Multi-scale Cartoon Motion Capture and Retargeting without Shape Matching. - Mohammad Rastegari; Niloofar Gheissari (DICTA, 2008)

Cartoon Motion Capturing and Retargeting by Rigid Shape Manipulation. - Mohammad Rastegari; Mohammad Rouhani; Niloofar Gheissari; Mir Mohsen Pedram (DICTA, 2009)

Object Detection using Pictorial Structure of Gabor Template. - Babak Saleh; Mohammad Rastegari (VISAPP (2), 2010)

Scalable object-class retrieval with approximate and top-k ranking. - Mohammad Rastegari; Chen Fang; Lorenzo Torresani (ICCV, 2011)

Attribute Discovery via Predictable Discriminative Binary Codes. - Mohammad Rastegari; Ali Farhadi; David A. Forsyth (ECCV (6), 2012)

Semantic Understanding of Professional Soccer Commentaries. - Hannaneh Hajishirzi; Mohammad Rastegari; Ali Farhadi; Jessica K. Hodgins (UAI, 2012)

Adding Unlabeled Samples to Categories by Learned Attributes. - Jonghyun Choi; Mohammad Rastegari; Ali Farhadi; Larry S. Davis (CVPR, 2013)

Multi-attribute Queries: To Merge or Not to Merge? - Mohammad Rastegari; Ali Diba; Devi Parikh; Ali Farhadi (CVPR, 2013)

Domain Adaptive Classification. - Fatemeh Mirrashed; Mohammad Rastegari (ICCV, 2013)

Predictable Dual-View Hashing. - Mohammad Rastegari; Jonghyun Choi; Shobeir Fakhraei; Hal Daumé III; Larry S. Davis (ICML (3), 2013)

Comparing apples to apples in the evaluation of binary coding methods. - Mohammad Rastegari; Shobeir Fakhraei; Jonghyun Choi; David W. Jacobs; Larry S. Davis (CoRR, 2014)

Discriminative and consistent similarities in instance-level Multiple Instance Learning. - Mohammad Rastegari; Hannaneh Hajishirzi; Ali Farhadi (CVPR, 2015)

Computationally bounded retrieval. - Mohammad Rastegari; Cem Keskin; Pushmeet Kohli; Shahram Izadi (CVPR, 2015)

Class consistent multi-modal fusion with binary features. - Ashish Shrivastava 001; Mohammad Rastegari; Sumit Shekhar; Rama Chellappa; Larry S. Davis (CVPR, 2015)

On Large-Scale Retrieval: Binary or n-ary Coding? - Mahyar Najibi; Mohammad Rastegari; Larry S. Davis (CoRR, 2015)

Action Recognition with Image Based CNN Features. - Mahdyar Ravanbakhsh; Hossein Mousavi; Mohammad Rastegari; Vittorio Murino; Larry S. Davis (CoRR, 2015)

Newtonian Image Understanding: Unfolding the Dynamics of Objects in Static Images. - Roozbeh Mottaghi; Hessam Bagherinezhad; Mohammad Rastegari; Ali Farhadi (CVPR, 2016)

G-CNN: An Iterative Grid Based Object Detector. - Mahyar Najibi; Mohammad Rastegari; Larry S. Davis (CVPR, 2016)

"What Happens If..." Learning to Predict the Effect of Forces in Images. - Roozbeh Mottaghi; Mohammad Rastegari; Abhinav Gupta 001; Ali Farhadi (ECCV (4), 2016)

XNOR-Net: ImageNet Classification Using Binary Convolutional Neural Networks. - Mohammad Rastegari; Vicente Ordonez; Joseph Redmon; Ali Farhadi (ECCV (4), 2016)

CNN-aware binary MAP for general semantic segmentation. - Mahdyar Ravanbakhsh; Hossein Mousavi; Moin Nabi; Mohammad Rastegari; Carlo S. Regazzoni (ICIP, 2016)

Rich and Efficient Visual Data Representation. - Mohammad Rastegari (2016)

LCNN: Lookup-Based Convolutional Neural Network. - Hessam Bagherinezhad; Mohammad Rastegari; Ali Farhadi (CVPR, 2017)

IQA: Visual Question Answering in Interactive Environments. - Daniel Gordon; Aniruddha Kembhavi; Mohammad Rastegari; Joseph Redmon; Dieter Fox; Ali Farhadi (CVPR, 2018)

ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation. - Sachin Mehta; Mohammad Rastegari; Anat Caspi; Linda G. Shapiro; Hannaneh Hajishirzi (ECCV (10), 2018)

Pyramidal Recurrent Unit for Language Modeling. - Sachin Mehta; Rik Koncel-Kedziorski; Mohammad Rastegari; Hannaneh Hajishirzi (EMNLP, 2018)

Label Refinery: Improving ImageNet Classification through Label Progression. - Hessam Bagherinezhad; Maxwell Horton; Mohammad Rastegari; Ali Farhadi (CoRR, 2018)

ELASTIC: Improving CNNs with Instance Specific Scaling Policies. - Huiyu Wang; Aniruddha Kembhavi; Ali Farhadi; Alan L. Yuille; Mohammad Rastegari (CoRR, 2018)

Assisted Excitation of Activations: A Learning Technique to Improve Object Detectors. - Mohammad Mahdi Derakhshani; Saeed Masoudnia; Amir Hossein Shaker; Omid Mersa; Mohammad Amin Sadeghi; Mohammad Rastegari; Babak Nadjar Araabi (CVPR, 2019)

Two Body Problem: Collaborative Visual Task Completion. - Unnat Jain; Luca Weihs; Eric Kolve; Mohammad Rastegari; Svetlana Lazebnik; Ali Farhadi; Alexander G. Schwing; Aniruddha Kembhavi (CVPR, 2019)

OK-VQA: A Visual Question Answering Benchmark Requiring External Knowledge. - Kenneth Marino; Mohammad Rastegari; Ali Farhadi; Roozbeh Mottaghi (CVPR, 2019)

ESPNetv2: A Light-Weight, Power Efficient, and General Purpose Convolutional Neural Network. - Sachin Mehta; Mohammad Rastegari; Linda G. Shapiro; Hannaneh Hajishirzi (CVPR, 2019)

ELASTIC: Improving CNNs With Dynamic Scaling Policies. - Huiyu Wang; Aniruddha Kembhavi; Ali Farhadi; Alan L. Yuille; Mohammad Rastegari (CVPR, 2019)

Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-Learning. - Mitchell Wortsman; Kiana Ehsani; Mohammad Rastegari; Ali Farhadi; Roozbeh Mottaghi (CVPR, 2019)

Discovering Neural Wirings. - Mitchell Wortsman; Ali Farhadi; Mohammad Rastegari (NeurIPS, 2019)

Butterfly Transform: An Efficient FFT Based Neural Architecture Design. - Keivan Alizadeh; Ali Farhadi; Mohammad Rastegari (CoRR, 2019)

DeFINE: DEep Factorized INput Word Embeddings for Neural Sequence Modeling. - Sachin Mehta; Rik Koncel-Kedziorski; Mohammad Rastegari; Hannaneh Hajishirzi (CoRR, 2019)

Butterfly Transform: An Efficient FFT Based Neural Architecture Design. - Keivan Alizadeh-Vahid; Anish Prabhu; Ali Farhadi; Mohammad Rastegari (CVPR, 2020)

What's Hidden in a Randomly Weighted Neural Network? - Vivek Ramanujan; Mitchell Wortsman; Aniruddha Kembhavi; Ali Farhadi; Mohammad Rastegari (CVPR, 2020)

DeFINE: Deep Factorized Input Token Embeddings for Neural Sequence Modeling. - Sachin Mehta; Rik Koncel-Kedziorski; Mohammad Rastegari; Hannaneh Hajishirzi (ICLR, 2020)

Supermasks in Superposition. - Mitchell Wortsman; Vivek Ramanujan; Rosanne Liu; Aniruddha Kembhavi; Mohammad Rastegari; Jason Yosinski; Ali Farhadi (NeurIPS, 2020)

Enabling AI at the edge with XNOR-networks. - Mohammad Rastegari; Vicente Ordonez; Joseph Redmon; Ali Farhadi (Commun. ACM, 2020)

Learning Neural Network Subspaces. - Mitchell Wortsman; Maxwell Horton; Carlos Guestrin; Ali Farhadi; Mohammad Rastegari (ICML, 2021)

Token Pooling in Vision Transformers. - Dmitrii Marin; Jen-Hao Rick Chang; Anurag Ranjan; Anish Prabhu; Mohammad Rastegari; Oncel Tuzel (CoRR, 2021)

LCS: Learning Compressible Subspaces for Adaptive Network Compression at Inference Time. - Elvis Nunez; Maxwell Horton; Anish Prabhu; Anurag Ranjan; Ali Farhadi; Mohammad Rastegari (CoRR, 2021)

SPIN: An Empirical Evaluation on Sharing Parameters of Isotropic Networks. - Chien-Yu Lin; Anish Prabhu; Thomas Merth; Sachin Mehta; Anurag Ranjan; Maxwell Horton; Mohammad Rastegari (ECCV (11), 2022)

DKM: Differentiable k-Means Clustering Layer for Neural Network Compression. - Minsik Cho; Keivan Alizadeh-Vahid; Saurabh Adya; Mohammad Rastegari (ICLR, 2022)

MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer. - Sachin Mehta; Mohammad Rastegari (ICLR, 2022)

Layer-Wise Data-Free CNN Compression. - Maxwell Horton; Yanzi Jin; Ali Farhadi; Mohammad Rastegari (ICPR, 2022)

CVNets: High Performance Library for Computer Vision. - Sachin Mehta; Farzad Abdolhosseini; Mohammad Rastegari (ACM Multimedia, 2022)

RangeAugment: Efficient Online Augmentation with Range Learning. - Sachin Mehta; Saeid Naderiparizi; Fartash Faghri; Maxwell Horton; Lailin Chen; Ali Farhadi; Oncel Tuzel; Mohammad Rastegari (CoRR, 2022)

DiCENet: Dimension-Wise Convolutions for Efficient Networks. - Sachin Mehta; Hannaneh Hajishirzi; Mohammad Rastegari (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Reinforce Data, Multiply Impact: Improved Model Accuracy and Robustness with Dataset Reinforcement. - Fartash Faghri; Hadi Pouransari; Sachin Mehta; Mehrdad Farajtabar; Ali Farhadi; Mohammad Rastegari; Oncel Tuzel (ICCV, 2023)

Token Pooling in Vision Transformers for Image Classification. - Dmitrii Marin; Jen-Hao Rick Chang; Anurag Ranjan; Anish Prabhu; Mohammad Rastegari; Oncel Tuzel (WACV, 2023)

On the Efficacy of Multi-scale Data Samplers for Vision Applications. - Elvis Nunez; Thomas Merth; Anish Prabhu; Mehrdad Farajtabar; Mohammad Rastegari; Sachin Mehta; Maxwell Horton (CoRR, 2023)

(Dynamic) Prompting might be all you need to repair Compressed LLMs. - Duc N. M. Hoang; Minsik Cho; Thomas Merth; Mohammad Rastegari; Zhangyang Wang (CoRR, 2023)

Diffusion Models as Masked Audio-Video Learners. - Elvis Nunez; Yanzi Jin; Mohammad Rastegari; Sachin Mehta; Maxwell Horton (CoRR, 2023)

Label-efficient Training of Small Task-specific Models by Leveraging Vision Foundation Models. - Raviteja Vemulapalli; Hadi Pouransari; Fartash Faghri; Sachin Mehta; Mehrdad Farajtabar; Mohammad Rastegari; Oncel Tuzel (CoRR, 2023)

Weight subcloning: direct initialization of transformers using larger pretrained ones. - Mohammad Samragh; Mehrdad Farajtabar; Sachin Mehta; Raviteja Vemulapalli; Fartash Faghri; Devang Naik; Oncel Tuzel; Mohammad Rastegari (CoRR, 2023)

LLM in a flash: Efficient Large Language Model Inference with Limited Memory. - Keivan Alizadeh; Iman Mirzadeh; Dmitry Belenko; Karen Khatamifard; Minsik Cho; Carlo C. del Mundo; Mohammad Rastegari; Mehrdad Farajtabar (CoRR, 2023)

Separable Self-attention for Mobile Vision Transformers. - Sachin Mehta; Mohammad Rastegari (Trans. Mach. Learn. Res., 2023)

LLM in a flash: Efficient Large Language Model Inference with Limited Memory. - Keivan Alizadeh; Iman Mirzadeh; Dmitry Belenko; S. Khatamifard; Minsik Cho; Carlo C. del Mundo; Mohammad Rastegari; Mehrdad Farajtabar (ACL (1), 2024)

SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding. - Haoxiang Wang 003; Pavan Kumar Anasosalu Vasu; Fartash Faghri; Raviteja Vemulapalli; Mehrdad Farajtabar; Sachin Mehta; Mohammad Rastegari; Oncel Tuzel; Hadi Pouransari (CVPR Workshops, 2024)

Speculative Streaming: Fast LLM Inference without Auxiliary Models. - Nikhil Bhendawade; Irina Belousova; Qichen Fu; Henry Mason; Mohammad Rastegari; Mahyar Najibi (ENLSP, 2024)

ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models. - Iman Mirzadeh; Keivan Alizadeh-Vahid; Sachin Mehta; Carlo C. del Mundo; Oncel Tuzel; Golnoosh Samei; Mohammad Rastegari; Mehrdad Farajtabar (ICLR, 2024)

KV-Runahead: Scalable Causal LLM Inference by Parallel Key-Value Cache Generation. - Minsik Cho; Mohammad Rastegari; Devang Naik (ICML, 2024)

Superposition Prompting: Improving and Accelerating Retrieval-Augmented Generation. - Thomas Merth; Qichen Fu; Mohammad Rastegari; Mahyar Najibi (ICML, 2024)

Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models. - Raviteja Vemulapalli; Hadi Pouransari; Fartash Faghri; Sachin Mehta; Mehrdad Farajtabar; Mohammad Rastegari; Oncel Tuzel (ICML, 2024)

eDKM: An Efficient and Accurate Train-Time Weight Clustering for Large Language Models. - Minsik Cho; Keivan Alizadeh-Vahid; Qichen Fu; Saurabh Adya; Carlo C. del Mundo; Mohammad Rastegari; Devang Naik; Peter Zatloukal (IEEE Comput. Archit. Lett., 2024)

OpenELM: An Efficient Language Model Family with Open Training and Inference Framework. - Sachin Mehta; Mohammad Hossein Sekhavat; Qingqing Cao; Maxwell Horton; Yanzi Jin; Chenfan Sun; Iman Mirzadeh; Mahyar Najibi; Dmitry Belenko; Peter Zatloukal; Mohammad Rastegari (CoRR, 2024)

CatLIP: CLIP-level Visual Recognition Accuracy with 2.7x Faster Pre-training on Web-scale Image-Text Data. - Sachin Mehta; Maxwell Horton; Fartash Faghri; Mohammad Hossein Sekhavat; Mahyar Najibi; Mehrdad Farajtabar; Oncel Tuzel; Mohammad Rastegari (CoRR, 2024)

LazyLLM: Dynamic Token Pruning for Efficient Long Context LLM Inference. - Qichen Fu; Minsik Cho; Thomas Merth; Sachin Mehta; Mohammad Rastegari; Mahyar Najibi (CoRR, 2024)

KV Prediction for Improved Time to First Token. - Maxwell Horton; Qingqing Cao; Chenfan Sun; Yanzi Jin; Sachin Mehta; Mohammad Rastegari; Moin Nabi (CoRR, 2024)

Bytes Are All You Need: Transformers Operating Directly On File Bytes. - Maxwell Horton; Sachin Mehta; Ali Farhadi; Mohammad Rastegari (Trans. Mach. Learn. Res., 2024)

CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement. - Mohammadreza Salehi; Mehrdad Farajtabar; Maxwell Horton; Fartash Faghri; Hadi Pouransari; Raviteja Vemulapalli; Oncel Tuzel; Ali Farhadi; Mohammad Rastegari; Sachin Mehta (Trans. Mach. Learn. Res., 2024)

SeedLM: Compressing LLM Weights into Seeds of Pseudo-Random Generators. - Rasoul Shafipour; David Harrison; Maxwell Horton; Jeffrey Marker; Houman Bedayat; Sachin Mehta; Mohammad Rastegari; Mahyar Najibi; Saman Naderiparizi (ICLR, 2025)