Cover Image

FoMEMO: Towards Foundation Models for Expensive Multi-objective Optimization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yao, Yiming, Liu, Fei, Zhao, Liang, Lin, Xi, Liu, Yilu, Zhang, Qingfu
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Quality-Diversity Optimization as Multi-Objective Optimization
by: Lin, Xi, et al.
Published: (2026)

Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization
by: Lin, Xi, et al.
Published: (2024)

Fine-tuning Large Language Model for Automated Algorithm Design
by: Liu, Fei, et al.
Published: (2025)

Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization
by: Liu, Fei, et al.
Published: (2024)

Expensive Multi-Objective Bayesian Optimization Based on Diffusion Models
by: Li, Bingdong, et al.
Published: (2024)

Smooth Tchebycheff Scalarization for Multi-Objective Optimization
by: Lin, Xi, et al.
Published: (2024)

EvoEngineer: Mastering Automated CUDA Kernel Code Evolution with Large Language Models
by: Guo, Ping, et al.
Published: (2025)

L-AutoDA: Leveraging Large Language Models for Automated Decision-based Adversarial Attacks
by: Guo, Ping, et al.
Published: (2024)

Pareto Continual Learning: Preference-Conditioned Learning and Adaption for Dynamic Stability-Plasticity Trade-off
by: Lai, Song, et al.
Published: (2025)

A Systematic Survey on Large Language Models for Algorithm Design
by: Liu, Fei, et al.
Published: (2024)

Prompt Learning for Generalized Vehicle Routing
by: Liu, Fei, et al.
Published: (2024)

Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization
by: Lee, Deokjae, et al.
Published: (2024)

CoEvo: Continual Evolution of Symbolic Solutions Using Large Language Models
by: Guo, Ping, et al.
Published: (2024)

FoMo X: Modular Explainability Signals for Outlier Detection Foundation Models
by: Klüttermann, Simon, et al.
Published: (2026)

Self-Improved Learning for Scalable Neural Combinatorial Optimization
by: Luo, Fu, et al.
Published: (2024)

MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework
by: Guo, Ping, et al.
Published: (2025)

FoME: A Foundation Model for EEG using Adaptive Temporal-Lateral Attention Scaling
by: Shi, Enze, et al.
Published: (2024)

FoMo-0D: A Foundation Model for Zero-shot Tabular Outlier Detection
by: Shen, Yuchen, et al.
Published: (2024)

Graph Foundation Models: Bridging Language Model Paradigms and Graph Optimization
by: Liang, Yunhao, et al.
Published: (2025)

Multi-objective Evolution of Heuristic Using Large Language Model
by: Yao, Shunyu, et al.
Published: (2024)

c-TPE: Tree-structured Parzen Estimator with Inequality Constraints for Expensive Hyperparameter Optimization
by: Watanabe, Shuhei, et al.
Published: (2022)

\emph{FoQuS}: A Forgetting-Quality Coreset Selection Framework for Automatic Modulation Recognition
by: Lu, Yao, et al.
Published: (2025)

Route to Rome Attack: Directing LLM Routers to Expensive Models via Adversarial Suffix Optimization
by: Tang, Haochun, et al.
Published: (2026)

Learning to Insert for Constructive Neural Vehicle Routing Solver
by: Luo, Fu, et al.
Published: (2025)

Towards Neural Scaling Laws for Time Series Foundation Models
by: Yao, Qingren, et al.
Published: (2024)

BoLT: A Benchmark to Democratize Black-box Optimization Research for Expensive LLM Tasks
by: Chew, Ruth Wan Theng, et al.
Published: (2026)

Destroy and Repair Using Hyper Graphs for Routing
by: Li, Ke, et al.
Published: (2025)

Metis: Learning to Jailbreak LLMs via Self-Evolving Metacognitive Policy Optimization
by: Zhou, Huilin, et al.
Published: (2026)

On Constructing Algorithm Portfolios in Algorithm Selection for Computationally Expensive Black-box Optimization in the Fixed-budget Setting
by: Yoshikawa, Takushi, et al.
Published: (2024)

Learning to Reduce Search Space for Generalizable Neural Routing Solver
by: Zhou, Changliang, et al.
Published: (2025)

Few-for-Many Personalized Federated Learning
by: Guo, Ping, et al.
Published: (2026)

A Survey on Mechanistic Interpretability for Multi-Modal Foundation Models
by: Lin, Zihao, et al.
Published: (2025)

Wisdom of Committee: Distilling from Foundation Model to Specialized Application Model
by: Liu, Zichang, et al.
Published: (2024)

Large Language Model for Multi-objective Evolutionary Optimization
by: Liu, Fei, et al.
Published: (2023)

Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training
by: Lai, Song, et al.
Published: (2025)

Towards Robust Multi-Modal Reasoning via Model Selection
by: Liu, Xiangyan, et al.
Published: (2023)

EoH-S: Evolution of Heuristic Set using LLMs for Automated Heuristic Design
by: Liu, Fei, et al.
Published: (2025)

Connector-S: A Survey of Connectors in Multi-modal Large Language Models
by: Zhu, Xun, et al.
Published: (2025)

AutoLLMResearch: Training Research Agents for Automating LLM Experiment Configuration - Learning from Cheap, Optimizing Expensive
by: Guo, Taicheng, et al.
Published: (2026)

Foundation Model in Biomedicine
by: Liu, Xiangrui, et al.
Published: (2025)