3 papers
cs.AI2026
EvoSim: Learning to Model, Modeling to Learn
Yun-Wei Song, Jinkai Tao, Jun-Dong Zhang +3
Physics-based models connect scientific explanation with quantitative prediction. Constructing them requires selecting physical processes, defining states and governing equations,…
cs.CL2026
Continuous Knowledge Metabolism: Generating Scientific Hypotheses from Evolving Literature
Jinkai Tao, Yubo Wang, Xiaoyu Liu +1
Identifying promising research directions in fast-moving subareas is one of the most cognitively expensive tasks in modern AI research. Existing LLM-driven scientific discovery sys…
cs.LG2026
Parameter-Efficient Fine-Tuning of LLMs with Mixture of Space Experts
Buze Zhang, Jinkai Tao, Zilang Zeng +4
Large Language Models (LLMs) have achieved remarkable progress, with Parameter-Efficient Fine-Tuning (PEFT) emerging as a key technique for downstream task adaptation. However, exi…