matrix multiplication

Adversarial Inputs for Linear Algebra Backends ICML 2025 A Fast Optimization View: Reformulating Single Layer Attention in LLM Based on Tensor and SVM Trick, and Solving It in Matrix Multiplication Time UAI 2025 An Efficient Matrix Multiplication Algorithm for Accelerating Inference in Binary and Ternary Neural Networks ICML 2025 any4: Learned 4-bit Numeric Representation for LLMs ICML 2025 Bitnet.cpp: Efficient Edge Inference for Ternary LLMs ACL 2025 DeepCompress-ViT: Rethinking Model Compression to Enhance Efficiency of Vision Transformers at the Edge CVPR 2025 Discovering Group Structures via Unitary Representation Learning ICLR 2025 Faster Algorithms for Structured Linear and Kernel Support Vector Machines ICLR 2025 NestQuant: nested lattice quantization for matrix products and LLMs ICML 2025 QiMeng-GEMM: Automatically Generating High-Performance Matrix Multiplication Code by Exploiting Large Language Models AAAI 2025 SageAttention2: Efficient Attention with Thorough Outlier Smoothing and Per-thread INT4 Quantization ICML 2025 SpargeAttention: Accurate and Training-free Sparse Attention Accelerating Any Model Inference ICML 2025 ThunderKittens: Simple, Fast, and Adorable Kernels ICLR 2025 Training LLMs with MXFP4 AISTATS 2025 A Provably Accurate Randomized Sampling Algorithm for Logistic Regression AAAI 2024 Efficient Detection of Long Consistent Cycles and its Application to Distributed Synchronization CVPR 2024 Fast Dynamic Sampling for Determinantal Point Processes AISTATS 2024 Fast Matrix Multiplications for Lookup Table-Quantized LLMs EMNLP 2024 FlattenQuant: Breaking through the Inference Compute-bound for Large Language Models with Per-tensor Quantization COLING 2024 In Defense of Structural Sparse Adapters for Concurrent LLM Serving EMNLP 2024 I/O Complexity of Attention, or How Optimal is FlashAttention? ICML 2024 John Ellipsoids via Lazy Updates NeurIPS 2024 LibAMM: Empirical Insights into Approximate Computing for Accelerating Matrix Multiplication NeurIPS 2024 LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models ICLR 2024 Nimbus: Secure and Efficient Two-Party Inference for Transformers NeurIPS 2024