Large Language Models via LoRA and Mixture-of-Experts**Sanjh Maheshwari, Aniket Singh Rajpoot, Oana Cocarascu, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/maheshwari-2026-improving-dialect-robustness-large-language/)
72. [**MUSCAT: MUltilingual, SCientific ConversATion Benchmark**Supriti Sinhamahapatra, Thai-Binh Nguyen, Yiğit Oğuz, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/sinhamahapatra-2026-muscat-multilingual-scientific-conversation-benchmark/)
73. [**Synthetic Function Demonstrations Improve Generation in Low-Resource Programming Languages**Nick McKenna, Xinnuo Xu, Jack Williams, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/mckenna-2026-synthetic-function-demonstrations-improve-generation/)
74. [**A Single Model Ensemble Framework for Neural Machine Translation Using Pivot Translation**Seokjin Oh, Keonwoong Noh, Woohwan Jung*2026*](https://md.research.elamur.ai/free/en/papers/oh-2026-single-model-ensemble-framework-neural/)
75. [**ArabicNumBench: Evaluating Arabic Number Reading in Large Language Models**Anas Alhumud, Abdulaziz Alhammadi, Muhammad Badruddin Khan*2026*](https://md.research.elamur.ai/free/en/papers/alhumud-2026-arabicnumbench-evaluating-arabic-number-reading/)
76. [**Consistency of LLMs to Comparative Statements in Mathematical Reasoning Tasks**Aidan W. San, Daniel Juyoung Son, Xiaodong Liu, et al.*2026*](https://md.research.elamur.ai/free/en/papers/san-2026-consistency-llms-comparative-statements-mathematical/)
77. [**Context-8: A Data Set for Evaluating Context Sensitivity in Machine Translation**Dongyue Wang, Kyo Kageura*2026*](https://md.research.elamur.ai/free/en/papers/wang-2026-context-8-data-set-evaluating/)
78. [**Evaluating Discriminability of Vision-Language Models**Masayasu Muraoka, Naoaki Okazaki*2026*](https://md.research.elamur.ai/free/en/papers/muraoka-2026-evaluating-discriminability-vision-language-models/)
79. [**Finding Sense in Nonsense with Generated Contexts: Perspectives from Humans and Language Models**Katrina Olsen, Sebastian Padó*2026*](https://md.research.elamur.ai/free/en/papers/olsen-2026-finding-sense-nonsense-generated-contexts/)
80. [**From Bones to Rocks: A Systematic Evaluation of Specialized Definition Generation for Portuguese**Rafael Oleques Nunes, Dennis Giovani Balreira, Joel Luís Carbonera*2026*](https://md.research.elamur.ai/free/en/papers/nunes-2026-bones-rocks-systematic-evaluation-specialized/)
81. [**GhostWriter: Hidden AI-Generated Texts over Multiple Languages, Domains and Generators**Manuel Schaaf, Kevin Bönisch, Alexander Mehler*2026*](https://md.research.elamur.ai/free/en/papers/schaaf-2026-ghostwriter-hidden-ai-generated-texts/)
82. [**Interlinear Glosses as a Multilingual Pivot for Machine Translation: An Updated Study on Turkish with Restricted Resources**Volkan Ozer, Shu Okabe, Alexander Fraser*2026*](https://md.research.elamur.ai/free/en/papers/ozer-2026-interlinear-glosses-as-multilingual-pivot/)
83. [**Lexical and Syntactic Diversity: Still Lost in Machine Translation?**Lise Volkart, Pierrette Bouillon*2026*](https://md.research.elamur.ai/free/en/papers/volkart-2026-lexical-syntactic-diversity-still-lost/)
84. [**MASA: A Novel Multimodal Foundation Model for L2 Speaking Assessment in Picture-description Scenarios**Bi-Cheng Yan, Fu-An Chao, Hong-Yun H.Y. Lin, et al.*2026*](https://md.research.elamur.ai/free/en/papers/yan-2026-masa-novel-multimodal-foundation-model/)
85. [**On the Use of LLMs for Specialised Terminology: A Good Alternative to Corpora?**Joachim Minder, Guillaume Wisniewski, Natalie Kübler*2026*](https://md.research.elamur.ai/free/en/papers/minder-2026-use-llms-specialised-terminology-good/)
86. [**Quantifying Metric and Model Agreement in Bias Evaluation of Large Language Models**Arash Asgari, Huan Wu, Amirreza Naziri, et al.*2026*](https://md.research.elamur.ai/free/en/papers/asgari-2026-quantifying-metric-model-agreement-bias/)
87. [**Reasoning Graph-Structured Question Answering: Datasets and Insights from LLM Benchmarking**Khin Yone, Devasha Trivedi, Anish Pahilajani, et al.*2026*](https://md.research.elamur.ai/free/en/papers/yone-2026-reasoning-graph-structured-question-answering/)
88. [**Smarter edits? Post-editing with error highlights and translation suggestions**Fleur V.J. van Tellingen, Gautam Ranka, Dora Žugčić, et al.*2026*](https://md.research.elamur.ai/free/en/papers/tellingen-2026-smarter-edits-post-editing-error/)
89. [**STRUDEL: Unrolling a Benchmark for Evaluating Vision-Language Models on Structured Diagram Understanding across Domains**Daniel Steinigen, Lucie Flek, Sebastian Houben*2026*](https://md.research.elamur.ai/free/en/papers/steinigen-2026-strudel-unrolling-benchmark-evaluating-vision/)
90. [**The MaTOS Pipeline for the Translation of Scientific Abstracts on the HAL Platform**Panagiotis Tsolakis, Ziqian Peng, Laurent Romary, et al.*2026*](https://md.research.elamur.ai/free/en/papers/tsolakis-2026-matos-pipeline-translation-scientific-abstracts/)
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