PlantGPT: An Arabidopsis‐Based Intelligent Agent that Answers Questions about Plant Functional Genomics
Abstract Research into plant gene function is crucial for developing strategies to increase crop yields. The recent introduction of large language models (LLMs) offers a means to aggregate large amounts of data into a queryable format, but the output can contain inaccurate or false claims known as h...
Saved in:
| Main Authors: | Ruixiang Zhang, Yu Wang, Weiyang Yang, Jun Wen, Weizhi Liu, Shipeng Zhi, Guangzhou Li, Nan Chai, Jiaqi Huang, Yongyao Xie, Xianrong Xie, Letian Chen, Miao Gu, Yao‐Guang Liu, Qinlong Zhu |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2025-08-01
|
| Series: | Advanced Science |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/advs.202503926 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhancing Plant Protection Knowledge with Large Language Models: A Fine-Tuned Question-Answering System Using LoRA
by: Jie Xiong, et al.
Published: (2025-04-01) -
Lipschitz Analysis of g-Phase Retrievable Frames
by: Mohammad Ali Hasankhani Fard
Published: (2025-01-01) -
Unsupervised Context-Linking Retriever for Question Answering on Long Narrative Books
by: Mohammad A. Ateeq, et al.
Published: (2025-01-01) -
A topic-enhanced python question-answering model
by: WANG Shuo, et al.
Published: (2025-01-01) -
Bridging the Question–Answer Gap in Retrieval-Augmented Generation: Hypothetical Prompt Embeddings
by: Domen Vake, et al.
Published: (2025-01-01)