---
title: "Who cites Lior Wolf — 437 papers of our library"
description: "437 papers of the Elamur Research library cite the works of Lior Wolf, found in their bibliographies; the most cited first."
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---
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# Who cites Lior Wolf

440 citations of their works from 437 papers of our library (of the 149,439 whose bibliographies we read) · 67 with a page here, the most cited first · [← Lior Wolf](https://md.research.elamur.ai/free/en/authors/lior-wolf/)

1. [**Attention Is All You Need arXiv:1706.03762**Ashish Vaswani, Noam Shazeer, Niki Parmar, et al.*2017 · 17,458 citations*](https://md.research.elamur.ai/free/en/papers/vaswani-2017-attention-all-need/)
2. [**Neural Architecture Search with Reinforcement Learning arXiv:1611.01578**Barret Zoph, Quoc V. Le*2016 · 4,413 citations*](https://md.research.elamur.ai/free/en/papers/zoph-2016-neural-architecture-search-reinforcement-learning/)
3. **[SpanBERT: Improving Pre-training by Representing and Predicting Spans](https://md.research.elamur.ai/free/en/papers/joshi-2019-spanbert-improving-pre-training-representing/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Mandar Joshi, Danqi Chen, Yinhan Liu, et al.*2019 · 2,616 citations*
4. [**Robust Speech Recognition via Large-Scale Weak Supervision arXiv:2212.04356**Alec Radford, Jong Wook Kim, Tao Xu, et al.*2022 · 2,546 citations*](https://md.research.elamur.ai/free/en/papers/radford-2022-robust-speech-recognition-large-scale/)
5. [**A Deep Reinforced Model for Abstractive Summarization arXiv:1705.04304**Romain Paulus, Caiming Xiong, Richard Socher*2017 · 1,657 citations*](https://md.research.elamur.ai/free/en/papers/paulus-2017-deep-reinforced-model-abstractive-summarization/)
6. [**CTRL: A Conditional Transformer Language Model for Controllable Generation arXiv:1909.05858**Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney, et al.*2019 · 1,291 citations*](https://md.research.elamur.ai/free/en/papers/keskar-2019-ctrl-conditional-transformer-language-model/)
7. **[Fast Abstractive Summarization with Reinforce-Selected Sentence Rewriting](https://md.research.elamur.ai/free/en/papers/chen-2018-fast-abstractive-summarization-reinforce-selected/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yen-Chun Chen, Mohit Bansal*2018 · 826 citations*
8. [**Regularizing and Optimizing LSTM Language Models arXiv:1708.02182**Stephen Merity, Nitish Shirish Keskar, Richard Socher*2017 · 633 citations*](https://md.research.elamur.ai/free/en/papers/merity-2017-regularizing-optimizing-lstm-language-models/)
9. [**An efficient framework for learning sentence representations arXiv:1803.02893**Lajanugen Logeswaran, Honglak Lee*2018 · 577 citations*](https://md.research.elamur.ai/free/en/papers/logeswaran-2018-efficient-framework-learning-sentence-representations/)
10. [**Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time arXiv:2203.05482**Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, et al.*2022 · 507 citations*](https://md.research.elamur.ai/free/en/papers/wortsman-2022-model-soups-averaging-weights-multiple/)
11. [**Marian: Fast Neural Machine Translation in C++ arXiv:1804.00344**Marcin Junczys-Dowmunt, Roman Grundkiewicz, Tomasz Dwojak, et al.*2018 · 507 citations*](https://md.research.elamur.ai/free/en/papers/junczys-dowmunt-2018-marian-fast-neural-machine-translation/)
12. [**Regularizing Neural Networks by Penalizing Confident Output Distributions arXiv:1701.06548**Gabriel Pereyra, George Tucker, Jan Chorowski, et al.*2017 · 496 citations*](https://md.research.elamur.ai/free/en/papers/pereyra-2017-regularizing-neural-networks-penalizing-confident/)
13. [**SimVLM: Simple Visual Language Model Pretraining with Weak Supervision arXiv:2108.10904**Zirui Wang, Jiahui Yu, Adams Wei Yu, et al.*2021 · 481 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-simvlm-simple-visual-language-model/)
14. **[Are All Languages Created Equal in Multilingual BERT?](https://md.research.elamur.ai/free/en/papers/wu-2020-are-all-languages-created-equal/) [Workshop on Representation Learning for NLP](https://md.research.elamur.ai/free/en/venues/repl4nlp/)**Shijie Wu, Mark Dredze*2020 · 460 citations*
15. [**The Falcon Series of Open Language Models arXiv:2311.16867**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 443 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
16. [**Pay Less Attention with Lightweight and Dynamic Convolutions arXiv:1901.10430**Felix Wu, Angela Fan, Alexei Baevski, et al.*2019 · 437 citations*](https://md.research.elamur.ai/free/en/papers/wu-2019-pay-less-attention-lightweight-dynamic/)
17. [**Tying Word Vectors and Word Classifiers: A Loss Framework for Language Modeling arXiv:1611.01462**Hakan Inan, Khashayar Khosravi, Richard Socher*2016 · 414 citations*](https://md.research.elamur.ai/free/en/papers/inan-2016-tying-word-vectors-word-classifiers/)
18. **[Sharp Nearby, Fuzzy Far Away: How Neural Language Models Use Context](https://md.research.elamur.ai/free/en/papers/khandelwal-2018-sharp-nearby-fuzzy-far-away/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Urvashi Khandelwal, He He, Peng Qi, et al.*2018 · 399 citations*
19. **[Emerging Cross-lingual Structure in Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/conneau-2020-emerging-cross-lingual-structure-pretrained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alexis Conneau, Shijie Wu, Haoran Li, et al.*2020 · 382 citations*
20. **[JW300: A Wide-Coverage Parallel Corpus for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/agic-2019-jw300-wide-coverage-parallel-corpus/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Željko Agić, Ivan Vulić*2019 · 374 citations*
21. **[Unsupervised Domain Clusters in Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/aharoni-2020-unsupervised-domain-clusters-pretrained-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Roee Aharoni, Yoav Goldberg*2020 · 330 citations*
22. [**ALFWorld: Aligning Text and Embodied Environments for Interactive Learning arXiv:2010.03768**Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, et al.*2020 · 322 citations*](https://md.research.elamur.ai/free/en/papers/shridhar-2020-alfworld-aligning-text-embodied-environments/)
23. **[Cross-Lingual Alignment of Contextual Word Embeddings, with Applications to Zero-shot Dependency Parsing](https://md.research.elamur.ai/free/en/papers/schuster-2019-cross-lingual-alignment-contextual-word/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tal Schuster, Ori Ram, Regina Barzilay, et al.*2019 · 298 citations*
24. [**Cloze-driven Pretraining of Self-attention Networks arXiv:1903.07785**Alexei Baevski, Sergey Edunov, Yinhan Liu, et al.*2019 · 286 citations*](https://md.research.elamur.ai/free/en/papers/baevski-2019-cloze-driven-pretraining-self-attention/)
25. [**Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering arXiv:1911.10470**Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, et al.*2019 · 280 citations*](https://md.research.elamur.ai/free/en/papers/asai-2019-learning-retrieve-reasoning-paths-over/)
26. **[The Importance of Being Recurrent for Modeling Hierarchical Structure](https://md.research.elamur.ai/free/en/papers/tran-2018-importance-being-recurrent-modeling-hierarchical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ke Tran, Arianna Bisazza, Christof Monz*2018 · 228 citations*
27. **[MTNT: A Testbed for Machine Translation of Noisy Text](https://md.research.elamur.ai/free/en/papers/michel-2018-mtnt-testbed-machine-translation-noisy/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Paul Michel, Graham Neubig*2018 · 227 citations*
28. **[Probing the Need for Visual Context in Multimodal Machine Translation](https://md.research.elamur.ai/free/en/papers/caglayan-2019-probing-need-visual-context-multimodal/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ozan Caglayan, Pranava Madhyastha, Lucia Specia, et al.*2019 · 217 citations*
29. **[Nematus: a Toolkit for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/sennrich-2017-nematus-toolkit-neural-machine-translation/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Rico Sennrich, Orhan Firat, Kyunghyun Cho, et al.*2017 · 206 citations*
30. **[Compound Probabilistic Context-Free Grammars for Grammar Induction](https://md.research.elamur.ai/free/en/papers/kim-2019-compound-probabilistic-context-free-grammars/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yoon Kim, Chris Dyer, Alexander Rush*2019 · 201 citations*
31. **[Jointly Learning to Align and Translate with Transformer Models](https://md.research.elamur.ai/free/en/papers/garg-2019-jointly-learning-align-translate-transformer/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sarthak Garg, Stephan Peitz, Udhyakumar Nallasamy, et al.*2019 · 199 citations*
32. [**Transformers without Tears: Improving the Normalization of Self-Attention arXiv:1910.05895**Toan Q. Nguyen, Julian Salazar*2019 · 189 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2019-transformers-tears-improving-normalization-self/)
33. [**Representation Degeneration Problem in Training Natural Language Generation Models arXiv:1907.12009**Jun Gao, Di He, Xu Tan, et al.*2019 · 181 citations*](https://md.research.elamur.ai/free/en/papers/gao-2019-representation-degeneration-problem-training-natural/)
34. [**Adaptive Input Representations for Neural Language Modeling arXiv:1809.10853**Alexei Baevski, Michael Auli*2018 · 177 citations*](https://md.research.elamur.ai/free/en/papers/baevski-2018-adaptive-input-representations-neural-language/)
35. [**Order-Embeddings of Images and Language arXiv:1511.06361**Ivan Vendrov, Ryan Kiros, Sanja Fidler, et al.*2015 · 177 citations*](https://md.research.elamur.ai/free/en/papers/vendrov-2015-order-embeddings-images-language/)
36. **[Unsupervised Opinion Summarization as Copycat-Review Generation](https://md.research.elamur.ai/free/en/papers/brazinskas-2020-unsupervised-opinion-summarization-as-copycat/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arthur Bražinskas, Mirella Lapata, Ivan Titov*2020 · 173 citations*
37. **[Extreme Adaptation for Personalized Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/michel-2018-extreme-adaptation-personalized-neural-machine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Paul Michel, Graham Neubig*2018 · 161 citations*
38. [**Jamba: A Hybrid Transformer-Mamba Language Model arXiv:2403.19887**Opher Lieber, Barak Lenz, Hofit Bata, et al.*2024 · 159 citations*](https://md.research.elamur.ai/free/en/papers/lieber-2024-jamba-hybrid-transformer-mamba-language/)
39. **[Norm-Based Curriculum Learning for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/liu-2020-norm-based-curriculum-learning-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuebo Liu, Houtim Lai, Derek F. Wong, et al.*2020 · 158 citations*
40. **[Do We Really Need Fully Unsupervised Cross-Lingual Embeddings?](https://md.research.elamur.ai/free/en/papers/vulic-2019-do-we-really-need-fully/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ivan Vulić, Goran Glavaš, Roi Reichart, et al.*2019 · 157 citations*
41. [**Recurrent Highway Networks arXiv:1607.03474**Julian Georg Zilly, Rupesh Kumar Srivastava, Jan Koutnik, et al.*2016 · 147 citations*](https://md.research.elamur.ai/free/en/papers/zilly-2016-recurrent-highway-networks/)
42. [**Rethinking embedding coupling in pre-trained language models arXiv:2010.12821**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/)
43. **[Representing Numbers in NLP: a Survey and a Vision](https://md.research.elamur.ai/free/en/papers/thawani-2021-representing-numbers-nlp-survey-vision/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Avijit Thawani, Jay Pujara, Filip Ilievski, et al.*2021 · 139 citations*
44. [**Deep Encoder, Shallow Decoder: Reevaluating Non-autoregressive Machine Translation arXiv:2006.10369**Jungo Kasai, Nikolaos Pappas, Hao Peng, et al.*2020 · 134 citations*](https://md.research.elamur.ai/free/en/papers/kasai-2020-deep-encoder-shallow-decoder-reevaluating/)
45. **[Analyzing Transformers in Embedding Space](https://md.research.elamur.ai/free/en/papers/dar-2023-analyzing-transformers-embedding-space/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guy Dar, Mor Geva, Ankit Gupta, et al.*2023 · 130 citations*
46. **[Document-level Neural MT: A Systematic Comparison](https://md.research.elamur.ai/free/en/papers/lopes-2020-document-level-neural-mt-systematic/) [Annual Conference of the European Association for Machine Translation (EAMT)](https://md.research.elamur.ai/free/en/venues/eamt/)**António Lopes, M. Amin Farajian, Rachel Bawden, et al.*2020 · 115 citations*
47. **[On the Relation between Linguistic Typology and (Limitations of) Multilingual Language Modeling](https://md.research.elamur.ai/free/en/papers/gerz-2018-relation-between-linguistic-typology-limitations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Daniela Gerz, Ivan Vulić, Edoardo Maria Ponti, et al.*2018 · 113 citations*
48. [**Linear Transformers Are Secretly Fast Weight Programmers arXiv:2102.11174**Imanol Schlag, Kazuki Irie, Jurgen Schmidhuber*2021 · 111 citations*](https://md.research.elamur.ai/free/en/papers/schlag-2021-linear-transformers-secretly-fast-weight/)
49. **[Multi-SimLex: A Large-Scale Evaluation of Multilingual and Crosslingual Lexical Semantic Similarity](https://md.research.elamur.ai/free/en/papers/vulic-2020-multi-simlex-large-scale-evaluation/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Ivan Vulić, Simon Baker, Edoardo Maria Ponti, et al.*2020 · 106 citations*
50. **[Findings of the WMT 2019 Shared Task on Automatic Post-Editing](https://md.research.elamur.ai/free/en/papers/chatterjee-2019-findings-wmt-2019-shared-task/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Rajen Chatterjee, Christian Federmann, Matteo Negri, et al.*2019 · 102 citations*
51. **[Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction](https://md.research.elamur.ai/free/en/papers/gerz-2018-language-modeling-morphologically-rich-languages/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Daniela Gerz, Ivan Vulić, Edoardo Ponti, et al.*2018 · 82 citations*
52. [**What Language Model to Train if You Have One Million GPU Hours? arXiv:2210.15424**Teven Le Scao, Thomas Wang, Daniel Hesslow, et al.*2022 · 73 citations*](https://md.research.elamur.ai/free/en/papers/scao-2022-language-model-train-if-have/)
53. [**A Primer on the Inner Workings of Transformer-based Language Models arXiv:2405.00208**Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/ferrando-2024-primer-inner-workings-transformer-based/)
54. **[Finding the Optimal Vocabulary Size for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gowda-2020-finding-optimal-vocabulary-size-neural/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Thamme Gowda, Jonathan May*2020 · 72 citations*
55. [**Lost in Evaluation: Misleading Benchmarks for Bilingual Dictionary Induction EMNLP-IJCNLP 2019 (Hong Kong)**Yova Kementchedjhieva, Mareike Hartmann, Anders Sgaard*2019 · 53 citations*](https://md.research.elamur.ai/free/en/papers/kementchedjhieva-2019-lost-in-evaluation/)
56. [**Hymba: A Hybrid-head Architecture for Small Language Models arXiv:2411.13676**Xin Dong, Yonggan Fu, Shizhe Diao, et al.*2024 · 50 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-hymba-hybrid-head-architecture-small/)
57. [**Language models scale reliably with over-training and on downstream tasks arXiv:2403.08540**Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/gadre-2024-language-models-scale-reliably-over/)
58. **[Coreference and Coherence in Neural Machine Translation: A Study Using Oracle Experiments](https://md.research.elamur.ai/free/en/papers/stojanovski-2018-coreference-coherence-neural-machine-translation/) [Conference on Machine Translation: Research Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-research-papers/)**Dario Stojanovski, Alexander Fraser*2018 · 46 citations*
59. **[Neural Lattice Language Models](https://md.research.elamur.ai/free/en/papers/buckman-2018-neural-lattice-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jacob Buckman, Graham Neubig*2018 · 35 citations*
60. [**Locating and Editing Factual Associations in Mamba arXiv:2404.03646**Arnab Sen Sharma, David Atkinson, David Bau*2024 · 18 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2024-locating-editing-factual-associations-mamba/)
61. **[Consonant is all you need: a compact representation of English text for efficient NLP](https://md.research.elamur.ai/free/en/papers/shaibani-2023-consonant-is-all-you-need/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Maged S. Al-shaibani, Irfan Ahmad*2023 · 6 citations*
62. **[Paramanu: Compact and Competitive Monolingual Language Models for Low-Resource Morphologically Rich Indian Languages](https://md.research.elamur.ai/free/en/papers/niyogi-2026-paramanu-compact-competitive-monolingual-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mitodru Niyogi, Eric Gaussier, Arnab Bhattacharya*2026 · 5 citations*
63. **[Dotless Arabic Text for Natural Language Processing](https://md.research.elamur.ai/free/en/papers/shaibani-2025-dotless-arabic-text-natural-language/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Maged S. Al-Shaibani, Irfan Ahmad*2025 · 3 citations*
64. [**Dotless Representation of Arabic Text: Analysis and Modeling arXiv:2312.16104**Maged S. Al-Shaibani, Irfan Ahmad*2023 · 1 citation*](https://md.research.elamur.ai/free/en/papers/al-shaibani-2023-dotless-representation-arabic-text-analysis/)
65. **[AYN: A Tiny Yet Competitive Indian Legal Language Model Pretrained from Scratch](https://md.research.elamur.ai/free/en/papers/niyogi-2026-ayn-tiny-yet-competitive-indian/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mitodru Niyogi, Eric Gaussier, Arnab Bhattacharya*2026*
66. **[Harnessing the Latent Space: From Steering Vectors to Model Calibrators for Control and Trust](https://md.research.elamur.ai/free/en/papers/subramani-2026-harnessing-latent-space-steering-vectors/) [Big Picture v2: Crafting a Research Narrative](https://md.research.elamur.ai/free/en/venues/bigpicture/)**Nishant Subramani*2026*
67. **[Weight Tying Biases Token Embeddings Towards the Output Space](https://md.research.elamur.ai/free/en/papers/lopardo-2026-weight-tying-biases-token-embeddings/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Antonio Lopardo, Avyukth Harish, Catherine Arnett, et al.*2026*

370 more citing papers of our library have no page here yet.

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