3 citations · 6 across the 11 of their papers we have counts for
13 papers
An Interpretable Linguistically-Grounded Analysis of Scene Saliency in Movie Screenplays
Uday Bindal, Ishaan Karan, Manan Garg +3
We investigate the factors affecting salience in movie screenplay by posing two research questions: 1. {\em Does Uniform Information Density (UID) predict salient scenes?} 2. {\em…
Learning from Teacher Continuations at Student States
Haojin Wang, Dylan Zhang, Huaibo Chen +8
We present OLIVE (OnLine InterVEntion). At each iteration, the evolving student policy generates a new prefix, the teacher continues it autoregressively, and the student is updated…
Perceive What Matters: Relevance-Driven Scheduling for Multimodal Streaming Perception
Dingcheng Huang, Xiaotong Zhang, Kamal Youcef-Toumi
In modern human-robot collaboration (HRC) applications, multiple perception modules jointly extract visual, auditory, and contextual cues to achieve comprehensive scene understandi…
Structured Multitask Gaussian Processes for Probabilistic Full-Body Human Motion Prediction
Jinger Chong, Xiaotong Zhang, Kamal Youcef-Toumi
Robots that share space with people need human motion predictions with reliable uncertainty, not just accurate means. This paper presents a structured multitask variational Gaussia…
VINA: Variational Invertible Neural Architectures
Shubhanshu Shekhar, Mohammad Javad Khojasteh, Ananya Acharya +2
The distinctive architectural features of normalizing flows (NFs), notably bijectivity and tractable Jacobians, make them well-suited for generative modeling. Invertible neural net…
Eye Movement Feature-Guided Signal De-Drifting in Electrooculography Systems
Lianming Hu, Xiaotong Zhang, Kamal Youcef-Toumi
Electrooculography (EOG) is widely used for gaze tracking in Human-Robot Collaboration (HRC). However, baseline drift caused by low-frequency noise significantly impacts the accura…
Bayesian Intention for Enhanced Human Robot Collaboration
Vanessa Hernandez-Cruz, Xiaotong Zhang, Kamal Youcef-Toumi
Predicting human intent is challenging yet essential to achieving seamless Human-Robot Collaboration (HRC). Many existing approaches fail to fully exploit the inherent relationship…
Relevance-driven Decision Making for Safer and More Efficient Human Robot Collaboration
Xiaotong Zhang, Dingcheng Huang, Kamal Youcef-Toumi
Human brain possesses the ability to effectively focus on important environmental components, which enhances perception, learning, reasoning, and decision-making. Inspired by this…
Relevance for Human Robot Collaboration
Xiaotong Zhang, Dean Huang, Kamal Youcef-Toumi
Inspired by the human ability to selectively focus on relevant information, this paper introduces relevance, a novel dimensionality reduction process for human-robot collaboration…
ISR: Invertible Symbolic Regression
Tony Tohme, Mohammad Javad Khojasteh, Mohsen Sadr +2
We introduce an Invertible Symbolic Regression (ISR) method. It is a machine learning technique that generates analytical relationships between inputs and outputs of a given datase…
Data-Driven Discovery of PDEs via the Adjoint Method
Mohsen Sadr, Tony Tohme, Kamal Youcef-Toumi
In this work, we present an adjoint-based method for discovering the underlying governing partial differential equations (PDEs) given data. The idea is to consider a parameterized…
How Does Perception Affect Safety: New Metrics and Strategy
Xiaotong Zhang, Jinger Chong, Kamal Youcef-Toumi
Perception serves as a critical component in the functionality of autonomous agents. However, the intricate relationship between perception metrics and robotic metrics remains uncl…
Enhanced Human-Robot Collaboration using Constrained Probabilistic Human-Motion Prediction
Aadi Kothari, Tony Tohme, Xiaotong Zhang +1
Human motion prediction is an essential step for efficient and safe human-robot collaboration. Current methods either purely rely on representing the human joints in some form of n…