4 citations · 4 across the 6 of their papers we have counts for
6 papers
Tool-Augmented On-Policy Distillation for LLM Domain Adaptation in Sequence-Based Omics Tasks
Jie Ying, Zhefan Wang, Zihong Chen +11
Multi-omics sequences contain complex biological patterns, yet deciphering their mechanisms for automated scientific discovery remains challenging. As large language models (LLMs)…
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…
Scalable Multi-Agent Reinforcement Learning for Residential Load Scheduling under Data Governance
Zhaoming Qin, Nanqing Dong, Di Liu +2
As a data-driven approach, multi-agent reinforcement learning (MARL) has made remarkable advances in solving cooperative residential load scheduling problems. However, centralized…