activation outlier

S2D: Selective Spectral Decay for Quantization-Friendly Conditioning of Neural Activations CVPR 2026 Theory-optimal Quantization Based on Flatness ACL 2026 AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference ACL 2025 BaWA: Automatic Optimizing Pruning Metric for Large Language Models with Balanced Weight and Activation ICML 2025 BoA: Attention-aware Post-training Quantization without Backpropagation ICML 2025 DecDEC: A Systems Approach to Advancing Low-Bit LLM Quantization OSDI 2025 DGQ: Distribution-Aware Group Quantization for Text-to-Image Diffusion Models ICLR 2025 KurTail : Kurtosis-based LLM Quantization EMNLP 2025 Outlier-Aware Post-Training Quantization for Image Super-Resolution ICCV 2025 Outlier-Safe Pre-Training for Robust 4-Bit Quantization of Large Language Models ACL 2025 Quaff: Quantized Parameter-Efficient Fine-Tuning under Outlier Spatial Stability Hypothesis ACL 2025 RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models ICML 2025 Systematic Outliers in Large Language Models ICLR 2025 DuQuant: Distributing Outliers via Dual Transformation Makes Stronger Quantized LLMs NeurIPS 2024 Prefixing Attention Sinks can Mitigate Activation Outliers for Large Language Model Quantization EMNLP 2024 Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models ICLR 2024 RoLoRA: Fine-tuning Rotated Outlier-free LLMs for Effective Weight-Activation Quantization EMNLP 2024 Outlier Suppression+: Accurate quantization of large language models by equivalent and effective shifting and scaling EMNLP 2023