Mengye Ren
Assistant Professor of Computer Science and Data Science
Studies machine learning and computer vision for agents that learn continually from few examples and from naturalistic visual experience.
Mengye Ren's lab at NYU works in Machine Learning. 34 papers since 2023, 19 at top venues, mostly ICLR and ICML. 6 PhD students and 9 master's students. 5 alumni. Applications close .
At a glance
- papers, 2023–2026
- 9/ year
- at T1 venues
- 56%
- PhD students
- 6
- MS students
- 9
- alumni listed
- 5
Papers by yearfrom the lab homepage, 2023–2026
- 16 papers2026 · T1 10 · collecting
- 7 papers2025 · T1 3
- 6 papers2024 · T1 3
- 5 papers2023 · T1 3
T1 venuesOtherVenues: ICLR, ICML, NeurIPS, CVPR, ECCV
Research focuspaper titles that use each topic's words
- agents2 papers
- experience0 papers
- learn0 papers
- courant0 papers
- studies machine0 papers
Paper list
From the lab homepage.
202616 papers
- ICML AI Forecasting WorkshopAlive and predicting: A live evaluation of multi-step forecasting agents
- CVPR ActiVis WorkshopCANON: Canonical observation pretraining for visuomotor control
- ICML (T1)Context tuning for in-context optimization
- COLMHyperThink: Text-to-parameter hypernetworks for efficient reasoning
- ICLR the Workshop on World Models: Understanding, Modelling and ScalingLaMo: A latent motion world model for long-horizon prediction
- ICLR (T1)Local reinforcement learning with action-conditioned root mean squared Q-functions
- EMNLP (T1)Memory Transfer Learning: How memories are transferred across domains in coding agents
- ICLR (T1)Midway Network: Learning representations for recognition and motion from latent dynamics
- NeurIPS (T1)On the geometry and latent-space composition of hypernetwork-generated LoRAs
- NeurIPS (T1)Probabilistic recursive reasoning
- NeurIPS (T1)Seeking the unfamiliar but memorable: Conceptual creativity as meta-learning
- ICLR (T1)SkillFactory: Self-distillation for learning cognitive behaviors
20257 papers
- ICML (T1)A general framework for inference-time scaling and steering of diffusion models
- ICML (T1)Are LLMs prescient? A continuous evaluation using daily news as the oracle
- WoTok: Workshop on Tokenization at ICMLDiscrete JEPA: Learning discrete token representations without reconstruction
- CoLLAsMemory Storyboard: Leveraging temporal segmentation for streaming self-supervised learning from egocentric videos
- NeurIPS WorkshopOpinion: Learning intuitive physics may require more than visual data
- ICLR (T1)PooDLe: Pooled and dense self-supervised learning from naturalistic videos
- CoLLAsReplay can provably increase forgetting
20246 papers
- COLMCoLLEGe: Concept embedding generation for large language models
- CoLLAsIntegrating present and past in unsupervised continual learning
- ICML (T1)Learning and forgetting unsafe examples in large language models
- ECCV (T1)ProCreate, don’t reproduce! Propulsive energy diffusion for creative generation
- NeurIPS (T1)Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training
- CogSciSelf-supervised learning of video representations from a child’s perspective
20235 papers
- International Ego4D Workshop at CVPREgocentric video comprehension via large language model inner speech
- ICLR (T1)Learning in temporally structured environments
- CogSciMultitask learning via interleaving: A neural network investigation
- ICLR (T1)Scaling forward gradient with local losses
- CVPR (T1)Towards unsupervised object detection from LiDAR point clouds
Where alumni went5 listed
Apply to NYUFall 2027
Computer Science PhD (Courant / Tandon)
- Round
- Single round (December)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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- Members
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