--- title: "Who cites Investigating Prior Knowledge for — 64 citing papers" description: "64 papers of the Elamur Research library cite «Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension»…" canonical: "https://research.elamur.ai/free/en/papers/sun-2019-investigating-prior-knowledge-challenging/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/sun-2019-investigating-prior-knowledge-challenging/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Investigating Prior Knowledge for Challenging…](https://md.research.elamur.ai/free/en/papers/sun-2019-investigating-prior-knowledge-challenging/) / cited by # Who cites «Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension» 64 papers of our library cite it (of the 141,840 whose bibliographies we read) · 13 with a page here, the most cited first · [← back to «Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension»](https://md.research.elamur.ai/free/en/papers/sun-2019-investigating-prior-knowledge-challenging/) 1. **[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 · 1,286 citations* 2. [**Crosslingual Generalization through Multitask Finetuning arXiv:2211.01786**Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.*2022 · 695 citations*](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-crosslingual-generalization-through-multitask-finetuning/) 3. [**What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams arXiv:2009.13081**Di Jin, Eileen Pan, Nassim Oufattole, et al.*2020 · 546 citations*](https://md.research.elamur.ai/free/en/papers/jin-2020-disease-this-patient-have-large/) 4. **[PPT: Pre-trained Prompt Tuning for Few-shot Learning](https://md.research.elamur.ai/free/en/papers/gu-2022-ppt-pre-trained-prompt-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxian Gu, Xu Han, Zhiyuan Liu, et al.*2022 · 469 citations* 5. [**ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation arXiv:2107.02137**Yu Sun, Shuohuan Wang, Shikun Feng, et al.*2021 · 328 citations*](https://md.research.elamur.ai/free/en/papers/sun-2021-ernie-3-0-large/) 6. [**InternLM2 Technical Report arXiv:2403.17297**Zheng Cai, Maosong Cao, Haojiong Chen, et al.*2024 · 299 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-internlm2-technical-report/) 7. [**Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling arXiv:2412.05271**Zhe Chen, Weiyun Wang, Yue Cao, et al.*2024 · 276 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-expanding-performance-boundaries-open/) 8. [**InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models arXiv:2504.10479**Jinguo Zhu, Weiyun Wang, Zhe Chen, et al.*2025 · 195 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-internvl3-exploring-advanced-training/) 9. [**ShortGPT: Layers in Large Language Models are More Redundant Than You Expect arXiv:2403.03853**Xin Men, Mingyu Xu, Qingyu Zhang, et al.*2024 · 167 citations*](https://md.research.elamur.ai/free/en/papers/men-2024-shortgpt-layers-large-language-models/) 10. [**InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency arXiv:2508.18265**Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.*2025 · 159 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-internvl3-5-advancing-open/) 11. [**Lawyer LLaMA Technical Report arXiv:2305.15062**Quzhe Huang, Mingxu Tao, Chen Zhang, et al.*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-lawyer-llama-technical-report/) 12. [**FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every Language arXiv:2506.20920**Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.*2025 · 97 citations*](https://md.research.elamur.ai/free/en/papers/penedo-2025-fineweb2-one-pipeline-scale-them/) 13. **[SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2024-seaeval-multilingual-foundation-models-cross/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Zhengyuan Liu, Xin Huang, et al.*2024 · 85 citations* 51 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/sun-2019-investigating-prior-knowledge-challenging/) — Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension