---
title: "Guangzhou–Foshan — works of 2023 — 9 papers in our library"
description: "9 works of Guangzhou–Foshan from 2023 in our library, the most cited first. Among them: Grounding DINO: Marrying DINO with Grounded…"
canonical: "https://research.elamur.ai/free/en/agglomerations/guangzhou-foshan/year/2023/"
---
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# Works of Guangzhou–Foshan from 2023

9 works · the most cited first · [← Guangzhou–Foshan](https://md.research.elamur.ai/free/en/agglomerations/guangzhou-foshan/)

1. [**Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection arXiv:2303.05499**Shilong Liu, Zhaoyang Zeng, Tianhe Ren, et al.*2023 · 430 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-grounding-dino-marrying-dino-grounded/)
2. **[AugGPT: Leveraging ChatGPT for Text Data Augmentation](https://md.research.elamur.ai/free/en/papers/dai-2023-auggpt-leveraging-chatgpt-text-data/) [IEEE Transactions on Big Data](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-big-data/)**Haixing Dai; Zhengliang Liu; Wenxiong Liao; Xiaoke Huang; Yihan Cao; Zihao Wu; Lin Zhao; Shaochen Xu; Wei Liu; Ninghao Liu; Sheng Li; Dajiang Zhu; Hongmin Cai; Lichao Sun; Quanzheng Li; Dinggang Shen; Tianming Liu;, Xiang Li*2023 · 306 citations*
3. **[OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/liu-2023-ocrbench-hidden-mystery-ocr-large/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Yuliang Liu, Zhang Li, Mingxin Huang, et al.*2023 · 297 citations*
4. **[Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data](https://md.research.elamur.ai/free/en/papers/xu-2023-baize-open-source-chat-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Canwen Xu, Daya Guo, Nan Duan, et al.*2023 · 296 citations*
5. [**MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning arXiv:2309.05653**Xiang Yue, Xingwei Qu, Ge Zhang, et al.*2023 · 288 citations*](https://md.research.elamur.ai/free/en/papers/yue-2023-mammoth-building-math-generalist-models/)
6. **[Assessing Cross-Cultural Alignment between ChatGPT and Human Societies: An Empirical Study](https://md.research.elamur.ai/free/en/papers/cao-2023-assessing-cross-cultural-alignment-between/) [Workshop on Cross-Cultural Considerations in NLP](https://md.research.elamur.ai/free/en/venues/c3nlp/)**Yong Cao, Li Zhou, Seolhwa Lee, et al.*2023 · 278 citations*
7. [**A Survey of Large Language Models in Medicine: Progress, Application, and Challenge arXiv:2311.05112**Hongjian Zhou, Fenglin Liu, Boyang Gu, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-survey-large-language-models-medicine/)
8. **[Large Language Models Meet Harry Potter: A Dataset for Aligning Dialogue Agents with Characters](https://md.research.elamur.ai/free/en/papers/chen-2023-large-language-models-meet-harry/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nuo Chen, Yan Wang, Haiyun Jiang, et al.*2023 · 80 citations*
9. **[Global and Local Hierarchy-aware Contrastive Framework for Implicit Discourse Relation Recognition](https://md.research.elamur.ai/free/en/papers/jiang-2023-global-local-hierarchy-aware-contrastive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuxin Jiang, Linhan Zhang, Wei Wang*2023 · 28 citations*
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