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Multi-Objective Optimization

154 papers

Papers per year

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18
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Papers

Robust Multi-Objective Preference Alignment with Online DPO AAAI 2025
Generative Flow Networks for Lead Optimization in Drug Design (Student Abstract) AAAI 2025
ERFSL: An Efficient Reward Function Searcher via Large Language Models for Custom-Environment Multi-Objective Reinforcement Learning (Student Abstract) AAAI 2025
Gradient-Adaptive Policy Optimization: Towards Multi-Objective Alignment of Large Language Models ACL 2025
K-order Ranking Preference Optimization for Large Language Models ACL 2025
4DGC: Rate-Aware 4D Gaussian Compression for Efficient Streamable Free-Viewpoint Video CVPR 2025
MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework CVPR 2025
COM-BOM: Bayesian Exemplar Search for Efficiently Exploring the Accuracy-Calibration Pareto Frontier EMNLP 2025
Auto-Weighted Group Relative Preference Optimization for Multi-Objective Text Generation Tasks EMNLP 2025
Multi-Surrogate-Objective Optimization for Neural Topic Models EMNLP 2025
A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problems NIPS 2024
Learning the Optimal Policy for Balancing Short-Term and Long-Term Rewards NIPS 2024
ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons NIPS 2024
Decoding-Time Language Model Alignment with Multiple Objectives NIPS 2024
HW-GPT-Bench: Hardware-Aware Architecture Benchmark for Language Models NIPS 2024
Multi-Stage Predict+Optimize for (Mixed Integer) Linear Programs NIPS 2024
Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime NIPS 2024
Fair and Welfare-Efficient Constrained Multi-Matchings under Uncertainty NIPS 2024
Panacea: Pareto Alignment via Preference Adaptation for LLMs NIPS 2024
An Analytical Study of Utility Functions in Multi-Objective Reinforcement Learning NIPS 2024
CE-NAS: An End-to-End Carbon-Efficient Neural Architecture Search Framework NIPS 2024
Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization NIPS 2024
Unveiling User Satisfaction and Creator Productivity Trade-Offs in Recommendation Platforms NIPS 2024
Long-Tailed Learning as Multi-Objective Optimization AAAI 2024
FairTrade: Achieving Pareto-Optimal Trade-Offs between Balanced Accuracy and Fairness in Federated Learning AAAI 2024