Exploring Models and Data for Image Question Answering. - Mengye Ren; Ryan Kiros; Richard S. Zemel (NIPS, 2015)

Image Question Answering: A Visual Semantic Embedding Model and a New Dataset. - Mengye Ren; Ryan Kiros; Richard S. Zemel (CoRR, 2015)

End-to-End Instance Segmentation and Counting with Recurrent Attention. - Mengye Ren; Richard S. Zemel (CoRR, 2016)

End-to-End Instance Segmentation with Recurrent Attention. - Mengye Ren; Richard S. Zemel (CVPR, 2017)

Normalizing the Normalizers: Comparing and Extending Network Normalization Schemes. - Mengye Ren; Renjie Liao; Raquel Urtasun; Fabian H. Sinz; Richard S. Zemel (ICLR (Poster), 2017)

The Reversible Residual Network: Backpropagation Without Storing Activations. - Aidan N. Gomez; Mengye Ren; Raquel Urtasun; Roger B. Grosse (NIPS, 2017)

SBNet: Sparse Blocks Network for Fast Inference. - Mengye Ren; Andrei Pokrovsky; Bin Yang 021; Raquel Urtasun (CVPR, 2018)

Meta-Learning for Semi-Supervised Few-Shot Classification. - Mengye Ren; Eleni Triantafillou; Sachin Ravi; Jake Snell; Kevin Swersky; Joshua B. Tenenbaum; Hugo Larochelle; Richard S. Zemel (ICLR (Poster), 2018)

Understanding Short-Horizon Bias in Stochastic Meta-Optimization. - Yuhuai Wu; Mengye Ren; Renjie Liao; Roger B. Grosse (ICLR (Poster), 2018)

Learning to Reweight Examples for Robust Deep Learning. - Mengye Ren; Wenyuan Zeng; Bin Yang 021; Raquel Urtasun (ICML, 2018)

Identifying Unknown Instances for Autonomous Driving. - Kelvin Wong; Shenlong Wang; Mengye Ren; Ming Liang; Raquel Urtasun (CoRL, 2019)

Graph HyperNetworks for Neural Architecture Search. - Chris Zhang 001; Mengye Ren; Raquel Urtasun (ICLR (Poster), 2019)

Jointly Learnable Behavior and Trajectory Planning for Self-Driving Vehicles. - Abbas Sadat; Mengye Ren; Andrei Pokrovsky; Yen-Chen Lin; Ersin Yumer; Raquel Urtasun (IROS, 2019)

Incremental Few-Shot Learning with Attention Attractor Networks. - Mengye Ren; Renjie Liao; Ethan Fetaya; Richard S. Zemel (NeurIPS, 2019)

Deformable Filter Convolution for Point Cloud Reasoning. - Yuwen Xiong; Mengye Ren; Renjie Liao; Kelvin Wong; Raquel Urtasun (CoRR, 2019)

Learning to Remember from a Multi-Task Teacher. - Yuwen Xiong; Mengye Ren; Raquel Urtasun (CoRR, 2019)

Learning to Communicate and Correct Pose Errors. - Nicholas Vadivelu; Mengye Ren; James Tu; Jingkang Wang; Raquel Urtasun (CoRL, 2020)

Physically Realizable Adversarial Examples for LiDAR Object Detection. - James Tu; Mengye Ren; Sivabalan Manivasagam; Ming Liang; Bin Yang 021; Richard Du; Frank Cheng; Raquel Urtasun (CVPR, 2020)

Perceive, Predict, and Plan: Safe Motion Planning Through Interpretable Semantic Representations. - Abbas Sadat; Sergio Casas 002; Mengye Ren; Xinyu Wu; Pranaab Dhawan; Raquel Urtasun (ECCV (23), 2020)

Multi-Agent Routing Value Iteration Network. - Quinlan Sykora; Mengye Ren; Raquel Urtasun (ICML, 2020)

End-to-end Contextual Perception and Prediction with Interaction Transformer. - Lingyun Luke Li; Bin Yang 021; Ming Liang; Wenyuan Zeng; Mengye Ren; Sean Segal; Raquel Urtasun (IROS, 2020)

LoCo: Local Contrastive Representation Learning. - Yuwen Xiong; Mengye Ren; Raquel Urtasun (NeurIPS, 2020)

Physically Realizable Adversarial Examples for LiDAR Object Detection. - James Tu; Mengye Ren; Siva Manivasagam; Ming Liang; Bin Yang 021; Richard Du; Frank Cheng; Raquel Urtasun (CoRR, 2020)

Flexible Few-Shot Learning with Contextual Similarity. - Mengye Ren; Eleni Triantafillou; Kuan-Chieh Wang; James Lucas; Jake Snell; Xaq Pitkow; Andreas S. Tolias; Richard S. Zemel (CoRR, 2020)

Just Label What You Need: Fine-Grained Active Selection for P&P through Partially Labeled Scenes. - Sean Segal; Nishanth Kumar; Sergio Casas 002; Wenyuan Zeng; Mengye Ren; Jingkang Wang; Raquel Urtasun (CoRL, 2021)

Exploring Adversarial Robustness of Multi-sensor Perception Systems in Self Driving. - James Tu; Huichen Li; Xinchen Yan; Mengye Ren; Yun Chen 014; Ming Liang; Eilyan Bitar; Ersin Yumer; Raquel Urtasun (CoRL, 2021)

SceneGen: Learning To Generate Realistic Traffic Scenes. - Shuhan Tan; Kelvin Wong; Shenlong Wang; Sivabalan Manivasagam; Mengye Ren; Raquel Urtasun (CVPR, 2021)

AdvSim: Generating Safety-Critical Scenarios for Self-Driving Vehicles. - Jingkang Wang; Ava Pun; James Tu; Sivabalan Manivasagam; Abbas Sadat; Sergio Casas 002; Mengye Ren; Raquel Urtasun (CVPR, 2021)

Adversarial Attacks On Multi-Agent Communication. - James Tu; Tsun-Hsuan Wang; Jingkang Wang; Sivabalan Manivasagam; Mengye Ren; Raquel Urtasun (ICCV, 2021)

Self-Supervised Representation Learning from Flow Equivariance. - Yuwen Xiong; Mengye Ren; Wenyuan Zeng; Raquel Urtasun Waabi (ICCV, 2021)

Theoretical bounds on estimation error for meta-learning. - James Lucas; Mengye Ren; Irene Raissa Kameni; Toniann Pitassi; Richard S. Zemel (ICLR, 2021)

Wandering within a world: Online contextualized few-shot learning. - Mengye Ren; Michael Louis Iuzzolino; Michael Curtis Mozer; Richard S. Zemel (ICLR, 2021)

SketchEmbedNet: Learning Novel Concepts by Imitating Drawings. - Alexander Wang; Mengye Ren; Richard S. Zemel (ICML, 2021)

Perceive, Attend, and Drive: Learning Spatial Attention for Safe Self-Driving. - Bob Wei; Mengye Ren; Wenyuan Zeng; Ming Liang; Bin Yang 021; Raquel Urtasun (ICRA, 2021)

Cost-Efficient Online Hyperparameter Optimization. - Jingkang Wang; Mengye Ren; Ilija Bogunovic; Yuwen Xiong; Raquel Urtasun (CoRR, 2021)

Just Label What You Need: Fine-Grained Active Selection for Perception and Prediction through Partially Labeled Scenes. - Sean Segal; Nishanth Kumar; Sergio Casas 002; Wenyuan Zeng; Mengye Ren; Jingkang Wang; Raquel Urtasun (CoRR, 2021)

Online Unsupervised Learning of Visual Representations and Categories. - Mengye Ren; Tyler R. Scott; Michael L. Iuzzolino; Michael C. Mozer; Richard S. Zemel (CoRR, 2021)

Rethinking Closed-Loop Training for Autonomous Driving. - Chris Zhang 001; Runsheng Guo 003; Wenyuan Zeng; Yuwen Xiong; Binbin Dai; Rui Hu 001; Mengye Ren; Raquel Urtasun (ECCV (39), 2022)

Learning to Reason With Relational Abstractions. - Andrew Joohun Nam; Mengye Ren; Chelsea Finn; James L. McClelland (CoRR, 2022)

Gaussian-Bernoulli RBMs Without Tears. - Renjie Liao; Simon Kornblith; Mengye Ren; David J. Fleet; Geoffrey E. Hinton (CoRR, 2022)

Open-world Machine Learning with Limited Labeled Data - Mengye Ren (2022)

Multitask Learning Via Interleaving: A Neural Network Investigation. - David Mayo; Tyler R. Scott; Mengye Ren; Gamaledin Elsayed; Katherine L. Hermann; Matt Jones 001; Michael Mozer (CogSci, 2023)

Towards Unsupervised Object Detection from LiDAR Point Clouds. - Lunjun Zhang; Anqi Joyce Yang; Yuwen Xiong; Sergio Casas 002; Bin Yang 021; Mengye Ren; Raquel Urtasun (CVPR, 2023)

Learning in temporally structured environments. - Matt Jones 001; Tyler R. Scott; Mengye Ren; Gamaleldin Fathy Elsayed; Katherine L. Hermann; David Mayo; Michael Curtis Mozer (ICLR, 2023)

Scaling Forward Gradient With Local Losses. - Mengye Ren; Simon Kornblith; Renjie Liao; Geoffrey E. Hinton (ICLR, 2023)

BIM: Block-Wise Self-Supervised Learning with Masked Image Modeling. - Yixuan Luo; Mengye Ren; Sai Qian Zhang (CoRR, 2023)

LifelongMemory: Leveraging LLMs for Answering Queries in Egocentric Videos. - Ying Wang 063; Yanlai Yang; Mengye Ren (CoRR, 2023)

Integrating Present and Past in Unsupervised Continual Learning. - Yipeng Zhang; Laurent Charlin; Richard S. Zemel; Mengye Ren (CoLLAs, 2024)

ProCreate, Don't Reproduce! Propulsive Energy Diffusion for Creative Generation. - Jack Lu; Ryan Teehan; Mengye Ren (ECCV (60), 2024)

Learning and Forgetting Unsafe Examples in Large Language Models. - Jiachen Zhao; Zhun Deng; David Madras; James Zou 001; Mengye Ren (ICML, 2024)

Reawakening knowledge: Anticipatory recovery from catastrophic interference via structured training. - Yanlai Yang; Matt Jones 001; Michael C. Mozer; Mengye Ren (NeurIPS, 2024)

Self-supervised learning of video representations from a child's perspective. - A. Emin Orhan; Wentao Wang; Alex N. Wang; Mengye Ren; Brenden M. Lake (CoRR, 2024)

CoLLEGe: Concept Embedding Generation for Large Language Models. - Ryan Teehan; Brenden M. Lake; Mengye Ren (CoRR, 2024)

PooDLe: Pooled and dense self-supervised learning from naturalistic videos. - Alex N. Wang; Christopher Hoang; Yuwen Xiong; Yann LeCun; Mengye Ren (CoRR, 2024)

Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle. - Hui Dai; Ryan Teehan; Mengye Ren (CoRR, 2024)

PooDLe🐩: Pooled and dense self-supervised learning from naturalistic videos. - Alex N. Wang; Christopher Hoang; Yuwen Xiong; Yann LeCun; Mengye Ren (ICLR, 2025)

A General Framework for Inference-time Scaling and Steering of Diffusion Models. - Raghav Singhal; Zachary Horvitz; Ryan Teehan; Mengye Ren; Zhou Yu; Kathleen McKeown; Rajesh Ranganath (CoRR, 2025)

Memory Storyboard: Leveraging Temporal Segmentation for Streaming Self-Supervised Learning from Egocentric Videos. - Yanlai Yang; Mengye Ren (CoRR, 2025)

Replay Can Provably Increase Forgetting. - Yasaman Mahdaviyeh; James Lucas; Mengye Ren; Andreas S. Tolias; Richard S. Zemel; Toniann Pitassi (CoRR, 2025)

Discrete JEPA: Learning Discrete Token Representations without Reconstruction. - Junyeob Baek; Hosung Lee; Christopher Hoang; Mengye Ren; Sungjin Ahn (CoRR, 2025)

Context Tuning for In-Context Optimization. - Jack Lu; Ryan Teehan; Zhenbang Yang; Mengye Ren (CoRR, 2025)

StreamMem: Query-Agnostic KV Cache Memory for Streaming Video Understanding. - Yanlai Yang; Zhuokai Zhao; Satya Narayan Shukla; Aashu Singh; Shlok Kumar Mishra; Lizhu Zhang; Mengye Ren (CoRR, 2025)