MIT HAN Lab ORG

[ICLR 2024] Efficient Streaming Language Models with Attention Sinks

StreamingLLM lets AI language models run indefinitely in long chat sessions without crashing or forgetting, by keeping only the first few anchor tokens and the most recent messages in memory.

[MLSys 2024 Best Paper Award] AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration

Efficient vision foundation models for high-resolution generation and perception.

[ICRA'23] BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation

[ICCV 2019] TSM: Temporal Shift Module for Efficient Video Understanding

[ICLR 2020] Once for All: Train One Network and Specialize it for Efficient Deployment

[ICML 2023] SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models

A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers.

[MICRO'23, MLSys'22] TorchSparse: Efficient Training and Inference Framework for Sparse Convolution on GPUs.

[ICLR 2019] ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware

[NeurIPS 2020] Differentiable Augmentation for Data-Efficient GAN Training

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[CVPR 2020] GAN Compression: Efficient Architectures for Interactive Conditional GANs

StreamingVLM: Real-Time Understanding for Infinite Video Streams

TinyChatEngine: On-Device LLM Inference Library

[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning; [NeurIPS 2022] MCUNetV3: On-Device Training Under 256KB Memory

[MLSys'25] QServe: W4A8KV4 Quantization and System Co-design for Efficient LLM Serving; [MLSys'25] LServe: Efficient Long-sequence LLM Serving with Unified Sparse Attention

[CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing

[CVPR 2024 Highlight] DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models

[IJCV] FastComposer: Tuning-Free Multi-Subject Image Generation with Localized Attention

[NeurIPS 2020] MCUNet: Tiny Deep Learning on IoT Devices; [NeurIPS 2021] MCUNetV2: Memory-Efficient Patch-based Inference for Tiny Deep Learning

[NeurIPS 2019, Spotlight] Point-Voxel CNN for Efficient 3D Deep Learning

HART: Efficient Visual Generation with Hybrid Autoregressive Transformer

[ECCV 2020] Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

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[ICLR 2020] Lite Transformer with Long-Short Range Attention

[NeurIPS 2025] Radial Attention: O(nlogn) Sparse Attention with Energy Decay for Long Video Generation

[ICLR 2025] DuoAttention: Efficient Long-Context LLM Inference with Retrieval and Streaming Heads

A sparse attention kernel supporting mix sparse patterns

On-Device Training Under 256KB Memory [NeurIPS'22]

[NeurIPS 2019] Deep Leakage From Gradients

[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices

[ICLR 2025] VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation

Real-Time VLAs via Future-state-aware Asynchronous Inference.

[CVPR 2019, Oral] HAQ: Hardware-Aware Automated Quantization with Mixed Precision

[ICML 2024] Quest: Query-Aware Sparsity for Efficient Long-Context LLM Inference

Offsite-Tuning: Transfer Learning without Full Model

[ACL'20] HAT: Hardware-Aware Transformers for Efficient Natural Language Processing

[CVPR'22] Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation

[ICML 2025] XAttention: Block Sparse Attention with Antidiagonal Scoring

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[MLSys 2021] IOS: Inter-Operator Scheduler for CNN Acceleration

Code for the papers: “Four Over Six: More Accurate NVFP4 Quantization with Adaptive Block Scaling” and “Adaptive Block-Scaled Data Types”

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[ASPLOS'26] Taming the Long-Tail: Efficient Reasoning RL Training with Adaptive Drafter

[ECCV 2018] AMC: AutoML for Model Compression and Acceleration on Mobile Devices

[CVPR 2020] APQ: Joint Search for Network Architecture, Pruning and Quantization Policy

[CVPR'23] FlatFormer: Flattened Window Attention for Efficient Point Cloud Transformer

[HPCA'21] SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning

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[ICLR 2026 Oral] Locality-aware Parallel Decoding for Efficient Autoregressive Image Generation

Patch convolution to avoid large GPU memory usage of Conv2D

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[CVPR'23] SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer

[CVPR 2026 Highlight] ForeAct: Steering Your VLA with Efficient Visual Foresight Planning

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Binary Neural Network on IceStick FPGA.

Efficient 3D Deep Learning

[JMLR'20] NeurIPS 2019 MicroNet Challenge Efficient Language Modeling, Champion

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[ICML 2026] Stable Asynchrony: Variance-Controlled Off-Policy RL for LLMs

A WebUI for Side-by-Side Comparison of Media (Images/Videos) Across Multiple Folders

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[ICCAD'22 TinyML Contest] Efficient Heart Stroke Detection on Low-cost Microcontrollers

[ECCV 2024] SparseRefine: Sparse Refinement for Efficient High-Resolution Semantic Segmentation

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OpenMMLab Pose Estimation Toolbox and Benchmark.