--- title: "Who cites Nitish Joshi — 174 papers of our library" description: "174 papers of the Elamur Research library cite the works of Nitish Joshi, found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/authors/nitish-joshi/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/nitish-joshi/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Nitish Joshi](https://md.research.elamur.ai/free/en/authors/nitish-joshi/) / cited by # Who cites Nitish Joshi 174 citations of their works from 174 papers of our library (of the 141,840 whose bibliographies we read) · 20 with a page here, the most cited first · [← Nitish Joshi](https://md.research.elamur.ai/free/en/authors/nitish-joshi/) 1. **[A Survey on Evaluation of Large Language Models](https://md.research.elamur.ai/free/en/papers/chang-2023-survey-evaluation-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/)**Yupeng Chang, Xu Wang, Jindong Wang, et al.*2023 · 3,641 citations* 2. [**Retrieval-Augmented Generation for Large Language Models: A Survey arXiv:2312.10997**Yunfan Gao, Yun Xiong, Xinyu Gao, et al.*2023 · 1,648 citations*](https://md.research.elamur.ai/free/en/papers/gao-2023-retrieval-augmented-generation-large-language/) 3. [**GPQA: A Graduate-Level Google-Proof Q&A Benchmark arXiv:2311.12022**David Rein, Betty Li Hou, Asa Cooper Stickland, et al.*2023 · 964 citations*](https://md.research.elamur.ai/free/en/papers/rein-2023-gpqa-graduate-level-google-proof/) 4. [**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/) 5. [**UL2: Unifying Language Learning Paradigms arXiv:2205.05131**Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.*2022 · 335 citations*](https://md.research.elamur.ai/free/en/papers/tay-2022-ul2-unifying-language-learning-paradigms/) 6. **[TRUE: Re-evaluating Factual Consistency Evaluation](https://md.research.elamur.ai/free/en/papers/honovich-2022-true-re-evaluating-factual-consistency/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Or Honovich, Roee Aharoni, Jonathan Herzig, et al.*2022 · 276 citations* 7. [**Teaching language models to support answers with verified quotes arXiv:2203.11147**Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.*2022 · 213 citations*](https://md.research.elamur.ai/free/en/papers/menick-2022-teaching-language-models-support-answers/) 8. [**RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval arXiv:2401.18059**Parth Sarthi, Salman Abdullah, Aditi Tuli, et al.*2024 · 191 citations*](https://md.research.elamur.ai/free/en/papers/sarthi-2024-raptor-recursive-abstractive-processing-tree/) 9. [**Effective Long-Context Scaling of Foundation Models arXiv:2309.16039**Wenhan Xiong, Jingyu Liu, Igor Molybog, et al.*2023 · 177 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-effective-long-context-scaling-foundation/) 10. **[LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers](https://md.research.elamur.ai/free/en/papers/olausson-2023-linc-neurosymbolic-approach-logical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.*2023 · 171 citations* 11. [**L-Eval: Instituting Standardized Evaluation for Long Context Language Models arXiv:2307.11088**Chenxin An, Shansan Gong, Ming Zhong, et al.*2023 · 160 citations*](https://md.research.elamur.ai/free/en/papers/an-2023-l-eval-instituting-standardized-evaluation/) 12. [**LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks arXiv:2412.15204**Yushi Bai, Shangqing Tu, Jiajie Zhang, et al.*2024 · 130 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-longbench-v2-deeper-understanding/) 13. [**Retrieval meets Long Context Large Language Models arXiv:2310.03025**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/) 14. **[ZeroSCROLLS: A Zero-Shot Benchmark for Long Text Understanding](https://md.research.elamur.ai/free/en/papers/shaham-2023-zeroscrolls-zero-shot-benchmark-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Uri Shaham, Maor Ivgi, Avia Efrat, et al.*2023 · 129 citations* 15. **[Efficient Long-Text Understanding with Short-Text Models](https://md.research.elamur.ai/free/en/papers/ivgi-2023-efficient-long-text-understanding-short/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Maor Ivgi, Uri Shaham, Jonathan Berant*2023 · 93 citations* 16. [**A Comprehensive Survey on Long Context Language Modeling arXiv:2503.17407**Jiaheng Liu, Dawei Zhu, Zhiqi Bai, et al.*2025 · 64 citations*](https://md.research.elamur.ai/free/en/papers/liu-2025-comprehensive-survey-long-context-language/) 17. **[BAMBOO: A Comprehensive Benchmark for Evaluating Long Text Modeling Capacities of Large Language Models](https://md.research.elamur.ai/free/en/papers/dong-2024-bamboo-comprehensive-benchmark-evaluating-long/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zican Dong, Tianyi Tang, Junyi Li, et al.*2024 · 59 citations* 18. [**Scaling Laws of RoPE-based Extrapolation arXiv:2310.05209**Xiaoran Liu, Hang Yan, Shuo Zhang, et al.*2023 · 53 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-scaling-laws-rope-based/) 19. **[OG-RAG: Ontology-grounded retrieval-augmented generation for large language models](https://md.research.elamur.ai/free/en/papers/sharma-2025-og-rag-ontology-grounded-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kartik Sharma, Peeyush Kumar, Yunqing Li*2025 · 37 citations* 20. **[KCIF: Knowledge-Conditioned Instruction Following](https://md.research.elamur.ai/free/en/papers/murthy-2026-kcif-knowledge-conditioned-instruction-following/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Rudra Murthy, Praveen Venkateswaran, Prince Kumar, et al.*2026 · 2 citations* 154 more citing papers of our library have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/authors/nitish-joshi/) — Nitish Joshi