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title: "Language models & pretraining — papers, page 9"
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# 🧠 Language models & pretraining

1,079 papers · page 9 of 12 · 726–825 · the most cited first · [all topics](https://md.research.elamur.ai/free/en/topics/)

Models that learn a language from raw text, and how they are pretrained, tuned and prompted.

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726. [**Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data**Mubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta, et al.*2023 · 38 citations*](https://md.research.elamur.ai/free/en/papers/akhtar-2023-exploring-numerical-reasoning-capabilities-language/)
727. [**DziriBERT: a Pre-trained Language Model for the Algerian Dialect**Amine Abdaoui, Mohamed Berrimi, Mourad Oussalah, et al.*2021 · 38 citations*](https://md.research.elamur.ai/free/en/papers/abdaoui-2021-dziribert-pre-trained-language-model/)
728. [**OG-RAG: Ontology-grounded retrieval-augmented generation for large language models**Kartik Sharma, Peeyush Kumar, Yunqing Li*2025 · 37 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2025-og-rag-ontology-grounded-retrieval/)
729. [**Towards Cross-Tokenizer Distillation: the Universal Logit Distillation Loss for LLMs**Nicolas Boizard, Kevin El Haddad, Celine Hudelot, et al.*2024 · 34 citations*](https://md.research.elamur.ai/free/en/papers/boizard-2024-towards-cross-tokenizer-distillation-universal/)
730. [**Language acquisition: do children and language models follow similar learning stages?**Linnea Evanson, Yair Lakretz, Jean-Rémi King*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/evanson-2023-language-acquisition-children-language-models/)
731. [**RST Discourse Parsing with Second-Stage EDU-Level Pre-training**Nan Yu, Meishan Zhang, Guohong Fu, et al.*2022 · 32 citations*](https://md.research.elamur.ai/free/en/papers/yu-2022-rst-discourse-parsing-second-stage/)
732. [**Probing Contextual Language Models for Common Ground with Visual Representations**Gabriel Ilharco, Rowan Zellers, Ali Farhadi, et al.*2021 · 31 citations*](https://md.research.elamur.ai/free/en/papers/ilharco-2021-probing-contextual-language-models-common/)
733. [**Filling the Gaps in Ancient Akkadian Texts: A Masked Language Modelling Approach**Koren Lazar, Benny Saret, Asaf Yehudai, et al.*2021 · 30 citations*](https://md.research.elamur.ai/free/en/papers/lazar-2021-filling-gaps-ancient-akkadian-texts/)
734. [**Assessing Discourse Relations in Language Generation from GPT-2**Wei-Jen Ko, Junyi Jessy Li*2020 · 30 citations*](https://md.research.elamur.ai/free/en/papers/ko-2020-assessing-discourse-relations-language-generation/)
735. [**BIDER: Bridging Knowledge Inconsistency for Efficient Retrieval-Augmented LLMs via Key Supporting Evidence**Jiajie Jin, Yutao Zhu, Yujia Zhou, et al.*2024 · 28 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-bider-bridging-knowledge-inconsistency-efficient/)
736. [**Observational Scaling Laws and the Predictability of Language Model Performance**Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto*2024 · 28 citations*](https://md.research.elamur.ai/free/en/papers/ruan-2024-observational-scaling-laws-predictability-language/)
737. [**Exploring the Relationship between LLM Hallucinations and Prompt Linguistic Nuances: Readability, Formality, and Concreteness**Vipula Rawte, Prachi Priya, S.M Towhidul Islam Tonmoy, et al.*2023 · 27 citations*](https://md.research.elamur.ai/free/en/papers/rawte-2023-exploring-relationship-between-llm-hallucinations/)
738. [**Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling**Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.*2024 · 26 citations*](https://md.research.elamur.ai/free/en/papers/bansal-2024-smaller-weaker-yet-better-training/)
739. [**Can Multilingual Language Models Transfer to an Unseen Dialect? A Case Study on North African Arabizi**Benjamin Muller, Benoit Sagot, Djame Seddah*2020 · 26 citations*](https://md.research.elamur.ai/free/en/papers/muller-2020-multilingual-language-models-transfer-unseen/)
740. [**How Is LLM Reasoning Distracted by Irrelevant Context? An Analysis Using a Controlled Benchmark**Minglai Yang, Ethan Huang, Liang Zhang, et al.*2025 · 24 citations*](https://md.research.elamur.ai/free/en/papers/yang-2025-llm-reasoning-distracted-irrelevant-context/)
741. [**A closer look at the performance of neural language models on reflexive anaphor licensing**Jennifer Hu, Sherry Yong Chen, Roger Levy*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/hu-2020-closer-look-performance-neural-language/)
742. [**MacBERTh: Development and Evaluation of a Historically Pre-trained Language Model for English (1450-1950)**Enrique Manjavacas Arevalo, Lauren Fonteyn*2021 · 23 citations*](https://md.research.elamur.ai/free/en/papers/arevalo-2021-macberth-development-evaluation-historically-pre/)
743. [**Unleashing the Power of Neural Discourse Parsers - A Context and Structure Aware Approach Using Large Scale Pretraining**Grigorii Guz, Patrick Huber, Giuseppe Carenini*2020 · 19 citations*](https://md.research.elamur.ai/free/en/papers/guz-2020-unleashing-power-neural-discourse-parsers/)
744. [**Do Large Language Models Understand Word Senses?**Domenico Meconi, Simone Stirpe, Federico Martelli*2025 · 18 citations*](https://md.research.elamur.ai/free/en/papers/meconi-2025-llms-word-senses/)
745. [**CamelEval: Advancing Culturally Aligned Arabic Language Models and Benchmarks**Zhaozhi Qian, Faroq Altam, Muhammad Alqurishi, et al.*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/qian-2024-cameleval-advancing-culturally-aligned-arabic/)
746. [**Construction Grammar Provides Unique Insight into Neural Language Models**Leonie Weissweiler, Taiqi He, Naoki Otani, et al.*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/weissweiler-2023-construction-grammar-provides-unique-insight/)
747. [**Evaluating statistical language models as pragmatic reasoners**Benjamin Lipkin, Lionel Wong, Gabriel Grand, et al.*2023 · 18 citations*](https://md.research.elamur.ai/free/en/papers/lipkin-2023-evaluating-statistical-language-models-pragmatic/)
748. [**ArabianGPT: Native Arabic GPT-based Large Language Model**Anis Koubaa, Adel Ammar, Lahouari Ghouti, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/koubaa-2024-arabiangpt-native-arabic-gpt-based/)
749. [**MultiPragEval: Multilingual Pragmatic Evaluation of Large Language Models**Dojun Park, Jiwoo Lee, Seohyun Park, et al.*2024 · 17 citations*](https://md.research.elamur.ai/free/en/papers/park-2024-multiprageval-multilingual-pragmatic-evaluation-large/)
750. [**Discursive Socratic Questioning: Evaluating the Faithfulness of Language Models' Understanding of Discourse Relations**Yisong Miao, Hongfu Liu, Wenqiang Lei, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/miao-2024-discursive-socratic-questioning-evaluating-faithfulness/)
751. [**Is Child-Directed Speech Effective Training Data for Language Models?**Steven Y. Feng, Noah D. Goodman, Michael C. Frank*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/feng-2024-is-child-directed-speech-effective/)
752. [**Rethinking Pragmatics in Large Language Models: Towards Open-Ended Evaluation and Preference Tuning**Shengguang Wu, Shusheng Yang, Zhenglun Chen, et al.*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-rethinking-pragmatics-large-language-models/)
753. [**A Large and Diverse Arabic Corpus for Language Modeling**Abbas Raza Ali, Muhammad Ajmal Siddiqui, Rema Algunaibet, et al.*2022 · 16 citations*](https://md.research.elamur.ai/free/en/papers/ali-2022-large-diverse-arabic-corpus-language/)
754. [**Ontology-Guided Reverse Thinking Makes Large Language Models Stronger on Knowledge Graph Question Answering**Runxuan Liu, Bei Luo, Jiaqi Li, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-ontology-guided-reverse-thinking-makes/)
755. [**Adapting LLMs to Hebrew: Unveiling DictaLM 2.0 with Enhanced Vocabulary and Instruction Capabilities**Shaltiel Shmidman, Avi Shmidman, Amir DN Cohen, et al.*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2024-adapting-llms-hebrew-unveiling-dictalm/)
756. [**AraSTEM: A Native Arabic Multiple Choice Question Benchmark for Evaluating LLMs Knowledge In STEM Subjects**Ahmad Mustapha; Hadi Al-Khansa; Hadi Al-Mubasher; Aya Mourad; Ranam Hamoud; Hasan El-Husseini; Marwah Al-Sakkaf;, Mariette Awad*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/mustapha-2024-arastem-native-arabic-multiple-choice/)
757. [**Evaluating Large Language Models for Health-related Queries with Presuppositions**Navreet Kaur, Monojit Choudhury, Danish Pruthi*2024 · 15 citations*](https://md.research.elamur.ai/free/en/papers/kaur-2024-evaluating-large-language-models-health/)
758. [**HeRo: RoBERTa and Longformer Hebrew Language Models**Vitaly Shalumov, Harel Haskey*2023 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shalumov-2023-hero-roberta-longformer-hebrew-language/)
759. [**Jais 2: A Family of Arabic-Centric Open Large Language Models**Mohamed Anwar, Abed Alhakim Freihat, George Ibrahim, et al.*2026 · 14 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2026-jais-2-family-arabic-centric/)
760. [**Comparative Study of Multilingual Idioms and Similes in Large Language Models**Paria Khoshtab, Danial Namazifard, Mostafa Masoudi, et al.*2025 · 14 citations*](https://md.research.elamur.ai/free/en/papers/khoshtab-2025-comparative-study-multilingual-idioms-similes/)
761. [**Alignment at Pre-training! Towards Native Alignment for Arabic LLMs**Juhao Liang, Zhenyang Cai, Jianqing Zhu, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/liang-2024-alignment-pre-training-towards-native/)
762. [**Resolving Discrepancies in Compute-Optimal Scaling of Language Models**Tomer Porian, Mitchell Wortsman, Jenia Jitsev, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/porian-2024-resolving-discrepancies-compute-optimal-scaling/)
763. [**SaudiBERT: A Large Language Model Pretrained on Saudi Dialect Corpora**Faisal Qarah*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/qarah-2024-saudibert-large-language-model-pretrained/)
764. [**Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models — The Story Goes On**Liang Zeng, Liangjun Zhong, Liang Zhao, et al.*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2024-skywork-math-data-scaling-laws/)
765. [**TigerCoder: A Novel Suite of LLMs for Code Generation in Bangla**Nishat Raihan, Antonios Anastasopoulos, Marcos Zampieri*2026 · 13 citations*](https://md.research.elamur.ai/free/en/papers/raihan-2026-tigercoder-novel-suite-llms-code/)
766. [**SSA-COMET: Do LLMs Outperform Learned Metrics in Evaluating MT for Under-Resourced African Languages?**Senyu Li, Jiayi Wang, Felermino D. M. A. Ali, et al.*2025 · 13 citations*](https://md.research.elamur.ai/free/en/papers/li-2025-ssa-comet-do-llms-outperform/)
767. [**from Benign import Toxic: Jailbreaking the Language Model via Adversarial Metaphors**Yu Yan, Sheng Sun, Zenghao Duan, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/yan-2025-benign-import-toxic-jailbreaking-language/)
768. [**The Impact of Token Granularity on the Predictive Power of Language Model Surprisal**Byung-Doh Oh, William Schuler*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/oh-2025-impact-token-granularity-predictive-power/)
769. [**When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning**Nishad Singhi, Hritik Bansal, Arian Hosseini, et al.*2025 · 12 citations*](https://md.research.elamur.ai/free/en/papers/singhi-2025-solve-verify-compute-optimal-problem/)
770. [**A Construction Grammar Corpus of Varying Schematicity: A Dataset for the Evaluation of Abstractions in Language Models**Claire Bonial, Harish Tayyar Madabushi*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/bonial-2024-construction-grammar-corpus-varying-schematicity/)
771. [**Amharic LLaMA and LLaVA: Multimodal LLMs for Low Resource Languages**Michael Andersland*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/andersland-2024-amharic-llama-llava-multimodal-llms/)
772. [**Towards Ontology Construction with Language Models**Maurice Funk, Simon Hosemann, Jean Christoph Jung, et al.*2023 · 12 citations*](https://md.research.elamur.ai/free/en/papers/funk-2023-towards-ontology-construction-language-models/)
773. [**How well can LLMs Grade Essays in Arabic?**Rayed Ghazawi, Edwin Simpson*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/ghazawi-2025-well-llms-grade-essays-arabic/)
774. [**Memorization or Reasoning? Exploring the Idiom Understanding of LLMs**Jisu Kim, Youngwoo Shin, Uiji Hwang, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/kim-2025-memorization-or-reasoning-exploring-idiom/)
775. [**Do Large Language Models Understand Conversational Implicature- A case study with a Chinese sitcom**Shisen Yue, Siyuan Song, Xinyuan Cheng, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/yue-2024-do-large-language-models-understand/)
776. [**Pragmatic Competence Evaluation of Large Language Models for the Korean Language**Dojun Park, Jiwoo Lee, Hyeyun Jeong, et al.*2024 · 11 citations*](https://md.research.elamur.ai/free/en/papers/park-2024-pragmatic-competence-evaluation-large-language/)
777. [**Are Frequent Phrases Directly Retrieved like Idioms? An Investigation with Self-Paced Reading and Language Models**Giulia Rambelli, Emmanuele Chersoni, Marco S. G. Senaldi, et al.*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/rambelli-2023-are-frequent-phrases-directly-retrieved/)
778. [**How Are Idioms Processed Inside Transformer Language Models?**Ye Tian, Isobel James, Hye Son*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/tian-2023-how-are-idioms-processed-inside/)
779. [**LLMs Struggle to Reject False Presuppositions when Misinformation Stakes are High**Judith Sieker, Clara Lachenmaier, Sina Zarrieß*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/sieker-2025-llms-struggle-reject-false-presuppositions/)
780. [**EgyBERT: A Large Language Model Pretrained on Egyptian Dialect Corpora**Faisal Qarah*2024 · 10 citations*](https://md.research.elamur.ai/free/en/papers/qarah-2024-egybert-large-language-model-pretrained/)
781. [**Child-Directed Language Does Not Consistently Boost Syntax Learning in Language Models**Francesca Padovani, Jaap Jumelet, Yevgen Matusevych, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/padovani-2025-child-directed-language-does-not/)
782. [**When Your Language Model Cannot Even Do Determiners Right: Probing for Anti-Presuppositions and the Maximize Presupposition! Principle**Judith Sieker, Sina Zarrieß*2023 · 9 citations*](https://md.research.elamur.ai/free/en/papers/sieker-2023-when-your-language-model-cannot/)
783. [**BERT, can HE predict contrastive focus? Predicting and controlling prominence in neural TTS using a language model**Brooke Stephenson, Laurent Besacier, Laurent Girin, et al.*2022 · 9 citations*](https://md.research.elamur.ai/free/en/papers/stephenson-2022-bert-he-predict-contrastive-focus/)
784. [**Can language models capture syntactic associations without surface cues? A case study of reflexive anaphor licensing in English control constructions**Soo-Hwan Lee, Sebastian Schuster*2022 · 9 citations*](https://md.research.elamur.ai/free/en/papers/lee-2022-can-language-models-capture-syntactic/)
785. [**Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Understanding**Abbas Ghaddar, Yimeng Wu, Sunyam Bagga, et al.*2022 · 9 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2022-revisiting-pre-trained-language-models-their/)
786. [**From Guidelines to Practice: A New Paradigm for Arabic Language Model Evaluation**Serry Sibaee, Omer Nacar, Adel Ammar, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/sibaee-2025-guidelines-practice-new-paradigm-arabic/)
787. [**Sacred or Synthetic? Evaluating LLM Reliability and Abstention for Religious Questions**Farah Atif, Nursultan Askarbekuly, Kareem Darwish, et al.*2025 · 8 citations*](https://md.research.elamur.ai/free/en/papers/atif-2025-sacred-synthetic-evaluating-llm-reliability/)
788. [**Optimized Quran Passage Retrieval Using an Expanded QA Dataset and Fine-Tuned Language Models**Mohamed Basem; Islam Oshallah; Baraa Hikal; Ali Hamdi;, Ammar Mohamed*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/basem-2024-optimized-quran-passage-retrieval-using/)
789. [**Bridging the Resource Gap: Exploring the Efficacy of English and Multilingual LLMs for Swedish**Oskar Holmström, Jenny Kunz, Marco Kuhlmann*2023 · 8 citations*](https://md.research.elamur.ai/free/en/papers/holmstrom-2023-bridging-resource-gap-exploring-efficacy/)
790. [**We Understand Elliptical Sentences, and Language Models should Too: A New Dataset for Studying Ellipsis and its Interaction with Thematic Fit**Davide Testa, Emmanuele Chersoni, Alessandro Lenci*2023 · 8 citations*](https://md.research.elamur.ai/free/en/papers/testa-2023-we-understand-elliptical-sentences-language/)
791. [**Beyond Random Sampling: Efficient Language Model Pretraining via Curriculum Learning**Yang Zhang, Amr Mohamed, Hadi Abdine, et al.*2026 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2026-beyond-random-sampling-efficient-language/)
792. [**This One or That One? A Study on Accessibility via Demonstratives with Multimodal Large Language Models**Yu Wang, Emmanuele Chersoni, Chu-Ren Huang*2026 · 7 citations*](https://md.research.elamur.ai/free/en/papers/wang-2026-this-one-or-that-one/)
793. [**A Comprehensive Evaluation of Large Language Models on Mental Illnesses in Arabic Context**Noureldin Zahran, Aya E. Fouda, Radwa J. Hanafy, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/zahran-2025-comprehensive-evaluation-large-language-models/)
794. [**Bilingual Adaptation of Monolingual Foundation Models**Gurpreet Gosal, Yishi Xu, Gokul Ramakrishnan, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/gosal-2024-bilingual-adaptation-monolingual-foundation-models/)
795. [**Cutting Through the Noise: Boosting LLM Performance on Math Word Problems**Ujjwala Anantheswaran, Himanshu Gupta, Kevin Scaria, et al.*2024 · 7 citations*](https://md.research.elamur.ai/free/en/papers/anantheswaran-2024-cutting-through-noise-boosting-llm/)
796. [**Explicit Morphological Knowledge Improves Pre-training of Language Models for Hebrew**Eylon Gueta, Omer Goldman, Reut Tsarfaty*2023 · 7 citations*](https://md.research.elamur.ai/free/en/papers/gueta-2023-explicit-morphological-knowledge-improves-pre/)
797. [**Towards more Human-like Language Models based on Contextualizer Pretraining Strategy**Chenghao Xiao, G Thomas Hudson, Noura Al Moubayed*2023 · 7 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2023-more-human-like-language-models/)
798. [**Large-scale text pre-training helps with dialogue act recognition, but not without fine-tuning**Bill Noble, Vladislav Maraev*2021 · 7 citations*](https://md.research.elamur.ai/free/en/papers/noble-2021-large-scale-text-pre-training/)
799. [**Comparing human and LLM politeness strategies in free production**Haoran Zhao, Robert D. Hawkins*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2025-comparing-human-llm-politeness-strategies/)
800. [**Do LLMs Understand Dialogues? A Case Study on Dialogue Acts**Ayesha Qamar, Jonathan Tong, Ruihong Huang*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/qamar-2025-do-llms-understand-dialogues-case/)
801. [**IPA CHILDES & G2P+: Feature-Rich Resources for Cross-Lingual Phonology and Phonemic Language Modeling**Zébulon Goriely, Paula Buttery*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/goriely-2025-ipa-childes-g2p-feature-rich/)
802. [**Pragmatic Inference Chain (PIC) Improving LLMs' Reasoning of Authentic Implicit Toxic Language**Xi Chen, Shuo Wang*2025 · 6 citations*](https://md.research.elamur.ai/free/en/papers/chen-2025-pragmatic-inference-chain-pic-improving/)
803. [**Detecting Anti-Semitic Hate Speech using Transformer-based Large Language Models**Dengyi Liu, Minghao Wang, Andrew G. Catlin*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-detecting-anti-semitic-hate-speech/)
804. [**Ensemble Language Models for Multilingual Sentiment Analysis**Md Arid Hasan*2024 · 6 citations*](https://md.research.elamur.ai/free/en/papers/hasan-2024-ensemble-language-models-multilingual-sentiment/)
805. [**Large Language Models and Arabic Content: A Review**Haneh Rhel, Dmitri Roussinov*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/rhel-2025-large-language-models-arabic-content/)
806. [**LLM Dependency Parsing with In-Context Rules**Michael Ginn, Alexis Palmer*2025 · 5 citations*](https://md.research.elamur.ai/free/en/papers/ginn-2025-llm-dependency-parsing-context-rules/)
807. [**Exploring Tokenization Strategies and Vocabulary Sizes for Enhanced Arabic Language Models**Mohamed Taher Alrefaie, Nour Eldin Morsy, Nada Samir*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/alrefaie-2024-exploring-tokenization-strategies-vocabulary-sizes/)
808. [**Do Pretrained Contextual Language Models Distinguish between Hebrew Homograph Analyses?**Avi Shmidman, Cheyn Shmuel Shmidman, Dan Bareket, et al.*2023 · 5 citations*](https://md.research.elamur.ai/free/en/papers/shmidman-2023-do-pretrained-contextual-language-models/)
809. [**Assessing the Linguistic Knowledge in Arabic Pre-trained Language Models Using Minimal Pairs**Wafa Abdullah Alrajhi, Hend Al-Khalifa, Abdulmalik AlSalman*2022 · 5 citations*](https://md.research.elamur.ai/free/en/papers/alrajhi-2022-assessing-linguistic-knowledge-arabic-pre/)
810. [**Parameter and Data Efficient Continual Pre-training for Robustness to Dialectal Variance in Arabic**Soumajyoti Sarkar, Kaixiang Lin, Sailik Sengupta, et al.*2022 · 5 citations*](https://md.research.elamur.ai/free/en/papers/sarkar-2022-parameter-data-efficient-continual-pre/)
811. [**Large Language Models as Oracles for Ontology Alignment**Sviatoslav Lushnei, Dmytro Shumskyi, Severyn Shykula, et al.*2026 · 4 citations*](https://md.research.elamur.ai/free/en/papers/lushnei-2026-large-language-models-as-oracles/)
812. [**An Ensemble Classification Approach in A Multi-Layered Large Language Model Framework for Disease Prediction**Ali Hamdi, Malak Mohamed, Rokaia Emad, et al.*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/hamdi-2025-ensemble-classification-approach-multi-layered/)
813. [**AraFinNews: Arabic Financial Summarisation with Domain-Adapted LLMs**Mo El-Haj, Paul Rayson*2025 · 4 citations*](https://md.research.elamur.ai/free/en/papers/el-haj-2025-arafinnews-arabic-financial-summarisation-domain/)
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