Hongyi Zhou
14 papers · 2022–2026 · 7 venues · across top CS/AI venues
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Achievements
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π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Silver πΊοΈ Taxonomy Completionist (30) π₯ Mega-Team Β· Squad π Grand Slam
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Prolific Year Β· Productive
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Renaissance Researcher
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Century Club Β· Bronze
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Research topics
Keywords
mean squared error
(2)
episodic reinforcement learning
(2)
diffusion model
(2)
robot learning
(2)
movement primitive
(2)
black-box optimization
(1)
sim-to-real transfer
(1)
zero-shot learning
(1)
monocular depth estimation
(1)
depth estimation
(1)
gaussian splatting
(1)
imitation learning
(1)
behavior cloning
(1)
importance sampling
(1)
off-policy learning
(1)
knowledge distillation
(1)
variance reduction
(1)
reconstruction error
(1)
optical flow
(1)
robot control
(1)
Papers
A Difference-in-Difference Approach to Detecting AI-Generated Images
CVPR 2026
HyperGLLM: An Efficient Framework for Endpoint Threat Detection via Hypergraph-Enhanced Large Language Models
AAAI 2026
NAMI: Efficient Image Generation via Bridged Progressive Rectified Flow Transformers
CVPR 2026
Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach
ICML 2025
Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation
ICML 2025
FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Flow Models
CoRL 2025
IRIS: An Immersive Robot Interaction System
CoRL 2025
MonoMobility: Zero-Shot 3D Mobility Analysis from Monocular Videos
ICCV 2025
TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning
ICLR 2025
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics
NeurIPS 2024
MaIL: Improving Imitation Learning with Selective State Space Models
CoRL 2024
Open the Black Box: Step-based Policy Updates for Temporally-Correlated Episodic Reinforcement Learning
ICLR 2024
Variational Distillation of Diffusion Policies into Mixture of Experts
NeurIPS 2024
Deep Black-Box Reinforcement Learning with Movement Primitives
CoRL 2022