---
title: "Who cites Illia Polosukhin — page 8"
description: "18,005 papers of the Elamur Research library cite the works of Illia Polosukhin, found in their bibliographies · page 8 of 12 · 701–800; the most cited…"
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---
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# Who cites Illia Polosukhin

18,396 citations of their works from 18,005 papers of our library (of the 140,884 whose bibliographies we read) · 1,116 with a page here, the most cited first · page 8 of 12 · 701–800 · [← Illia Polosukhin](https://md.research.elamur.ai/free/en/authors/illia-polosukhin/)

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701. [**Measuring short-form factuality in large language models**Jason Wei, Nguyen Karina, Hyung Won Chung, et al.*2024 · 147 citations*](https://md.research.elamur.ai/free/en/papers/wei-2024-measuring-short-form-factuality-large/)
702. [**Looking for a Needle in a Haystack: A Comprehensive Study of Hallucinations in Neural Machine Translation**Nuno M. Guerreiro, Elena Voita, André Martins*2023 · 147 citations*](https://md.research.elamur.ai/free/en/papers/guerreiro-2023-looking-needle-haystack-comprehensive-study/)
703. [**Neural Models for Reasoning over Multiple Mentions Using Coreference**Bhuwan Dhingra, Qiao Jin, Zhilin Yang, et al.*2018 · 147 citations*](https://md.research.elamur.ai/free/en/papers/dhingra-2018-neural-models-reasoning-over-multiple/)
704. [**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/)
705. [**Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding**Heming Xia, Zhe Yang, Qingxiu Dong, et al.*2024 · 145 citations*](https://md.research.elamur.ai/free/en/papers/xia-2024-unlocking-efficiency-large-language-model/)
706. [**Context-faithful Prompting for Large Language Models**Wenxuan Zhou, Sheng Zhang, Hoifung Poon, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-context-faithful-prompting-large-language/)
707. [**Fact-Checking Complex Claims with Program-Guided Reasoning**Liangming Pan, Xiaobao Wu, Xinyuan Lu, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-fact-checking-complex-claims-program/)
708. [**RA-DIT: Retrieval-Augmented Dual Instruction Tuning**Xi Victoria Lin, Xilun Chen, Mingda Chen, et al.*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-ra-dit-retrieval-augmented-dual/)
709. [**Unified Demonstration Retriever for In-Context Learning**Xiaonan Li, Kai Lv, Hang Yan, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-unified-demonstration-retriever-context-learning/)
710. [**GLUCOSE: GeneraLized and COntextualized Story Explanations**Nasrin Mostafazadeh, Aditya Kalyanpur, Lori Moon, et al.*2020 · 144 citations*](https://md.research.elamur.ai/free/en/papers/mostafazadeh-2020-glucose-generalized-contextualized-story-explanations/)
711. [**TALM: Tool Augmented Language Models**Aaron Parisi, Yao Zhao, Noah Fiedel*2022 · 142 citations*](https://md.research.elamur.ai/free/en/papers/parisi-2022-talm-tool-augmented-language-models/)
712. [**Rethinking embedding coupling in pre-trained language models**Hyung Won Chung, Thibault Févry, Henry Tsai, et al.*2020 · 142 citations*](https://md.research.elamur.ai/free/en/papers/chung-2020-rethinking-embedding-coupling-pre-trained/)
713. [**Paragraph-level Simplification of Medical Texts**Ashwin Devaraj, Iain Marshall, Byron Wallace, et al.*2021 · 139 citations*](https://md.research.elamur.ai/free/en/papers/devaraj-2021-paragraph-level-simplification-medical-texts/)
714. [**On The Evaluation of Machine Translation Systems Trained With Back-Translation**Sergey Edunov, Myle Ott, Marc'Aurelio Ranzato, et al.*2020 · 139 citations*](https://md.research.elamur.ai/free/en/papers/edunov-2020-evaluation-machine-translation-systems-trained/)
715. [**Trivial Transfer Learning for Low-Resource Neural Machine Translation**Tom Kocmi, Ondřej Bojar*2018 · 139 citations*](https://md.research.elamur.ai/free/en/papers/kocmi-2018-trivial-transfer-learning-low-resource/)
716. [**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/)
717. [**Lost in Translation: Loss and Decay of Linguistic Richness in Machine Translation**Eva Vanmassenhove, Dimitar Shterionov, Andy Way*2019 · 137 citations*](https://md.research.elamur.ai/free/en/papers/vanmassenhove-2019-lost-translation-loss-decay-linguistic/)
718. [**Agent Laboratory: Using LLM Agents as Research Assistants**Samuel Schmidgall, Yusheng Su, Ze Wang, et al.*2025 · 136 citations*](https://md.research.elamur.ai/free/en/papers/schmidgall-2025-agent-laboratory-using-llm/)
719. [**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/)
720. [**SummScreen: A Dataset for Abstractive Screenplay Summarization**Mingda Chen, Zewei Chu, Sam Wiseman, et al.*2022 · 136 citations*](https://md.research.elamur.ai/free/en/papers/chen-2022-summscreen-dataset-abstractive-screenplay-summarization/)
721. [**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/)
722. [**Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention**Jingyang Yuan, Huazuo Gao, Damai Dai, et al.*2025 · 135 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2025-native-sparse-attention-hardware/)
723. [**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/)
724. [**Affective and Contextual Embedding for Sarcasm Detection**Nastaran Babanejad, Heidar Davoudi, Aijun An, et al.*2020 · 135 citations*](https://md.research.elamur.ai/free/en/papers/babanejad-2020-affective-contextual-embedding-sarcasm-detection/)
725. [**Domain Robustness in Neural Machine Translation**Mathias Müller, Annette Rios, Rico Sennrich*2020 · 135 citations*](https://md.research.elamur.ai/free/en/papers/muller-2020-domain-robustness-neural-machine-translation/)
726. [**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/)
727. [**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/)
728. [**Enhancing Zero-shot and Few-shot Stance Detection with Commonsense Knowledge Graph**Rui Liu, Zheng Lin, Yutong Tan, et al.*2021 · 134 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-enhancing-zero-shot-few-shot/)
729. [**Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning**Pan Lu, Ran Gong, Shibiao Jiang, et al.*2021 · 134 citations*](https://md.research.elamur.ai/free/en/papers/lu-2021-inter-gps-interpretable-geometry-problem/)
730. [**Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches**Shane Storks, Qiaozi Gao, Joyce Y. Chai*2019 · 134 citations*](https://md.research.elamur.ai/free/en/papers/storks-2019-recent-advances-natural-language-inference/)
731. [**Findings of the WMT 2018 Shared Task on Quality Estimation**Lucia Specia, Frédéric Blain, Varvara Logacheva, et al.*2018 · 134 citations*](https://md.research.elamur.ai/free/en/papers/specia-2018-findings-wmt-2018-shared-task/)
732. [**Towards Multi-Modal Sarcasm Detection via Hierarchical Congruity Modeling with Knowledge Enhancement**Hui Liu, Wenya Wang, Haoliang Li*2022 · 132 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-multi-modal-sarcasm-detection-hierarchical/)
733. [**Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine Translation**Jungo Kasai, Nikolaos Pappas, Hao Peng, et al.*2020 · 132 citations*](https://md.research.elamur.ai/free/en/papers/kasai-2020-deep-encoder-shallow-decoder-reevaluating/)
734. [**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/)
735. [**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/)
736. [**Task-aware Retrieval with Instructions**Akari Asai, Timo Schick, Patrick Lewis, et al.*2023 · 131 citations*](https://md.research.elamur.ai/free/en/papers/asai-2023-task-aware-retrieval-instructions/)
737. [**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/)
738. [**MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems**Jakub Macina, Nico Daheim, Sankalan Chowdhury, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/macina-2023-mathdial-dialogue-tutoring-dataset-rich/)
739. [**Analyzing Transformers in Embedding Space**Guy Dar, Mor Geva, Ankit Gupta, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/dar-2023-analyzing-transformers-embedding-space/)
740. [**Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition**Vered Shwartz, Ido Dagan*2019 · 129 citations*](https://md.research.elamur.ai/free/en/papers/shwartz-2019-still-pain-neck-evaluating-text/)
741. [**Fanar: An Arabic-Centric Multimodal Generative AI Platform**Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.*2025 · 127 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2025-fanar-arabic-centric-multimodal-generative/)
742. [**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/)
743. [**Understanding Factual Errors in Summarization: Errors, Summarizers, Datasets, Error Detectors**Liyan Tang, Tanya Goyal, Alex Fabbri, et al.*2023 · 126 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-understanding-factual-errors-summarization-errors/)
744. [**A Recipe For Arbitrary Text Style Transfer with Large Language Models**Emily Reif, Daphne Ippolito, Ann Yuan, et al.*2021 · 125 citations*](https://md.research.elamur.ai/free/en/papers/reif-2021-recipe-arbitrary-text-style-transfer/)
745. [**Adversarial Learning for Zero-Shot Stance Detection on Social Media**Emily Allaway, Malavika Srikanth, Kathleen McKeown*2021 · 124 citations*](https://md.research.elamur.ai/free/en/papers/allaway-2021-adversarial-learning-zero-shot-stance/)
746. [**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/)
747. [**Machine Learning for Ancient Languages: A Survey**Thea Sommerschield, Yannis Assael, John Pavlopoulos, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/sommerschield-2023-machine-learning-ancient-languages-survey/)
748. [**DocNLI: A Large-scale Dataset for Document-level Natural Language Inference**Wenpeng Yin, Dragomir Radev, Caiming Xiong*2021 · 121 citations*](https://md.research.elamur.ai/free/en/papers/yin-2021-docnli-large-scale-dataset-document/)
749. [**High Quality Rather than High Model Probability: Minimum Bayes Risk Decoding with Neural Metrics**Markus Freitag, David Grangier, Qijun Tan, et al.*2022 · 120 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2022-high-quality-rather-than-high/)
750. [**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/)
751. [**MetricX-23: The Google Submission to the WMT 2023 Metrics Shared Task**Juraj Juraska, Mara Finkelstein, Daniel Deutsch, et al.*2023 · 118 citations*](https://md.research.elamur.ai/free/en/papers/juraska-2023-metricx-23-google-submission-wmt/)
752. [**Findings of the AmericasNLP 2021 Shared Task on Open Machine Translation for Indigenous Languages of the Americas**Manuel Mager, Arturo Oncevay, Abteen Ebrahimi, et al.*2021 · 118 citations*](https://md.research.elamur.ai/free/en/papers/mager-2021-findings-americasnlp-2021-shared-task/)
753. [**I-BERT: Integer-only BERT Quantization**Sehoon Kim, Amir Gholami, Zhewei Yao, et al.*2021 · 118 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-i-bert-integer-only-bert/)
754. [**DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence**DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.*2026 · 117 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2026-deepseek-v4-highly-efficient/)
755. [**MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases**Louis Martin, Angela Fan, Éric de la Clergerie, et al.*2022 · 117 citations*](https://md.research.elamur.ai/free/en/papers/martin-2022-muss-multilingual-unsupervised-sentence-simplification/)
756. [**Scaling Laws for Autoregressive Generative Modeling**Tom Henighan, Jared Kaplan, Mor Katz, et al.*2020 · 115 citations*](https://md.research.elamur.ai/free/en/papers/henighan-2020-scaling-laws-autoregressive-generative-modeling/)
757. [**RECOMP: Improving Retrieval-Augmented LMs with Compression and Selective Augmentation**Fangyuan Xu, Weijia Shi, Eunsol Choi*2023 · 114 citations*](https://md.research.elamur.ai/free/en/papers/xu-2023-recomp-improving-retrieval-augmented-lms/)
758. [**Document-level Neural MT: A Systematic Comparison**António Lopes, M. Amin Farajian, Rachel Bawden, et al.*2020 · 114 citations*](https://md.research.elamur.ai/free/en/papers/lopes-2020-document-level-neural-mt-systematic/)
759. [**Entity Linking in 100 Languages**Jan A. Botha, Zifei Shan, Daniel Gillick*2020 · 114 citations*](https://md.research.elamur.ai/free/en/papers/botha-2020-entity-linking-100-languages/)
760. [**MLSUM: The Multilingual Summarization Corpus**Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, et al.*2020 · 114 citations*](https://md.research.elamur.ai/free/en/papers/scialom-2020-mlsum-multilingual-summarization-corpus/)
761. [**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/)
762. [**DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search**Huajian Xin, Z. Z. Ren, Junxiao Song, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/xin-2024-deepseek-prover-v1-5-harnessing/)
763. [**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/)
764. [**Language ID in the Wild: Unexpected Challenges on the Path to a Thousand-Language Web Text Corpus**Isaac Caswell, Theresa Breiner, Daan van Esch, et al.*2020 · 111 citations*](https://md.research.elamur.ai/free/en/papers/caswell-2020-language-id-wild-unexpected/)
765. [**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/)
766. [**DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments**Yuxiang Zheng, Dayuan Fu, Xiangkun Hu, et al.*2025 · 108 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2025-deepresearcher-scaling-deep-research-reinforcement/)
767. [**AMR-To-Text Generation with Graph Transformer**Tianming Wang, Xiaojun Wan, Hanqi Jin*2020 · 108 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-amr-text-generation-graph-transformer/)
768. [**APE at Scale and Its Implications on MT Evaluation Biases**Markus Freitag, Isaac Caswell, Scott Roy*2019 · 107 citations*](https://md.research.elamur.ai/free/en/papers/freitag-2019-ape-scale-its-implications-mt/)
769. [**Can Transformer be Too Compositional? Analysing Idiom Processing in Neural Machine Translation**Verna Dankers, Christopher Lucas, Ivan Titov*2022 · 105 citations*](https://md.research.elamur.ai/free/en/papers/dankers-2022-can-transformer-be-too-compositional/)
770. [**LENS: A Learnable Evaluation Metric for Text Simplification**Mounica Maddela, Yao Dou, David Heineman, et al.*2023 · 103 citations*](https://md.research.elamur.ai/free/en/papers/maddela-2023-lens-learnable-evaluation-metric-text/)
771. [**Nemotron-4 340B Technical Report**Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.*2024 · 102 citations*](https://md.research.elamur.ai/free/en/papers/adler-2024-nemotron-4-340b-technical-report/)
772. [**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/)
773. [**Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction**Zhanming Jie, Jierui Li, Wei Lu*2022 · 102 citations*](https://md.research.elamur.ai/free/en/papers/jie-2022-learning-reason-deductively-math-word/)
774. [**Probing Natural Language Inference Models through Semantic Fragments**Kyle Richardson, Hai Hu, Lawrence S. Moss, et al.*2019 · 102 citations*](https://md.research.elamur.ai/free/en/papers/richardson-2019-probing-natural-language-inference-models/)
775. [**UniTE: Unified Translation Evaluation**Yu Wan, Dayiheng Liu, Baosong Yang, et al.*2022 · 100 citations*](https://md.research.elamur.ai/free/en/papers/wan-2022-unite-unified-translation-evaluation/)
776. [**Gender in Danger? Evaluating Speech Translation Technology on the MuST-SHE Corpus**Luisa Bentivogli, Beatrice Savoldi, Matteo Negri, et al.*2020 · 100 citations*](https://md.research.elamur.ai/free/en/papers/bentivogli-2020-gender-danger-evaluating-speech-translation/)
777. [**Cross-Domain Label-Adaptive Stance Detection**Momchil Hardalov, Arnav Arora, Preslav Nakov, et al.*2021 · 96 citations*](https://md.research.elamur.ai/free/en/papers/hardalov-2021-cross-domain-label-adaptive-stance/)
778. [**LinCE: A Centralized Benchmark for Linguistic Code-switching Evaluation**Gustavo Aguilar, Sudipta Kar, Thamar Solorio*2020 · 96 citations*](https://md.research.elamur.ai/free/en/papers/aguilar-2020-lince-centralized-benchmark-linguistic-code/)
779. [**SemDeDup: Data-efficient learning at web-scale through semantic deduplication**Amro Abbas, Kushal Tirumala, Dániel Simig, et al.*2023 · 94 citations*](https://md.research.elamur.ai/free/en/papers/abbas-2023-semdedup-data-efficient-learning-web/)
780. [**A Unified Linear-Time Framework for Sentence-Level Discourse Parsing**Xiang Lin, Shafiq Joty, Prathyusha Jwalapuram, et al.*2019 · 94 citations*](https://md.research.elamur.ai/free/en/papers/lin-2019-unified-linear-time-framework-sentence/)
781. [**SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning**Roshanak Mirzaee, Hossein Rajaby Faghihi, Qiang Ning, et al.*2021 · 92 citations*](https://md.research.elamur.ai/free/en/papers/mirzaee-2021-spartqa-textual-question-answering-benchmark/)
782. [**The NiuTrans Machine Translation Systems for WMT19**Bei Li, Yinqiao Li, Chen Xu, et al.*2019 · 92 citations*](https://md.research.elamur.ai/free/en/papers/li-2019-niutrans-machine-translation-systems-wmt19/)
783. [**Prompsit's submission to WMT 2018 Parallel Corpus Filtering shared task**Víctor M. Sánchez-Cartagena, Marta Bañón, Sergio Ortiz-Rojas, et al.*2018 · 92 citations*](https://md.research.elamur.ai/free/en/papers/cartagena-2018-prompsit-s-submission-wmt-2018/)
784. [**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/)
785. [**BabyBERTa: Learning More Grammar With Small-Scale Child-Directed Language**Philip A. Huebner, Elior Sulem, Fisher Cynthia, et al.*2021 · 91 citations*](https://md.research.elamur.ai/free/en/papers/huebner-2021-babyberta-learning-more-grammar-small/)
786. [**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/)
787. [**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/)
788. [**BlonDe: An Automatic Evaluation Metric for Document-level Machine Translation**Yuchen Jiang, Tianyu Liu, Shuming Ma, et al.*2022 · 85 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2022-blonde-automatic-evaluation-metric-document/)
789. [**Coreference-Aware Dialogue Summarization**Zhengyuan Liu, Ke Shi, Nancy Chen*2021 · 81 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-coreference-aware-dialogue-summarization/)
790. [**Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2023 · 79 citations*](https://md.research.elamur.ai/free/en/papers/tay-2023-scaling-laws-vs-model-architectures/)
791. [**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/)
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