UniQL: Unified Quantization and Low-rank Compression for Adaptive Edge LLMs Paper • 2512.03383 • Published 4 days ago • 3
SparseLoRA: Accelerating LLM Fine-Tuning with Contextual Sparsity Paper • 2506.16500 • Published Jun 19 • 17
MLE-Dojo: Interactive Environments for Empowering LLM Agents in Machine Learning Engineering Paper • 2505.07782 • Published May 12 • 19
Model-GLUE: Democratized LLM Scaling for A Large Model Zoo in the Wild Paper • 2410.05357 • Published Oct 7, 2024
PortLLM: Personalizing Evolving Large Language Models with Training-Free and Portable Model Patches Paper • 2410.10870 • Published Oct 8, 2024 • 1
Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models Paper • 2503.22879 • Published Mar 28 • 9
Quamba: A Post-Training Quantization Recipe for Selective State Space Models Paper • 2410.13229 • Published Oct 17, 2024 • 1
Efficient Low-rank Backpropagation for Vision Transformer Adaptation Paper • 2309.15275 • Published Sep 26, 2023 • 1
MobileTL: On-device Transfer Learning with Inverted Residual Blocks Paper • 2212.03246 • Published Dec 5, 2022 • 1
Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study Paper • 2404.10719 • Published Apr 16, 2024 • 6
On Designing Effective RL Reward at Training Time for LLM Reasoning Paper • 2410.15115 • Published Oct 19, 2024
Mixture-of-Mamba: Enhancing Multi-Modal State-Space Models with Modality-Aware Sparsity Paper • 2501.16295 • Published Jan 27 • 8
Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback Paper • 2501.10799 • Published Jan 18 • 15
Learning to (Learn at Test Time): RNNs with Expressive Hidden States Paper • 2407.04620 • Published Jul 5, 2024 • 34
MoA: Mixture of Sparse Attention for Automatic Large Language Model Compression Paper • 2406.14909 • Published Jun 21, 2024 • 16
ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization Paper • 2406.05981 • Published Jun 10, 2024 • 16