Hongyi Zhou
12 papers · 2022–2026 · 6 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+5 more ↓ Show less ↑
πΊοΈ Taxonomy Completionist (16) π§ Keyword Pioneer π Conference Polyglot (5) π Cross-Pollinator (13) π Renaissance Researcher (5)
π
Interdisciplinary Bridge
π
Grand Slam
π₯
Mega-Team
(22)
π
Century Club
(11)
β‘
Prolific Year
(6)
Conferences
CORL (4)
ICLR (2)
ICML (2)
NIPS (2)
AAAI (1)
ICCV (1)
Top co-authors
Keywords
deep reinforcement learning
(1)
zero-shot learning
(1)
sim-to-real transfer
(1)
black-box optimization
(1)
variational inference
(1)
knowledge distillation
(1)
depth estimation
(1)
monocular depth estimation
(1)
gaussian splatting
(1)
robot learning
(1)
behavior cloning
(1)
robot control
(1)
optical flow
(1)
diffusion model
(1)
mixture of expert
(1)
robotic control
(1)
diffusion distillation
(1)
articulated object
(1)
behavior learning
(1)
long context
(1)
Papers
HyperGLLM: An Efficient Framework for Endpoint Threat Detection via Hypergraph-Enhanced Large Language Models
AAAI 2026
MonoMobility: Zero-Shot 3D Mobility Analysis from Monocular Videos
ICCV 2025
IRIS: An Immersive Robot Interaction System
CORL 2025
FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Flow Models
CORL 2025
TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning
ICLR 2025
Demystifying the Paradox of Importance Sampling with an Estimated History-Dependent Behavior Policy in Off-Policy Evaluation
ICML 2025
Balancing Interference and Correlation in Spatial Experimental Designs: A Causal Graph Cut Approach
ICML 2025
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
NIPS 2024
A Retrospective on the Robot Air Hockey Challenge: Benchmarking Robust, Reliable, and Safe Learning Techniques for Real-world Robotics
NIPS 2024
Deep Black-Box Reinforcement Learning with Movement Primitives
CORL 2022