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cs.CL2026
Evolutionary Soups: Evolving Mixture-of-Experts for Multi-Objective LLM Alignment
Lingxiao Kong, Steffen Staab, Cong Yang +2
Large language models are increasingly required to generate responses that satisfy multiple competing objectives. Since optimal trade-offs depend on both user preferences and input…
cs.CL2025
Multi-Objective Reinforcement Learning for Large Language Model Optimization: Visionary Perspective
Lingxiao Kong, Cong Yang, Oya Deniz Beyan +1
Multi-Objective Reinforcement Learning (MORL) presents significant challenges and opportunities for optimizing multiple objectives in Large Language Models (LLMs). We introduce a M…
cs.CL2025
EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning
Lingxiao Kong, Cong Yang, Susanne Neufang +2
Recent advances in reinforcement learning (RL) for large language model (LLM) fine-tuning show promise in addressing multi-objective tasks but still face significant challenges, in…