MoEGen: Mixture-of-Experts for Instance-Adaptive LoRA Generation
cs.CL
Submitted: 2026-08-04
Updated: 2026-09-29
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Scaling Sparse Fine-Tuning to Large Language Models
- PIQA: Reasoning about Physical Commonsense in Natural Language
- PaLM: Scaling Language Modeling with Pathways
- BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions
- Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
- GLaM: Efficient Scaling of Language Models with Mixture-of-Experts
- Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity
- The Llama 3 Herd of Models
- Parameter-Efficient Transfer Learning for NLP
- PubMedQA: A Dataset for Biomedical Research Question Answering
- Solving Quantitative Reasoning Problems with Language Models
- Prefix-Tuning: Optimizing Continuous Prompts for Generation
- LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
- Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning
- When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications
- DoRA: Weight-Decomposed Low-Rank Adaptation
- Decoupled Weight Decay Regularization
- All-in-One Tuning and Structural Pruning for Domain-Specific LLMs
- 2 OLMo 2 Furious
- GPT-4 Technical Report
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