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Mengye Ren

Assistant Professor

Mengye Ren is an assistant professor of computer science and data science at New York University (NYU). He runs the Agentic Learning AI Lab. Before joining NYU, he was a visiting faculty researcher at Google Brain Toronto working with Prof. Geoffrey Hinton. From 2017 to 2021, he was a senior research scientist at Uber Advanced Technologies Group (ATG) and Waabi, working on self-driving vehicles. He received PhD in Computer Science from the University of Toronto, advised by Prof. Richard Zemel and Prof. Raquel Urtasun. His research focuses on making machine learning more natural and human-like, in order for AIs to continually learn, adapt, and reason in naturalistic environments.

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Mengye Ren's Papers

Local Reinforcement Learning with Action-Conditioned Root Mean Squared Q-Functions

Local Reinforcement Learning with Action-Conditioned Root Mean Squared Q-Functions

Frank (Zequan) Wu and Mengye Ren

Midway Network: Learning Representations for Recognition and Motion from Latent Dynamics

Midway Network: Learning Representations for Recognition and Motion from Latent Dynamics

Chris Hoang and Mengye Ren

StreamMem: Query-Agnostic KV Cache Memory for Streaming Video Understanding

StreamMem: Query-Agnostic KV Cache Memory for Streaming Video Understanding

Yanlai Yang, Zhuokai Zhao, Satya Narayan Shukla, Aashu Singh, Shlok Kumar Mishra, Lizhu Zhang, and Mengye Ren

Context Tuning for In-Context Optimization

Context Tuning for In-Context Optimization

Jack Lu, Ryan Teehan, Zhenbang Yang, and Mengye Ren

Discrete JEPA: Learning Discrete Token Representations without Reconstruction

Discrete JEPA: Learning Discrete Token Representations without Reconstruction

Junyeob Baek, Hosung Lee, Chris Hoang, Mengye Ren, and Sungjin Ahn

Replay Can Provably Increase Forgetting

Replay Can Provably Increase Forgetting

Yasaman Mahdaviyeh, James Lucas, Mengye Ren, Andreas S. Tolias, Richard Zemel, and Toniann Pitassi

Memory Storyboard: Leveraging Temporal Segmentation for Streaming Self-Supervised Learning from Egocentric Videos

Memory Storyboard: Leveraging Temporal Segmentation for Streaming Self-Supervised Learning from Egocentric Videos

Yanlai Yang and Mengye Ren

Are LLMs Prescient? A Continuous Evaluation using Daily News as Oracle

Are LLMs Prescient? A Continuous Evaluation using Daily News as Oracle

Amelia (Hui) Dai, Ryan Teehan, and Mengye Ren

PooDLe: Pooled and Dense Self-Supervised Learning from Naturalistic Videos

PooDLe: Pooled and Dense Self-Supervised Learning from Naturalistic Videos

Alex N. Wang, Chris Hoang, Yuwen Xiong, Yann LeCun, and Mengye Ren

ProCreate, Don't Reproduce! Propulsive Energy Diffusion for Creative Generation

ProCreate, Don't Reproduce! Propulsive Energy Diffusion for Creative Generation

Jack Lu, Ryan Teehan, and Mengye Ren

Integrating Present and Past in Unsupervised Continual Learning

Integrating Present and Past in Unsupervised Continual Learning

Yipeng Zhang, Laurent Charlin, Richard S. Zemel, and Mengye Ren

CoLLEGe: Concept Embedding Generation for Large Language Models

CoLLEGe: Concept Embedding Generation for Large Language Models

Ryan Teehan, Brenden M. Lake, and Mengye Ren

Reawakening Knowledge: Anticipatory Recovery from Catastrophic Interference via Structured Training

Reawakening Knowledge: Anticipatory Recovery from Catastrophic Interference via Structured Training

Yanlai Yang, Matt Jones, Michael C. Mozer, and Mengye Ren

Self-Supervised Learning of Video Representations from a Child's Perspective

Self-Supervised Learning of Video Representations from a Child's Perspective

A. Emin Orhan, Wentao Wang, Alex N. Wang, Mengye Ren, and Brenden M. Lake

Learning and Forgetting Unsafe Examples in Large Language Models

Learning and Forgetting Unsafe Examples in Large Language Models

Jiachen Zhao, Zhun Deng, David Madras, James Zou, and Mengye Ren

LifelongMemory: Leveraging LLMs for Answering Queries in Long-form Egocentric Videos

LifelongMemory: Leveraging LLMs for Answering Queries in Long-form Egocentric Videos

Ying Wang, Yanlai Yang, and Mengye Ren