Efficient Computing

Minimax optimality of convolutional neural networks for infinite dimensional input-output problems and separation from kernel methods ICLR 2024 Mini-Sequence Transformers: Optimizing Intermediate Memory for Long Sequences Training NeurIPS 2024 MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens NeurIPS 2024 Mitigating Overfitting in Structured Pruning of ASR Models with Gradient-Guided Parameter Regularization Interspeech 2024 Mitigating the Impact of Reference Quality on Evaluation of Summarization Systems with Reference-Free Metrics EMNLP 2024 Mixed-Precision Quantization for Federated Learning on Resource-Constrained Heterogeneous Devices CVPR 2024 Mixture of Nested Experts: Adaptive Processing of Visual Tokens NeurIPS 2024 Mixture of Scales: Memory-Efficient Token-Adaptive Binarization for Large Language Models NeurIPS 2024 Mixture-of-Supernets: Improving Weight-Sharing Supernet Training with Architecture-Routed Mixture-of-Experts ACL 2024 MLIP: Efficient Multi-Perspective Language-Image Pretraining with Exhaustive Data Utilization ICML 2024 MLP Can Be A Good Transformer Learner CVPR 2024 Mobile Attention: Mobile-Friendly Linear-Attention for Vision Transformers ICML 2024 MobileConfig: Remote Configuration Management for Mobile Apps at Hyperscale NSDI 2024 MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases ICML 2024 MobileNVC: Real-Time 1080p Neural Video Compression on a Mobile Device WACV 2024 Mobile PresenTra: NICT fast neural text-to-speech system on smartphones with incremental inference of MS-FC-HiFi-GAN for law-latency synthesis Interspeech 2024 MobileQuant: Mobile-friendly Quantization for On-device Language Models EMNLP 2024 MobileSpeech: A Fast and High-Fidelity Framework for Mobile Zero-Shot Text-to-Speech ACL 2024 ModaVerse: Efficiently Transforming Modalities with LLMs CVPR 2024 Model Adaptation for Time Constrained Embodied Control CVPR 2024 Modeling the Real World with High-Density Visual Particle Dynamics CoRL 2024 MoEAD: A Parameter-efficient Model for Multi-class Anomaly Detection ECCV 2024 MonoNN: Enabling a New Monolithic Optimization Space for Neural Network Inference Tasks on Modern GPU-Centric Architectures OSDI 2024 MOSEL: Inference Serving Using Dynamic Modality Selection EMNLP 2024 MOTE-NAS: Multi-Objective Training-based Estimate for Efficient Neural Architecture Search NeurIPS 2024