1 citations · 1 across the 9 of their papers we have counts for
Showing cs.LGShow all
3 papers · 1 filter
cs.LG2025
CoMoE: Contrastive Representation for Mixture-of-Experts in Parameter-Efficient Fine-tuning
Jinyuan Feng, Chaopeng Wei, Tenghai Qiu +2
In parameter-efficient fine-tuning, mixture-of-experts (MoE), which involves specializing functionalities into different experts and sparsely activating them appropriately, has bee…
cs.LG2025
OMoE: Diversifying Mixture of Low-Rank Adaptation by Orthogonal Finetuning
Jinyuan Feng, Zhiqiang Pu, Tianyi Hu +3
Building mixture-of-experts (MoE) architecture for Low-rank adaptation (LoRA) is emerging as a potential direction in parameter-efficient fine-tuning (PEFT) for its modular design…
cs.LG2024
Efficient Multi-Task Reinforcement Learning via Task-Specific Action Correction
Jinyuan Feng, Min Chen, Zhiqiang Pu +2
Multi-task reinforcement learning (MTRL) demonstrate potential for enhancing the generalization of a robot, enabling it to perform multiple tasks concurrently. However, the perform…