3 papers
cs.AI2025
Grounding Multimodal LLMs to Embodied Agents that Ask for Help with Reinforcement Learning
Ram Ramrakhya, Matthew Chang, Xavier Puig +3
Embodied agents operating in household environments must interpret ambiguous and under-specified human instructions. A capable household robot should recognize ambiguity and ask re…
cs.RO2024
PARTNR: A Benchmark for Planning and Reasoning in Embodied Multi-agent Tasks
Matthew Chang, Gunjan Chhablani, Alexander Clegg +17
We present a benchmark for Planning And Reasoning Tasks in humaN-Robot collaboration (PARTNR) designed to study human-robot coordination in household activities. PARTNR tasks exhib…
cs.AI2024
GOAT-Bench: A Benchmark for Multi-Modal Lifelong Navigation
Mukul Khanna, Ram Ramrakhya, Gunjan Chhablani +7
The Embodied AI community has made significant strides in visual navigation tasks, exploring targets from 3D coordinates, objects, language descriptions, and images. However, these…