Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Paper • 2507.21049 • Published Jul 28 • 40 • 4
Rep-MTL: Unleashing the Power of Representation-level Task Saliency for Multi-Task Learning Paper • 2507.21049 • Published Jul 28 • 40 • 4
Taming LLMs by Scaling Learning Rates with Gradient Grouping Paper • 2506.01049 • Published Jun 1 • 38 • 4
MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization Paper • 2504.00999 • Published Apr 1 • 93 • 7
MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization Paper • 2504.00999 • Published Apr 1 • 93 • 7
MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization Paper • 2504.00999 • Published Apr 1 • 93 • 7
MergeVQ: A Unified Framework for Visual Generation and Representation with Disentangled Token Merging and Quantization Paper • 2504.00999 • Published Apr 1 • 93 • 7
Switch EMA: A Free Lunch for Better Flatness and Sharpness Paper • 2402.09240 • Published Feb 14, 2024 • 4 • 1
Unveiling the Backbone-Optimizer Coupling Bias in Visual Representation Learning Paper • 2410.06373 • Published Oct 8, 2024 • 35 • 3
Unveiling the Backbone-Optimizer Coupling Bias in Visual Representation Learning Paper • 2410.06373 • Published Oct 8, 2024 • 35 • 3