2 citations · 3 across the 12 of their papers we have counts for
5 papers · 1 filter
It's Morphing Time: Unleashing the Potential of Multiple LLMs via Multi-objective Optimization
Bingdong Li, Zixiang Di, Yanting Yang +5
In this paper, we introduce a novel approach for addressing the multi-objective optimization problem in large language model merging via black-box multi-objective optimization algo…
ORCDF: An Oversmoothing-Resistant Cognitive Diagnosis Framework for Student Learning in Online Education Systems
Hong Qian, Shuo Liu, Mingjia Li +3
Cognitive diagnosis models (CDMs) are designed to learn students' mastery levels using their response logs. CDMs play a fundamental role in online education systems since they sign…
A First Look at Kolmogorov-Arnold Networks in Surrogate-assisted Evolutionary Algorithms
Hao Hao, Xiaoqun Zhang, Bingdong Li +1
Surrogate-assisted Evolutionary Algorithm (SAEA) is an essential method for solving expensive expensive problems. Utilizing surrogate models to substitute the optimization function…
Expensive Multi-Objective Bayesian Optimization Based on Diffusion Models
Bingdong Li, Zixiang Di, Yongfan Lu +5
Multi-objective Bayesian optimization (MOBO) has shown promising performance on various expensive multi-objective optimization problems (EMOPs). However, effectively modeling compl…
Context-aware Diversity Enhancement for Neural Multi-Objective Combinatorial Optimization
Yongfan Lu, Zixiang Di, Bingdong Li +5
Multi-objective combinatorial optimization (MOCO) problems are prevalent in various real-world applications. Most existing neural MOCO methods rely on problem decomposition to tran…