Fetching the paper…
Reading the bibliography…
We present AgMMU, a challenging real-world benchmark for evaluating and advancing vision-language models (VLMs) in the knowledge-intensive domain of agriculture.
Making the V in VQA matter: Elevating the role of image understanding in Visual Question Answering
Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh · 2017
Earlier work this paper cites.
Computer vision and artificial intelligence in precision agriculture for grain crops: A systematic review
Diego Inácio Patrício and Rafael Rieder · 2018
Earlier work this paper cites.
Gqa: A new dataset for real-world visual reasoning and compositional question answering
Drew A Hudson and Christopher D Manning · 2019
Earlier work this paper cites.
Towards VQA models that can read
Amanpreet Singh, Vivek Natarajan, Meet Shah, Yu Jiang, Xinlei Chen, Dhruv Batra, Devi Parikh, and Marcus Rohrbach · 2019
Earlier work this paper cites.
Plantdoc: A dataset for visual plant disease detection
Davinder Singh, Naman Jain, Pranjali Jain, Pratik Kayal, Sudhakar Kumawat, and Nipun Batra · 2020
Earlier work this paper cites.
A role of computer vision in fruits and vegetables among various horticulture products of agriculture fields: A survey
Mukesh Kumar Tripathi and Dhananjay D. Maktedar · 2020
Earlier work this paper cites.
Diamos plant: A dataset for diagnosis and monitoring plant disease
Gianni Fenu and Francesca Maridina Malloci · 2021
Earlier work this paper cites.
inat challenge 2021, 2021
Grant Van Horn and Oisin Mac Aodha · 2021
Earlier work this paper cites.
Lora: Low-rank adaptation of large language models
Edward J Hu, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, Weizhu Chen, et al · 2021
Earlier work this paper cites.
Plant disease recognition: A large-scale benchmark dataset and a visual region and loss reweighting approach
Xinda Liu, Weiqing Min, Shuhuan Mei, Lili Wang, and Shuqiang Jiang · 2021
Earlier work this paper cites.
Docvqa: A dataset for vqa on document images
Minesh Mathew, Dimosthenis Karatzas, and CV Jawahar · 2021
Earlier work this paper cites.
Machine learning in agriculture domain: A state-of-art survey
Vishal Meshram, Kailas Patil, Vidula Meshram, Dinesh Hanchate, and S.D. Ramkteke · 2021
Earlier work this paper cites.
Review on knowledge extraction from text and scope in agriculture domain - Artificial Intelligence Review — link.springer.com, 2022
M.B. Nismi Mol E.A., Santosh Kumar · 2022
Earlier work this paper cites.
Scienceqa: A novel resource for question answering on scholarly articles
Tanik Saikh, Tirthankar Ghosal, Amish Mittal, Asif Ekbal, and Pushpak Bhattacharyya · 2022
Earlier work this paper cites.
Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
Cited alongside, same era.
Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou · 2023
Cited alongside, same era.
Deep learning powered real-time identification of insects using citizen science data
S Chiranjeevi, M Sadaati, Deng ZK, J Koushik, Jubery TZ, D Mueller, ME O’Neal, N Merchant, A Singh, AK Singh, S Sarkar, A Singh, and B Ganapathysubramanian · 2023
Cited alongside, same era.
Farmer.chat by digital green – making vetted farmer knowledge accessible
Inc. Digital Green · 2023
Cited alongside, same era.
Meet norm, the world’s first ai ag advisor
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al · 2024
Later among the works it cites.
Zero-shot insect detection via weak language supervision
Benjamin Feuer, Ameya Joshi, Minsu Cho, Shivani Chiranjeevi, Zi Kang Deng, Aditya Balu, Asheesh K. Singh, Soumik Sarkar, Nirav Merchant, and Arti Singh · 2024
Later among the works it cites.
A step towards worldwide biodiversity assessment: The bioscan-1m insect dataset
Zahra Gharaee, ZeMing Gong, Nicholas Pellegrino, Iuliia Zarubiieva, Joakim Bruslund Haurum, Scott Lowe, Jaclyn McKeown, Chris Ho, Joschka McLeod, Yi-Yun Wei, et al · 2024
Later among the works it cites.
Bioscan-clip: Bridging vision and genomics for biodiversity monitoring at scale
ZeMing Gong, Austin T Wang, Joakim Bruslund Haurum, Scott C Lowe, Graham W Taylor, and Angel X Chang · 2024
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
The Farmers Business Network (FBN) · 2023
Cited alongside, same era.
Ask extension
Extention Foundation · 2023
Cited alongside, same era.
Llava-med: Training a large language-and-vision assistant for biomedicine in one day, 2023
Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, and Jianfeng Gao · 2023
Cited alongside, same era.
Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
Cited alongside, same era.
Gpt-4 as an agronomist assistant? answering agriculture exams using large language models
Bruno Silva, Leonardo Nunes, Roberto Estevão, Vijay Aski, and Ranveer Chandra · 2023
Cited alongside, same era.
Gemini: A family of highly capable multimodal models
Gemini Team, Rohan Anil, Sebastian Borgeaud, Yonghui Wu, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, et al · 2023
Cited alongside, same era.
Cropwizard: Visual and computational question answering for agriculture professionals
V Adve, K Day, A Dabholkar, and R Marwaha · 2024
Cited alongside, same era.
Agrogpt: Efficient agricultural vision-language model with expert tuning, 2024
Muhammad Awais, Ali Husain Salem Abdulla Alharthi, Amandeep Kumar, Hisham Cholakkal, and Rao Muhammad Anwer · 2024
Cited alongside, same era.
Bo Li, Yuanhan Zhang, Dong Guo, Renrui Zhang, Feng Li, Hao Zhang, Kaichen Zhang, Yanwei Li, Ziwei Liu, and Chunyuan Li · 2024
Later among the works it cites.
VILA: On pre-training for visual language models
Ji Lin, Hongxu Yin, Wei Ping, Pavlo Molchanov, Mohammad Shoeybi, and Song Han · 2024
Later among the works it cites.
M Maruf, Arka Daw, Kazi Sajeed Mehrab, Harish Babu Manogaran, Abhilash Neog, Medha Sawhney, Mridul Khurana, James P Balhoff, Yasin Bakis, Bahadir Altintas, et al · 2024
Later among the works it cites.
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al · 2024
Later among the works it cites.
Bioclip: A vision foundation model for the tree of life
Samuel Stevens, Jiaman Wu, Matthew J Thompson, Elizabeth G Campolongo, Chan Hee Song, David Edward Carlyn, Li Dong, Wasila M Dahdul, Charles Stewart, Tanya Berger-Wolf, et al · 2024
Later among the works it cites.
Taranis launches ag assistant to transform farm decision making
Inc. Taranis · 2024
Later among the works it cites.
Grok, 2024
xAI Team · 2024
Later among the works it cites.
Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, et al · 2024
Later among the works it cites.
Agribench: A hierarchical agriculture benchmark for multimodal large language models
Yutong Zhou and Masahiro Ryo · 2024
Later among the works it cites.