Rami Al‐Rfou

Computer Science · Physical Sciences

23h-index6.4kcitations61works3.22yr avg
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Research Topics

Topic Modeling(35), Natural Language Processing Techniques(32), Speech Recognition and Synthesis(8), Text Readability and Simplification(8), Autonomous Vehicle Technology and Safety(7)

Publications61 total

Scaling Laws of Motion Forecasting and Planning -- Technical Report
arXiv (Cornell University)·2025Open Access
MoST: Multi-modality Scene Tokenization for Motion Prediction
2024· 9 cited
Scaling Motion Forecasting Models with Ensemble Distillation
2024· 3 cited
MoST: Multi-modality Scene Tokenization for Motion Prediction
arXiv (Cornell University)·2024· 1 citedOpen Access
Scaling Motion Forecasting Models with Ensemble Distillation
arXiv (Cornell University)·2024Open Access
Let Your Graph Do the Talking: Encoding Structured Data for LLMs
arXiv (Cornell University)·2024· 6 citedOpen Access
MotionLM: Multi-Agent Motion Forecasting as Language Modeling
2023· 72 cited
MotionLM: Multi-Agent Motion Forecasting as Language Modeling
arXiv (Cornell University)·2023· 1 citedOpen Access
Wayformer: Motion Forecasting via Simple & Efficient Attention Networks
2023· 193 cited
Fine-Tashkeel: Fine-Tuning Byte-Level Models for Accurate Arabic Text Diacritization
2023· 4 cited
Fine-Tashkeel: Finetuning Byte-Level Models for Accurate Arabic Text Diacritization
arXiv (Cornell University)·2023Open Access
Wayformer: Motion Forecasting via Simple & Efficient Attention Networks
arXiv (Cornell University)·2022· 6 citedOpen Access
VN-Transformer: Rotation-Equivariant Attention for Vector Neurons
arXiv (Cornell University)·2022· 11 citedOpen Access
Narrowing the Coordinate-frame Gap in Behavior Prediction Models: Distillation for Efficient and Accurate Scene-centric Motion Forecasting
arXiv (Cornell University)·2022Open Access
Narrowing the coordinate-frame gap in behavior prediction models: Distillation for efficient and accurate scene-centric motion forecasting
2022 International Conference on Robotics and Automation (ICRA)·2022· 10 cited
SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)·2022· 166 citedOpen Access
ByT5: Towards a Token-Free Future with Pre-trained Byte-to-Byte Models
Transactions of the Association for Computational Linguistics·2022· 218 citedOpen Access
SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer
arXiv (Cornell University)·2021Open Access
nmT5 -- Is parallel data still relevant for pre-training massively multilingual language models?
arXiv (Cornell University)·2021· 1 citedOpen Access
ByT5: Towards a token-free future with pre-trained byte-to-byte models
arXiv (Cornell University)·2021· 69 citedOpen Access
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Frequent Co-authors

Noah Constant(12), Bryan Perozzi(12), Steven Skiena(10), Linting Xue(6), Mihir Kale(6), Aditya Barua(6), Vivek Kulkarni(5), Brian Strope(5), Kratarth Goel(5), Aditya Siddhant(4), Colin Raffel(4), Nigamaa Nayakanti(4), Benjamin Sapp(4), Adam P. Roberts(3), Matthew Henderson(3), Yun-Hsuan Sung(3), Aurick Zhou(3), Khaled S. Refaat(3), Mandy Guo(3), Yinfei Yang(3)