289 citations · 443 across the 8 of their papers we have counts for
8 papers
Human-Centered Planning
Yuliang Li, Nitin Kamra, Ruta Desai +1
LLMs have recently made impressive inroads on tasks whose output is structured, such as coding, robotic planning and querying databases. The vision of creating AI-powered personal…
Pretrained Language Models as Visual Planners for Human Assistance
Dhruvesh Patel, Hamid Eghbalzadeh, Nitin Kamra +3
In our pursuit of advancing multi-modal AI assistants capable of guiding users to achieve complex multi-step goals, we propose the task of "Visual Planning for Assistance (VPA)". G…
Effective Baselines for Multiple Object Rearrangement Planning in Partially Observable Mapped Environments
Engin Tekin, Elaheh Barati, Nitin Kamra +1
Many real-world tasks, from house-cleaning to cooking, can be formulated as multi-object rearrangement problems -- where an agent needs to get specific objects into appropriate goa…
Action Dynamics Task Graphs for Learning Plannable Representations of Procedural Tasks
Weichao Mao, Ruta Desai, Michael Louis Iuzzolino +1
Given video demonstrations and paired narrations of an at-home procedural task such as changing a tire, we present an approach to extract the underlying task structure -- relevant…
Multi-agent Trajectory Prediction with Fuzzy Query Attention
Nitin Kamra, Hao Zhu, Dweep Trivedi +2
Trajectory prediction for scenes with multiple agents and entities is a challenging problem in numerous domains such as traffic prediction, pedestrian tracking and path planning. W…
PolSIRD: Modeling Epidemic Spread under Intervention Policies
Nitin Kamra, Yizhou Zhang, Sirisha Rambhatla +2
Epidemic spread in a population is traditionally modeled via compartmentalized models which represent the free evolution of disease in absence of any intervention policies. In addi…
DynGEM: Deep Embedding Method for Dynamic Graphs
Palash Goyal, Nitin Kamra, Xinran He +1
Embedding large graphs in low dimensional spaces has recently attracted significant interest due to its wide applications such as graph visualization, link prediction and node clas…
Deep Generative Dual Memory Network for Continual Learning
Nitin Kamra, Umang Gupta, Yan Liu
Despite advances in deep learning, neural networks can only learn multiple tasks when trained on them jointly. When tasks arrive sequentially, they lose performance on previously l…