agentic learning ai lab
@agentic-ai-lab.bsky.social
AI research lab @nyu.edu led by Mengye Ren @mengyer.bsky.social | Partially run by students | Also find us @agentic_ai_lab on X
Babies learn to perceive the world and develop object and motion recognition in the early stages of life. Can a network bootstrap this understanding just by watching video? Check out the new blog post featuring our latest research on the Midway Network.
Research from CDS Asst Prof @mengyer.bsky.social and Courant PhD student Christopher Hoang shows how the Midway Network learns object recognition and motion jointly from raw video, using motion latents and a gating unit to model real dynamics.
nyudatascience.medium.com/watching-the...
nyudatascience.medium.com/watching-the...
Watching the World Go By: New AI Architecture Learns Motion and Meaning Simultaneously
A CDS/Courant study from Mengye Ren and Christopher Hoang teaches both object recognition and motion understanding directly from raw video.
nyudatascience.medium.com
December 19, 2025 at 9:25 PM
Babies learn to perceive the world and develop object and motion recognition in the early stages of life. Can a network bootstrap this understanding just by watching video? Check out the new blog post featuring our latest research on the Midway Network.
Excited to share our new research on local RL without backprop!
CDS Assistant Professor of Computer Science and Data Science @mengyer.bsky.social and co-author Frank Wu introduce ARQ, a new learning algorithm that skips backpropagation in favor of a more biologically plausible and computationally efficient method.
nyudatascience.medium.com/ditching-bac...
nyudatascience.medium.com/ditching-bac...
Ditching Backpropagation: A New Method Mimics How Brains Learn to Make Decisions
Mengye Ren and Frank Wu introduce a biologically-inspired learning algo that outperforms traditional methods without using backpropagation.
nyudatascience.medium.com
December 12, 2025 at 12:46 AM
Excited to share our new research on local RL without backprop!
Lab gathering at #NeurIPS2025. Proud of this year’s work and excited about the ideas we’re building toward next!
December 10, 2025 at 12:27 AM
Lab gathering at #NeurIPS2025. Proud of this year’s work and excited about the ideas we’re building toward next!
Reposted by agentic learning ai lab
Midway networks are cool: representation learning of motion and reconstruction jointly. I see similar motivation in V-JEPA 2 "AC", but I really like the execution here:
- hierarchical,
- backwards features with cross-attention.
arxiv.org/abs/2510.05558
C. Hoang, @mengyer.bsky.social
NYU
- hierarchical,
- backwards features with cross-attention.
arxiv.org/abs/2510.05558
C. Hoang, @mengyer.bsky.social
NYU
October 27, 2025 at 12:12 PM
Midway networks are cool: representation learning of motion and reconstruction jointly. I see similar motivation in V-JEPA 2 "AC", but I really like the execution here:
- hierarchical,
- backwards features with cross-attention.
arxiv.org/abs/2510.05558
C. Hoang, @mengyer.bsky.social
NYU
- hierarchical,
- backwards features with cross-attention.
arxiv.org/abs/2510.05558
C. Hoang, @mengyer.bsky.social
NYU
Check out our latest paper on representation learning from naturalistic videos →
How can we leverage naturalistic videos for visual SSL? Naturalistic, i.e. uncurated, videos are abundant and can emulate the egocentric perspective.
Our paper at ICLR 2025, PooDLe🐩, proposes a new SSL method to address the challenges of learning from naturalistic videos. 🧵
Our paper at ICLR 2025, PooDLe🐩, proposes a new SSL method to address the challenges of learning from naturalistic videos. 🧵
April 20, 2025 at 8:35 PM
Check out our latest paper on representation learning from naturalistic videos →
Reposted by agentic learning ai lab
New research by CDS MS student Amelia (Hui) Dai, PhD student Ryan Teehan, and Asst. Prof. Mengye Ren (@mengyer.bsky.social) shows that models’ accuracy on current events drops 20% over time—even when given the source articles. Presented at #NeurIPS2024.
nyudatascience.medium.com/language-mod...
nyudatascience.medium.com/language-mod...
Language Models’ Prediction of Current Events Degrades Over Time, Even With Latest Information
Language models lose accuracy on predicting events over time, even with access to up-to-date information.
nyudatascience.medium.com
January 22, 2025 at 4:57 PM
New research by CDS MS student Amelia (Hui) Dai, PhD student Ryan Teehan, and Asst. Prof. Mengye Ren (@mengyer.bsky.social) shows that models’ accuracy on current events drops 20% over time—even when given the source articles. Presented at #NeurIPS2024.
nyudatascience.medium.com/language-mod...
nyudatascience.medium.com/language-mod...