4 papers
Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains
Zhonghang Yuan, Zhefan Wang, Fang Hu +7
Reinforcement learning with verifiable rewards (RLVR) has demonstrated promising potential to enhance the reasoning capabilities of large language models (LLMs) in domains such as…
SeedBench: A Multi-task Benchmark for Evaluating Large Language Models in Seed Science
Jie Ying, Zihong Chen, Zhefan Wang +7
Seed science is essential for modern agriculture, directly influencing crop yields and global food security. However, challenges such as interdisciplinary complexity and high costs…
ROGRAG: A Robustly Optimized GraphRAG Framework
Zhefan Wang, Huanjun Kong, Jie Ying +2
Large language models (LLMs) commonly struggle with specialized or emerging topics which are rarely seen in the training corpus. Graph-based retrieval-augmented generation (GraphRA…
An Embarrassingly Simple Approach to Enhance Transformer Performance in Genomic Selection for Crop Breeding
Renqi Chen, Wenwei Han, Haohao Zhang +6
Genomic selection (GS), as a critical crop breeding strategy, plays a key role in enhancing food production and addressing the global hunger crisis. The predominant approaches in G…