MACaQ: Fast, Model Agnostic Calibrated Quantization for Low-Precision Weights and Activations Paper • 2611.10649 • Published 6 days ago • 31
GitScholar: A Dataset for Predicting AI Research Impact from GitHub Engagement Paper • 2609.26361 • Published Sep 22
Top-Theta Attention: Sparsifying Transformers by Compensated Thresholding Paper • 2502.08363 • Published Feb 12, 2025 • 1
KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Paper • 2606.03458 • Published Jun 2 • 62
Don't be so Stief! Learning KV Cache low-rank approximation over the Stiefel manifold Paper • 2601.21686 • Published May 29
MACaQ: Fast, Model Agnostic Calibrated Quantization for Low-Precision Weights and Activations Paper • 2611.10649 • Published 6 days ago • 31
Running 97 Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation 🌼 97 Depth, surface normals, and albedo from a single image
Marigold V2: Revisiting Diffusion Transformers for Monocular Depth Estimation Paper • 2609.08084 • Published Sep 8 • 60
KVarN: Variance-Normalized KV-Cache Quantization Mitigates Error Accumulation in Reasoning Tasks Paper • 2606.03458 • Published Jun 2 • 62