---
title: "Who cites Jun Gao — 201 papers of our library"
description: "201 papers of the Elamur Research library cite the works of Jun Gao, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/jun-gao/cited-by/"
---
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# Who cites Jun Gao

204 citations of their works from 201 papers of our library (of the 141,840 whose bibliographies we read) · 18 with a page here, the most cited first · [← Jun Gao](https://md.research.elamur.ai/free/en/authors/jun-gao/)

1. **[SimCSE: Simple Contrastive Learning of Sentence Embeddings](https://md.research.elamur.ai/free/en/papers/gao-2021-simcse-simple-contrastive-learning-sentence/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tianyu Gao, Xingcheng Yao, Danqi Chen*2021 · 3,922 citations*
2. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,863 citations*
3. [**Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models arXiv:2304.01852 · Meta-Radiology (2023)100,017**Yiheng Liu, Tianle Han, Siyuan Ma, et al.*2023 · 938 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-summary-chatgpt-related-research-perspective/)
4. **[On the Sentence Embeddings from Pre-trained Language Models](https://md.research.elamur.ai/free/en/papers/li-2020-sentence-embeddings-pre-trained-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bohan Li, Hao Zhou, Junxian He, et al.*2020 · 831 citations*
5. **[ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation Transfer](https://md.research.elamur.ai/free/en/papers/yan-2021-consert-contrastive-framework-self-supervised/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuanmeng Yan, Rumei Li, Sirui Wang, et al.*2021 · 648 citations*
6. **[Instruction Tuning for Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/zhang-2023-instruction-tuning-large-language-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Shengyu Zhang, Linfeng Dong, Xiaoya Li, et al.*2023 · 517 citations*
7. **[ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning](https://md.research.elamur.ai/free/en/papers/lai-2023-chatgpt-beyond-english-comprehensive-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Viet Dac Lai, Nghia Ngo, Amir Pouran Ben Veyseh, et al.*2023 · 421 citations*
8. [**Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference arXiv:2412.13663**Benjamin Warner, Antoine Chaffin, Benjamin Clavié, et al.*2024 · 355 citations*](https://md.research.elamur.ai/free/en/papers/warner-2024-smarter-better-faster-longer-modern/)
9. **[Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!](https://md.research.elamur.ai/free/en/papers/ma-2023-large-language-model-is-not/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yubo Ma, Yixin Cao, Yong Hong, et al.*2023 · 211 citations*
10. [**COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining arXiv:2102.08473**Yu Meng, Chenyan Xiong, Payal Bajaj, et al.*2021 · 196 citations*](https://md.research.elamur.ai/free/en/papers/meng-2021-coco-lm-correcting-contrasting-text/)
11. **[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*
12. **[All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational Quality](https://md.research.elamur.ai/free/en/papers/timkey-2021-all-bark-no-bite-rogue/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**William Timkey, Marten van Schijndel*2021 · 139 citations*
13. **[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 · 129 citations*
14. [**The case for 4-bit precision: k-bit Inference Scaling Laws arXiv:2212.09720**Tim Dettmers, Luke Zettlemoyer*2022 · 119 citations*](https://md.research.elamur.ai/free/en/papers/dettmers-2022-case-4-bit-precision-k/)
15. [**Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies arXiv:2407.13623**Chaofan Tao, Qian Liu, Longxu Dou, et al.*2024 · 42 citations*](https://md.research.elamur.ai/free/en/papers/tao-2024-scaling-laws-vocabulary-larger-models/)
16. **[Synergetic Event Understanding: A Collaborative Approach to Cross-Document Event Coreference Resolution with Large Language Models](https://md.research.elamur.ai/free/en/papers/min-2024-synergetic-event-understanding-collaborative-approach/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingkai Min, Qipeng Guo, Xiangkun Hu, et al.*2024 · 19 citations*
17. [**MiqraBERT: Regression-Based Sentence-BERT Finetuning for Biblical Hebrew Parallel Detection**David M. Smiley*2026*](https://md.research.elamur.ai/free/en/papers/smiley-2026-miqrabert-regression-based-sentence-bert/)
18. **[MUC-4 Revisited: Document-level Event Analysis beyond Span-based Arguments](https://md.research.elamur.ai/free/en/papers/olsen-2026-muc-4-revisited-document-level/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Helene Bøsei Olsen, Erik Velldal, Lilja Øvrelid*2026*

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

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