---
title: "Who cites Tolga Bolukbasi — 4,232 papers of our library"
description: "4,232 papers of the Elamur Research library cite the works of Tolga Bolukbasi, found in their bibliographies · page 1 of 11 · 1–100; the most…"
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---
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# Who cites Tolga Bolukbasi

4,441 citations of their works from 4,232 papers of our library (of the 149,439 whose bibliographies we read) · 1,076 with a page here, the most cited first · page 1 of 11 · 1–100 · [← Tolga Bolukbasi](https://md.research.elamur.ai/free/en/authors/tolga-bolukbasi/)

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1. [**GPT-4 Technical Report arXiv:2303.08774**OpenAI, Josh Achiam, Steven Adler, et al.*2023 · 13,036 citations*](https://md.research.elamur.ai/free/en/papers/openai-2023-gpt-4-technical-report/)
2. [**Learning Transferable Visual Models From Natural Language Supervision arXiv:2103.00020**Alec Radford, Jong Wook Kim, Chris Hallacy, et al.*2021 · 8,767 citations*](https://md.research.elamur.ai/free/en/papers/radford-2021-learning-transferable-visual-models-natural/)
3. [**The Llama 3 Herd of Models arXiv:2407.21783**Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.*2024 · 7,682 citations*](https://md.research.elamur.ai/free/en/papers/grattafiori-2024-llama-3-herd-models/)
4. **[A Survey on Bias and Fairness in Machine Learning](https://md.research.elamur.ai/free/en/papers/mehrabi-2019-survey-bias-fairness-machine-learning/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Ninareh Mehrabi, Fred Morstatter, Nripsuta Saxena, et al.*2019 · 5,638 citations*
5. **[A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-hallucination-large-language-models/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Lei Huang, Weijiang Yu, Weitao Ma, et al.*2023 · 3,231 citations*
6. [**Sparks of Artificial General Intelligence: Early experiments with GPT-4 arXiv:2303.12712**Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, et al.*2023 · 2,439 citations*](https://md.research.elamur.ai/free/en/papers/bubeck-2023-sparks-artificial-general-intelligence-early/)
7. [**DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models arXiv:2402.03300**Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.*2024 · 2,115 citations*](https://md.research.elamur.ai/free/en/papers/shao-2024-deepseekmath-pushing-limits-mathematical-reasoning/)
8. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
9. **[Language (Technology) is Power: A Critical Survey of “Bias” in NLP](https://md.research.elamur.ai/free/en/papers/blodgett-2020-language-technology-is-power-critical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Su Lin Blodgett, Solon Barocas, Hal Daumé III, et al.*2020 · 1,716 citations*
10. [**Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context arXiv:2403.05530**Gemini Team, Petko Georgiev, Ving Ian Lei, et al.*2024 · 1,589 citations*](https://md.research.elamur.ai/free/en/papers/gemini-team-2024-gemini-1-5-unlocking-multimodal/)
11. [**LaMDA: Language Models for Dialog Applications arXiv:2201.08239**Romal Thoppilan, Daniel De Freitas, Jamie Hall, et al.*2022 · 1,344 citations*](https://md.research.elamur.ai/free/en/papers/thoppilan-2022-lamda-language-models-dialog-applications/)
12. **[A Comprehensive Overview of Large Language Models](https://md.research.elamur.ai/free/en/papers/naveed-2023-comprehensive-overview-large-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Humza Naveed, Asad Ullah Khan, Shi Qiu, et al.*2023 · 1,287 citations*
13. **[The Rise and Potential of Large Language Model Based Agents: A Survey](https://md.research.elamur.ai/free/en/papers/xi-2023-rise-potential-large-language/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhiheng Xi, Wenxiang Chen, Xin Guo, et al.*2023 · 1,272 citations*
14. **[Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods](https://md.research.elamur.ai/free/en/papers/zhao-2018-gender-bias-coreference-resolution-evaluation/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jieyu Zhao, Tianlu Wang, Mark Yatskar, et al.*2018 · 1,202 citations*
15. **[StereoSet: Measuring stereotypical bias in pretrained language models](https://md.research.elamur.ai/free/en/papers/nadeem-2021-stereoset-measuring-stereotypical-bias-pretrained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Moin Nadeem, Anna Bethke, Siva Reddy*2021 · 1,141 citations*
16. [**Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone arXiv:2404.14219**Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.*2024 · 1,134 citations*](https://md.research.elamur.ai/free/en/papers/abdin-2024-phi-3-technical-report-highly/)
17. **[SemEval-2018 Task 1: Affect in Tweets](https://md.research.elamur.ai/free/en/papers/mohammad-2018-semeval-2018-task-1-affect/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Saif Mohammad, Felipe Bravo-Marquez, Mohammad Salameh, et al.*2018 · 1,094 citations*
18. **[Bias and Fairness in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/gallegos-2023-bias-fairness-large-language-models/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.*2023 · 1,082 citations*
19. **[Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints](https://md.research.elamur.ai/free/en/papers/zhao-2017-men-also-like-shopping-reducing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jieyu Zhao, Tianlu Wang, Mark Yatskar, et al.*2017 · 1,050 citations*
20. [**Qwen2.5-VL Technical Report arXiv:2502.13923**Shuai Bai, Keqin Chen, Xuejing Liu, et al.*2025 · 1,031 citations*](https://md.research.elamur.ai/free/en/papers/bai-2025-qwen2-5-vl-technical/)
21. **[MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI](https://md.research.elamur.ai/free/en/papers/yue-2023-mmmu-massive-multi-discipline-multimodal/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Xiang Yue, Yuansheng Ni, Kai Zhang, et al.*2023 · 1,005 citations*
22. [**Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities arXiv:2507.06261**Gheorghe Comanici, Eric Bieber, Mike Schaekermann, et al.*2025 · 974 citations*](https://md.research.elamur.ai/free/en/papers/comanici-2025-gemini-2-5-pushing-frontier/)
23. **[MMBench: Is Your Multi-modal Model an All-around Player?](https://md.research.elamur.ai/free/en/papers/liu-2023-mmbench-multi-modal-model-all/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yuan Liu, Haodong Duan, Yuanhan Zhang, et al.*2023 · 942 citations*
24. **[Gender Bias in Coreference Resolution](https://md.research.elamur.ai/free/en/papers/rudinger-2018-gender-bias-coreference-resolution/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Rachel Rudinger, Jason Naradowsky, Brian Leonard, et al.*2018 · 864 citations*
25. [**Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution arXiv:2409.12191**Peng Wang, Shuai Bai, Sinan Tan, et al.*2024 · 860 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-qwen2-vl-enhancing-vision/)
26. **[On Measuring Social Biases in Sentence Encoders](https://md.research.elamur.ai/free/en/papers/may-2019-measuring-social-biases-sentence-encoders/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chandler May, Alex Wang, Shikha Bordia, et al.*2019 · 769 citations*
27. **[The Woman Worked as a Babysitter: On Biases in Language Generation](https://md.research.elamur.ai/free/en/papers/sheng-2019-woman-worked-as-babysitter-biases/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, et al.*2019 · 764 citations*
28. **[MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark](https://md.research.elamur.ai/free/en/papers/wang-2024-mmlu-pro-more-robust-challenging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yubo Wang, Xueguang Ma, Ge Zhang, et al.*2024 · 761 citations*
29. **[SGLang: Efficient Execution of Structured Language Model Programs](https://md.research.elamur.ai/free/en/papers/zheng-2023-sglang-efficient-execution-structured-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, et al.*2023 · 729 citations*
30. **[Mitigating Gender Bias in Natural Language Processing: Literature Review](https://md.research.elamur.ai/free/en/papers/sun-2019-mitigating-gender-bias-natural-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tony Sun, Andrew Gaut, Shirlyn Tang, et al.*2019 · 724 citations*
31. **[Red Teaming Language Models with Language Models](https://md.research.elamur.ai/free/en/papers/perez-2022-red-teaming-language-models-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ethan Perez, Saffron Huang, Francis Song, et al.*2022 · 700 citations*
32. [**ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools arXiv:2406.12793**Team GLM, Aohan Zeng, Bin Xu, et al.*2024 · 691 citations*](https://md.research.elamur.ai/free/en/papers/glm-2024-chatglm-family-large-language-models/)
33. [**Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model arXiv:2201.11990**Shaden Smith, Mostofa Patwary, Brandon Norick, et al.*2022 · 615 citations*](https://md.research.elamur.ai/free/en/papers/smith-2022-using-deepspeed-megatron-train-megatron/)
34. **[Evaluating Gender Bias in Machine Translation](https://md.research.elamur.ai/free/en/papers/stanovsky-2019-evaluating-gender-bias-machine-translation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gabriel Stanovsky, Noah A. Smith, Luke Zettlemoyer*2019 · 593 citations*
35. **[Measuring Bias in Contextualized Word Representations](https://md.research.elamur.ai/free/en/papers/kurita-2019-measuring-bias-contextualized-word-representations/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Keita Kurita, Nidhi Vyas, Ayush Pareek, et al.*2019 · 590 citations*
36. **[Racial Bias in Hate Speech and Abusive Language Detection Datasets](https://md.research.elamur.ai/free/en/papers/davidson-2019-racial-bias-hate-speech-abusive/) [Workshop on Abusive Language Online](https://md.research.elamur.ai/free/en/venues/workshop-on-abusive-language-online/)**Thomas Davidson, Debasmita Bhattacharya, Ingmar Weber*2019 · 583 citations*
37. **[Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems](https://md.research.elamur.ai/free/en/papers/kiritchenko-2018-examining-gender-race-bias-two/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Svetlana Kiritchenko, Saif Mohammad*2018 · 579 citations*
38. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
39. [**Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters arXiv:2408.03314**Charlie Snell, Jaehoon Lee, Kelvin Xu, et al.*2024 · 567 citations*](https://md.research.elamur.ai/free/en/papers/snell-2024-scaling-llm-test-time-compute/)
40. [**Jailbreaking Black Box Large Language Models in Twenty Queries arXiv:2310.08419**Patrick Chao, Alexander Robey, Edgar Dobriban, et al.*2023 · 553 citations*](https://md.research.elamur.ai/free/en/papers/chao-2023-jailbreaking-black-box-large-language/)
41. [**Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference arXiv:2403.04132**Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, et al.*2024 · 546 citations*](https://md.research.elamur.ai/free/en/papers/chiang-2024-chatbot-arena-open-platform-evaluating/)
42. **[How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites](https://md.research.elamur.ai/free/en/papers/chen-2024-far-gpt-4v-closing/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Zhe Chen, Weiyun Wang, Hao Tian, et al.*2024 · 541 citations*
43. [**Unleashing the potential of prompt engineering for large language models arXiv:2310.14735 · Patterns 6(6) 101,260 (2025)**Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.*2023 · 536 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-unleashing-potential-prompt-engineering-large/)
44. **[Learning Gender-Neutral Word Embeddings](https://md.research.elamur.ai/free/en/papers/zhao-2018-learning-gender-neutral-word-embeddings/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jieyu Zhao, Yichao Zhou, Zeyu Li, et al.*2018 · 520 citations*
45. **[Gender Bias in Contextualized Word Embeddings](https://md.research.elamur.ai/free/en/papers/zhao-2019-gender-bias-contextualized-word-embeddings/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jieyu Zhao, Tianlu Wang, Mark Yatskar, et al.*2019 · 508 citations*
46. [**GLaM: Efficient Scaling of Language Models with Mixture-of-Experts arXiv:2112.06905**Nan Du, Yanping Huang, Andrew M. Dai, et al.*2021 · 496 citations*](https://md.research.elamur.ai/free/en/papers/du-2021-glam-efficient-scaling-language-models/)
47. **[Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection](https://md.research.elamur.ai/free/en/papers/ravfogel-2020-null-it-out-guarding-protected/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shauli Ravfogel, Yanai Elazar, Hila Gonen, et al.*2020 · 488 citations*
48. [**LLaVA-OneVision: Easy Visual Task Transfer arXiv:2408.03326**Bo Li, Yuanhan Zhang, Dong Guo, et al.*2024 · 477 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-onevision-easy-visual-task/)
49. [**Cultural Bias and Cultural Alignment of Large Language Models arXiv:2311.14096 · PNAS Nexus, Volume 3, Issue 9, September 2024, pgae346**Yan Tao, Olga Viberg, Ryan S. Baker, et al.*2023 · 470 citations*](https://md.research.elamur.ai/free/en/papers/tao-2023-cultural-bias-cultural-alignment-large/)
50. **[Reducing Gender Bias in Abusive Language Detection](https://md.research.elamur.ai/free/en/papers/park-2018-reducing-gender-bias-abusive-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ji Ho Park, Jamin Shin, Pascale Fung*2018 · 470 citations*
51. [**MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts arXiv:2310.02255**Pan Lu, Hritik Bansal, Tony Xia, et al.*2023 · 468 citations*](https://md.research.elamur.ai/free/en/papers/lu-2023-mathvista-evaluating-mathematical-reasoning-foundation/)
52. **[OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems](https://md.research.elamur.ai/free/en/papers/he-2024-olympiadbench-challenging-benchmark-promoting-agi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaoqun He, Renjie Luo, Yuzhuo Bai, et al.*2024 · 456 citations*
53. **[GeDi: Generative Discriminator Guided Sequence Generation](https://md.research.elamur.ai/free/en/papers/krause-2021-gedi-generative-discriminator-guided-sequence/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ben Krause, Akhilesh Deepak Gotmare, Bryan McCann, et al.*2021 · 449 citations*
54. [**FinGPT: Open-Source Financial Large Language Models arXiv:2306.06031**Hongyang Yang, Xiao-Yang Liu, Christina Dan Wang*2023 · 445 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-fingpt-open-source-financial-large/)
55. [**Kimi k1.5: Scaling Reinforcement Learning with LLMs arXiv:2501.12599**Kimi Team, Angang Du, Bofei Gao, et al.*2025 · 431 citations*](https://md.research.elamur.ai/free/en/papers/kimi-team-2025-kimi-k1-5-scaling-reinforcement/)
56. **[Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis](https://md.research.elamur.ai/free/en/papers/fu-2024-video-mme-first-ever-comprehensive/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Chaoyou Fu, Yuhan Dai, Yongdong Luo, et al.*2024 · 427 citations*
57. [**Tulu 3: Pushing Frontiers in Open Language Model Post-Training arXiv:2411.15124**Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.*2024 · 423 citations*](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/)
58. **[Lipstick on a Pig: Debiasing Methods Cover up Systematic Gender Biases in Word Embeddings But do not Remove Them](https://md.research.elamur.ai/free/en/papers/gonen-2019-lipstick-pig-debiasing-methods-cover/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hila Gonen, Yoav Goldberg*2019 · 416 citations*
59. **[BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 409 citations*
60. [**Yi: Open Foundation Models by 01.AI arXiv:2403.04652**Alex Young, Bei Chen, Chao Li, et al.*2024 · 408 citations*](https://md.research.elamur.ai/free/en/papers/ai-2024-yi-open-foundation-models-01/)
61. **[Social Biases in NLP Models as Barriers for Persons with Disabilities](https://md.research.elamur.ai/free/en/papers/hutchinson-2020-social-biases-nlp-models-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, et al.*2020 · 404 citations*
62. [**RULER: What's the Real Context Size of Your Long-Context Language Models? arXiv:2404.06654**Cheng-Ping Hsieh, Simeng Sun, Samuel Kriman, et al.*2024 · 400 citations*](https://md.research.elamur.ai/free/en/papers/hsieh-2024-ruler-s-real-context-size/)
63. [**Representation Engineering: A Top-Down Approach to AI Transparency arXiv:2310.01405**Andy Zou, Long Phan, Sarah Chen, et al.*2023 · 397 citations*](https://md.research.elamur.ai/free/en/papers/zou-2023-representation-engineering-top-down-approach/)
64. **[Gender Bias in Neural Natural Language Processing](https://md.research.elamur.ai/free/en/papers/lu-2018-gender-bias-neural-natural-language/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Kaiji Lu, Piotr Mardziel, Fangjing Wu, et al.*2018 · 397 citations*
65. **[German's Next Language Model](https://md.research.elamur.ai/free/en/papers/chan-2020-german-s-next-language-model/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Branden Chan, Stefan Schweter, Timo Möller*2020 · 385 citations*
66. **[VILA: On Pre-training for Visual Language Models](https://md.research.elamur.ai/free/en/papers/lin-2023-vila-pre-training-visual-language/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Ji Lin, Hongxu Yin, Wei Ping, et al.*2023 · 381 citations*
67. **[Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology](https://md.research.elamur.ai/free/en/papers/zmigrod-2019-counterfactual-data-augmentation-mitigating-gender/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ran Zmigrod, Sabrina J. Mielke, Hanna Wallach, et al.*2019 · 376 citations*
68. **[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*
69. [**The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery arXiv:2408.06292**Chris Lu, Cong Lu, Robert Tjarko Lange, et al.*2024 · 372 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-ai-scientist-fully-automated/)
70. [**WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct arXiv:2308.09583**Haipeng Luo, Qingfeng Sun, Can Xu, et al.*2023 · 372 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-wizardmath-empowering-mathematical-reasoning-large/)
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