26 citations · 100 across the 23 of their papers we have counts for
8 papers · 1 filter
A Benchmark for Modeling Violation-of-Expectation in Physical Reasoning Across Event Categories
Arijit Dasgupta, Jiafei Duan, Marcelo H. Ang +4
Recent work in computer vision and cognitive reasoning has given rise to an increasing adoption of the Violation-of-Expectation (VoE) paradigm in synthetic datasets. Inspired by in…
AVoE: A Synthetic 3D Dataset on Understanding Violation of Expectation for Artificial Cognition
Arijit Dasgupta, Jiafei Duan, Marcelo H. Ang +1
Recent work in cognitive reasoning and computer vision has engendered an increasing popularity for the Violation-of-Expectation (VoE) paradigm in synthetic datasets. Inspired by wo…
TDAM: Top-Down Attention Module for Contextually Guided Feature Selection in CNNs
Shantanu Jaiswal, Basura Fernando, Cheston Tan
Attention modules for Convolutional Neural Networks (CNNs) are an effective method to enhance performance on multiple computer-vision tasks. While existing methods appropriately mo…
PIP: Physical Interaction Prediction via Mental Simulation with Span Selection
Jiafei Duan, Samson Yu, Soujanya Poria +2
Accurate prediction of physical interaction outcomes is a crucial component of human intelligence and is important for safe and efficient deployments of robots in the real world. W…
SPACE: A Simulator for Physical Interactions and Causal Learning in 3D Environments
Jiafei Duan, Samson Yu Bai Jian, Cheston Tan
Recent advancements in deep learning, computer vision, and embodied AI have given rise to synthetic causal reasoning video datasets. These datasets facilitate the development of AI…
A nonlinear hidden layer enables actor-critic agents to learn multiple paired association navigation
M Ganesh Kumar, Cheston Tan, Camilo Libedinsky +2
Navigation to multiple cued reward locations has been increasingly used to study rodent learning. Though deep reinforcement learning agents have been shown to be able to learn the…
One-shot learning of paired association navigation with biologically plausible schemas
M Ganesh Kumar, Cheston Tan, Camilo Libedinsky +2
After learning a multiple paired-association (MPA) navigation task, rodents can rapidly learn new cue-location associations after a single exposure, a phenomenon proposed to be fac…
A Survey of Embodied AI: From Simulators to Research Tasks
Jiafei Duan, Samson Yu, Hui Li Tan +2
There has been an emerging paradigm shift from the era of "internet AI" to "embodied AI", where AI algorithms and agents no longer learn from datasets of images, videos or text cur…