--- title: "Language models & pretraining — papers, page 8" description: "Language models & pretraining: 1,079 papers of the Elamur Research library · page 8 of 12 · 626–725, the most cited first." canonical: "https://research.elamur.ai/free/en/topics/language-models/page/8/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/topics/language-models/page/8/) [home](https://md.research.elamur.ai/free/en/) / [topics](https://md.research.elamur.ai/free/en/topics/) / [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/) / page 8 # 🧠 Language models & pretraining 1,079 papers · page 8 of 12 · 626–725 · 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. [← prev](https://md.research.elamur.ai/free/en/topics/language-models/page/7/) [1](https://md.research.elamur.ai/free/en/topics/language-models/) … [7](https://md.research.elamur.ai/free/en/topics/language-models/page/7/) **8** [9](https://md.research.elamur.ai/free/en/topics/language-models/page/9/) … [12](https://md.research.elamur.ai/free/en/topics/language-models/page/12/) [next →](https://md.research.elamur.ai/free/en/topics/language-models/page/9/) 626. [**LLMs instead of Human Judges? A Large Scale Empirical Study across 20 NLP Evaluation Tasks**Anna Bavaresco, Raffaella Bernardi, Leonardo Bertolazzi, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/bavaresco-2024-llms-instead-human-judges-large/) 627. [**Efficient Training of Language Models to Fill in the Middle**Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.*2022 · 137 citations*](https://md.research.elamur.ai/free/en/papers/bavarian-2022-efficient-training-language-models-fill/) 628. [**A fine-grained comparison of pragmatic language understanding in humans and language models**Jennifer Hu, Sammy Floyd, Olessia Jouravlev, et al.*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-fine-grained-comparison-pragmatic-language/) 629. [**Detecting Language Model Attacks with Perplexity**Gabriel Alon, Michael Kamfonas*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/alon-2023-detecting-language-model-attacks-perplexity/) 630. [**MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback**Xingyao Wang, Zihan Wang, Jiateng Liu, et al.*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-mint-evaluating-llms-multi-turn/) 631. [**mPLUG-Owl2: Revolutionizing Multi-modal Large Language Model with Modality Collaboration**Qinghao Ye, Haiyang Xu, Jiabo Ye, et al.*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/ye-2023-mplug-owl2-revolutionizing-multi-modal/) 632. [**Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models**Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.*2022 · 136 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2022-attributed-question-answering-evaluation-modeling/) 633. [**Byte Pair Encoding is Suboptimal for Language Model Pretraining**Kaj Bostrom, Greg Durrett*2020 · 136 citations*](https://md.research.elamur.ai/free/en/papers/bostrom-2020-byte-pair-encoding-is-suboptimal/) 634. [**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/) 635. [**RAFT: Adapting Language Model to Domain Specific RAG**Tianjun Zhang, Shishir G. Patil, Naman Jain, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-raft-adapting-language-model-domain/) 636. [**Token-Budget-Aware LLM Reasoning**Tingxu Han, Zhenting Wang, Chunrong Fang, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/han-2024-token-budget-aware-llm-reasoning/) 637. [**SafetyBench: Evaluating the Safety of Large Language Models**Zhexin Zhang, Leqi Lei, Lindong Wu, et al.*2023 · 135 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-safetybench-evaluating-safety-large/) 638. [**Many-Shot In-Context Learning**Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.*2024 · 134 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2024-many-shot-context-learning/) 639. [**Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Models**Paul Röttger, Valentin Hofmann, Valentina Pyatkin, et al.*2024 · 134 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-political-compass-or-spinning-arrow/) 640. [**Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models**Pat Verga, Sebastian Hofstatter, Sophia Althammer, et al.*2024 · 134 citations*](https://md.research.elamur.ai/free/en/papers/verga-2024-replacing-judges-juries-evaluating-llm/) 641. [**Simple and Effective Masked Diffusion Language Models**Subham Sekhar Sahoo, Marianne Arriola, Yair Schiff, et al.*2024 · 134 citations*](https://md.research.elamur.ai/free/en/papers/sahoo-2024-simple-effective-masked-diffusion-language/) 642. [**Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models**Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.*2023 · 134 citations*](https://md.research.elamur.ai/free/en/papers/singh-2023-human-data-scaling-self-training/) 643. [**InFoBench: Evaluating Instruction Following Ability in Large Language Models**Yiwei Qin, Kaiqiang Song, Yebowen Hu, et al.*2024 · 133 citations*](https://md.research.elamur.ai/free/en/papers/qin-2024-infobench-evaluating-instruction-following-ability/) 644. [**TOFU: A Task of Fictitious Unlearning for LLMs**Pratyush Maini, Zhili Feng, Avi Schwarzschild, et al.*2024 · 133 citations*](https://md.research.elamur.ai/free/en/papers/maini-2024-tofu-task-fictitious-unlearning-llms/) 645. [**Prompting is not a substitute for probability measurements in large language models**Jennifer Hu, Roger Levy*2023 · 133 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-prompting-is-not-substitute-probability/) 646. [**Long-context LLMs Struggle with Long In-context Learning**Tianle Li, Ge Zhang, Quy Duc Do, et al.*2024 · 132 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-long-context-llms-struggle-long/) 647. [**EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 131 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-2-faster-inference-language/) 648. [**EuroLLM: Multilingual Language Models for Europe**Pedro Henrique Martins, Patrick Fernandes, Joao Alves, et al.*2024 · 131 citations*](https://md.research.elamur.ai/free/en/papers/martins-2024-eurollm-multilingual-language-models-europe/) 649. [**Understanding the Effects of RLHF on LLM Generalisation and Diversity**Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, et al.*2023 · 131 citations*](https://md.research.elamur.ai/free/en/papers/kirk-2023-understanding-effects-rlhf-llm-generalisation/) 650. [**Extracting Latent Steering Vectors from Pretrained Language Models**Nishant Subramani, Nivedita Suresh, Matthew Peters*2022 · 131 citations*](https://md.research.elamur.ai/free/en/papers/subramani-2022-extracting-latent-steering-vectors-pretrained/) 651. [**FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation**Tu Vu, Mohit Iyyer, Xuezhi Wang, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/vu-2023-freshllms-refreshing-large-language-models/) 652. [**Secrets of RLHF in Large Language Models Part I: PPO**Rui Zheng, Shihan Dou, Songyang Gao, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2023-secrets-rlhf-large-language-models/) 653. [**Improving Language Model Negotiation with Self-Play and In-Context Learning from AI Feedback**Yao Fu, Hao Peng, Tushar Khot, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/fu-2023-improving-language-model-negotiation-self/) 654. [**Retrieval meets Long Context Large Language Models**Peng Xu, Wei Ping, Xianchao Wu, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-retrieval-meets-long-context-large/) 655. [**AceGPT, Localizing Large Language Models in Arabic**Huang Huang, Fei Yu, Jianqing Zhu, et al.*2024 · 127 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-acegpt-localizing-large-language-models/) 656. [**Time Travel in LLMs: Tracing Data Contamination in Large Language Models**Shahriar Golchin, Mihai Surdeanu*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/golchin-2023-time-travel-llms-tracing-data/) 657. [**Knowledge Unlearning for Mitigating Privacy Risks in Language Models**Joel Jang, Dongkeun Yoon, Sohee Yang, et al.*2022 · 126 citations*](https://md.research.elamur.ai/free/en/papers/jang-2022-knowledge-unlearning-mitigating-privacy-risks/) 658. [**InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory**Chaojun Xiao, Pengle Zhang, Xu Han, et al.*2024 · 125 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2024-infllm-training-free-long-context/) 659. [**Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations**Zeming Wei, Yifei Wang, Ang Li, et al.*2023 · 125 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-jailbreak-guard-aligned-language-models/) 660. [**Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions**Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/bianchi-2023-safety-tuned-llamas-lessons-improving/) 661. [**Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models**Lei Li, Yuqi Wang, Runxin Xu, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-multimodal-arxiv-dataset-improving-scientific/) 662. [**Large Language Model Alignment: A Survey**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/) 663. [**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/) 664. [**Automated evaluation of written discourse coherence using GPT-4**Ben Naismith, Phoebe Mulcaire, Jill Burstein*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/naismith-2023-automated-evaluation-written-discourse-coherence/) 665. [**Fine-tuning Language Models for Factuality**Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/tian-2023-fine-tuning-language-models-factuality/) 666. [**The Impact of Reasoning Step Length on Large Language Models**Mingyu Jin, Qinkai Yu, Dong Shu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-impact-reasoning-step-length-large/) 667. [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 118 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/) 668. [**Chameleon: Mixed-Modal Early-Fusion Foundation Models**Chameleon Team*2024 · 117 citations*](https://md.research.elamur.ai/free/en/papers/team-2024-chameleon-mixed-modal-early-fusion/) 669. [**Pretraining Language Models with Human Preferences**Tomasz Korbak, Kejian Shi, Angelica Chen, et al.*2023 · 117 citations*](https://md.research.elamur.ai/free/en/papers/korbak-2023-pretraining-language-models-human-preferences/) 670. [**QuIP#: Even Better LLM Quantization with Hadamard Incoherence and Lattice Codebooks**Albert Tseng, Jerry Chee, Qingyao Sun, et al.*2024 · 116 citations*](https://md.research.elamur.ai/free/en/papers/tseng-2024-quip-even-better-llm-quantization/) 671. [**HealthBench: Evaluating Large Language Models Towards Improved Human Health**Rahul K. Arora, Jason Wei, Rebecca Soskin Hicks, et al.*2025 · 115 citations*](https://md.research.elamur.ai/free/en/papers/arora-2025-healthbench-evaluating-large-language-models/) 672. [**Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities**Kazuki Fujii, Taishi Nakamura, Mengsay Loem, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/fujii-2024-continual-pre-training-cross-lingual/) 673. [**Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models**Yangzhen Wu, Zhiqing Sun, Shanda Li, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/wu-2024-inference-scaling-laws-empirical-analysis/) 674. [**SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models**Lijun Li, Bowen Dong, Ruohui Wang, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-salad-bench-hierarchical-comprehensive-safety/) 675. [**Demystifying Long Chain-of-Thought Reasoning in LLMs**Edward Yeo, Yuxuan Tong, Morry Niu, et al.*2025 · 113 citations*](https://md.research.elamur.ai/free/en/papers/yeo-2025-demystifying-long-chain-thought-reasoning/) 676. [**ALLaM: Large Language Models for Arabic and English**M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/bari-2024-allam-large-language-models-arabic/) 677. [**Quiet-STaR: Language models can teach themselves to think before speaking***2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/al-2024-quiet-star-language-models-teach/) 678. [**Break the Sequential Dependency of LLM Inference Using Lookahead Decoding**Yichao Fu, Peter Bailis, Ion Stoica, et al.*2024 · 112 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-break-sequential-dependency-llm-inference/) 679. [**DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Data**Huajian Xin, Daya Guo, Zhihong Shao, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/xin-2024-deepseek-prover-advancing-theorem-proving/) 680. [**DistiLLM: Towards Streamlined Distillation for Large Language Models**Jongwoo Ko, Sungnyun Kim, Tianyi Chen, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/ko-2024-distillm-towards-streamlined-distillation-large/) 681. [**Certifying LLM Safety against Adversarial Prompting**Aounon Kumar, Chirag Agarwal, Suraj Srinivas, et al.*2023 · 110 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2023-certifying-llm-safety-against-adversarial/) 682. [**Olmo 3**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 109 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/) 683. [**DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads**Guangxuan Xiao, Jiaming Tang, Jingwei Zuo, et al.*2024 · 109 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2024-duoattention-efficient-long-context-llm/) 684. [**Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification**Aojun Zhou, Ke Wang, Zimu Lu, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-solving-challenging-math-word-problems/) 685. [**RestGPT: Connecting Large Language Models with Real-World RESTful APIs**Yifan Song, Weimin Xiong, Dawei Zhu, et al.*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/song-2023-restgpt-connecting-large-language-models/) 686. [**Data Engineering for Scaling Language Models to 128K Context**Yao Fu, Rameswar Panda, Xinyao Niu, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/fu-2024-data-engineering-scaling-language-models/) 687. [**GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers**Qintong Li, Leyang Cui, Xueliang Zhao, et al.*2024 · 107 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-gsm-plus-comprehensive-benchmark-evaluating/) 688. [**Evaluating the Performance of Large Language Models on GAOKAO Benchmark**Xiaotian Zhang, Chunyang Li, Yi Zong, et al.*2023 · 107 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-evaluating-performance-large-language/) 689. [**Physics of Language Models: Part 3.1, Knowledge Storage and Extraction**Zeyuan Allen-Zhu, Yuanzhi Li*2023 · 107 citations*](https://md.research.elamur.ai/free/en/papers/allen-zhu-2023-physics-language-models-part-3/) 690. [**French CrowS-Pairs: Extending a challenge dataset for measuring social bias in masked language models to a language other than English**Aurélie Névéol, Yoann Dupont, Julien Bezançon, et al.*2022 · 107 citations*](https://md.research.elamur.ai/free/en/papers/neveol-2022-french-crows-pairs-extending-challenge/) 691. [**GPT detectors are biased against non-native English writers**Weixin Liang, Mert Yuksekgonul, Yining Mao, et al.*2023 · 106 citations*](https://md.research.elamur.ai/free/en/papers/liang-2023-gpt-detectors-biased-against-non/) 692. [**TokenSkip: Controllable Chain-of-Thought Compression in LLMs**Heming Xia, Chak Tou Leong, Wenjie Wang, et al.*2025 · 105 citations*](https://md.research.elamur.ai/free/en/papers/xia-2025-tokenskip-controllable-chain-thought-compression/) 693. [**Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs**Chris Yuhao Liu, Liang Zeng, Jiacai Liu, et al.*2024 · 104 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-skywork-reward-bag-tricks/) 694. [**Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning**Tian Xie, Zitian Gao, Qingnan Ren, et al.*2025 · 103 citations*](https://md.research.elamur.ai/free/en/papers/xie-2025-logic-rl-unleashing-llm/) 695. [**Tokenizer Choice For LLM Training: Negligible or Crucial?**Mehdi Ali, Michael Fromm, Klaudia Thellmann, et al.*2024 · 102 citations*](https://md.research.elamur.ai/free/en/papers/ali-2024-tokenizer-choice-llm-training-negligible/) 696. [**Scaling Laws for Transfer**Danny Hernandez, Jared Kaplan, Tom Henighan, et al.*2021 · 102 citations*](https://md.research.elamur.ai/free/en/papers/hernandez-2021-scaling-laws-transfer/) 697. [**Rethinking Benchmark and Contamination for Language Models with Rephrased Samples**Shuo Yang, Wei-Lin Chiang, Lianmin Zheng, et al.*2023 · 100 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-rethinking-benchmark-contamination-language-models/) 698. [**MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning**Ke Wang, Houxing Ren, Aojun Zhou, et al.*2023 · 98 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-mathcoder-seamless-code-integration-llms/) 699. [**LongAlign: A Recipe for Long Context Alignment of Large Language Models**Yushi Bai, Xin Lv, Jiajie Zhang, et al.*2024 · 97 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-longalign-recipe-long-context/) 700. [**Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs**Xin Lai, Zhuotao Tian, Yukang Chen, et al.*2024 · 97 citations*](https://md.research.elamur.ai/free/en/papers/lai-2024-step-dpo-step-wise-preference/) 701. [**Skywork: A More Open Bilingual Foundation Model**Tianwen Wei, Liang Zhao, Lichang Zhang, et al.*2023 · 91 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-skywork-more-open-bilingual/) 702. [**WECHSEL: Effective initialization of subword embeddings for cross-lingual transfer of monolingual language models**Benjamin Minixhofer, Fabian Paischer, Navid Rekabsaz*2022 · 90 citations*](https://md.research.elamur.ai/free/en/papers/minixhofer-2022-wechsel-effective-initialization-subword-embeddings/) 703. [**Language Modeling Is Compression**Gregoire Deletang, Anian Ruoss, Paul-Ambroise Duquenne, et al.*2023 · 89 citations*](https://md.research.elamur.ai/free/en/papers/deletang-2023-language-modeling-compression/) 704. [**AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Models**Harish Tayyar Madabushi, Edward Gow-Smith, Carolina Scarton, et al.*2021 · 86 citations*](https://md.research.elamur.ai/free/en/papers/madabushi-2021-astitchinlanguagemodels-dataset-methods-exploration-idiomaticity/) 705. [**Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction**Daniela Gerz, Ivan Vulić, Edoardo Ponti, et al.*2018 · 82 citations*](https://md.research.elamur.ai/free/en/papers/gerz-2018-language-modeling-morphologically-rich-languages/) 706. [**D4: Improving LLM Pretraining via Document De-Duplication and Diversification**Kushal Tirumala, Daniel Simig, Armen Aghajanyan, et al.*2023 · 79 citations*](https://md.research.elamur.ai/free/en/papers/tirumala-2023-d4-improving-llm-pretraining-document/) 707. [**Are Pretrained Language Models Symbolic Reasoners over Knowledge?**Nora Kassner, Benno Krojer, Hinrich Schütze*2020 · 79 citations*](https://md.research.elamur.ai/free/en/papers/kassner-2020-are-pretrained-language-models-symbolic/) 708. [**PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics Capabilities**Settaluri Sravanthi, Meet Doshi, Pavan Tankala, et al.*2024 · 75 citations*](https://md.research.elamur.ai/free/en/papers/sravanthi-2024-pub-pragmatics-understanding-benchmark-assessing/) 709. [**Dipping PLMs Sauce: Bridging Structure and Text for Effective Knowledge Graph Completion via Conditional Soft Prompting**Chen Chen, Yufei Wang, Aixin Sun, et al.*2023 · 75 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-dipping-plms-sauce-bridging-structure/) 710. [**MT-Eval: A Multi-Turn Capabilities Evaluation Benchmark for Large Language Models**Wai-Chung Kwan, Xingshan Zeng, Yuxin Jiang, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/kwan-2024-mt-eval-multi-turn-capabilities/) 711. [**AlephBERT: Language Model Pre-training and Evaluation from Sub-Word to Sentence Level**Amit Seker, Elron Bandel, Dan Bareket, et al.*2022 · 57 citations*](https://md.research.elamur.ai/free/en/papers/seker-2022-alephbert-language-model-pre-training/) 712. [**AlephBERT: A Hebrew Large Pre-Trained Language Model to Start-off your Hebrew NLP Application With**Amit Seker, Elron Bandel, Dan Bareket, et al.*2021 · 56 citations*](https://md.research.elamur.ai/free/en/papers/seker-2021-alephbert-hebrew-large-pre-trained/) 713. [**Tree Linearization in English: Improving Language Model Based Approaches**Katja Filippova, Michael Strube*2009 · 56 citations*](https://md.research.elamur.ai/free/en/papers/filippova-2009-tree-linearization-english-improving-language/) 714. [**Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs**Aaditya K. Singh, DJ Strouse*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/singh-2024-tokenization-counts-impact-tokenization-arithmetic/) 715. [**The Unreasonable Effectiveness of Transformer Language Models in Grammatical Error Correction**Dimitris Alikaniotis, Vipul Raheja*2019 · 52 citations*](https://md.research.elamur.ai/free/en/papers/alikaniotis-2019-unreasonable-effectiveness-transformer-language-models/) 716. [**SpeechTokenizer: Unified Speech Tokenizer for Speech Large Language Models**Xin Zhang, Dong Zhang, Shimin Li, et al.*2023 · 51 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-speechtokenizer-unified-speech-tokenizer-speech/) 717. [**Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges**Bolei Ma, Yuting Li, Wei Zhou, et al.*2025 · 49 citations*](https://md.research.elamur.ai/free/en/papers/ma-2025-pragmatics-era-large-language-models/) 718. [**Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws**Nikhil Sardana, Jacob Portes, Sasha Doubov, et al.*2024 · 47 citations*](https://md.research.elamur.ai/free/en/papers/sardana-2024-chinchilla-optimal-accounting-inference-language/) 719. 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