5 citations · 15 across the 7 of their papers we have counts for
7 papers
Multimodality as Supervision: Self-Supervised Specialization to the Test Environment via Multimodality
Kunal Pratap Singh, Ali Garjani, Rishubh Singh +6
Cross-modal learning, i.e., learning to predict one modality from another, is a fundamental mechanism for self-supervision via leveraging multimodality. Many practical applications…
SPOC: Imitating Shortest Paths in Simulation Enables Effective Navigation and Manipulation in the Real World
Kiana Ehsani, Tanmay Gupta, Rose Hendrix +11
Reinforcement learning (RL) with dense rewards and imitation learning (IL) with human-generated trajectories are the most widely used approaches for training modern embodied agents…
A General Purpose Supervisory Signal for Embodied Agents
Kunal Pratap Singh, Jordi Salvador, Luca Weihs +1
Training effective embodied AI agents often involves manual reward engineering, expert imitation, specialized components such as maps, or leveraging additional sensors for depth an…
Ask4Help: Learning to Leverage an Expert for Embodied Tasks
Kunal Pratap Singh, Luca Weihs, Alvaro Herrasti +3
Embodied AI agents continue to become more capable every year with the advent of new models, environments, and benchmarks, but are still far away from being performant and reliable…
BNAS v2: Learning Architectures for Binary Networks with Empirical Improvements
Dahyun Kim, Kunal Pratap Singh, Jonghyun Choi
Backbone architectures of most binary networks are well-known floating point (FP) architectures such as the ResNet family. Questioning that the architectures designed for FP networ…
Factorizing Perception and Policy for Interactive Instruction Following
Kunal Pratap Singh, Suvaansh Bhambri, Byeonghwi Kim +2
Performing simple household tasks based on language directives is very natural to humans, yet it remains an open challenge for AI agents. The 'interactive instruction following' ta…
Learning Architectures for Binary Networks
Dahyun Kim, Kunal Pratap Singh, Jonghyun Choi
Backbone architectures of most binary networks are well-known floating point architectures such as the ResNet family. Questioning that the architectures designed for floating point…