activity
20172022
most citedGenerating Interactive Worlds with Text

3 citations · 9 across the 7 of their papers we have counts for

collaborators

14 papers

cs.RO20222 cited

Eliciting Compatible Demonstrations for Multi-Human Imitation Learning

Kanishk Gandhi, Siddharth Karamcheti, Madeline Liao +1

Imitation learning from human-provided demonstrations is a strong approach for learning policies for robot manipulation. While the ideal dataset for imitation learning is homogenou…

cs.RO20212 cited

LILA: Language-Informed Latent Actions

Siddharth Karamcheti, Megha Srivastava, Percy Liang +1

We introduce Language-Informed Latent Actions (LILA), a framework for learning natural language interfaces in the context of human-robot collaboration. LILA falls under the shared…

cs.CL2021

Mind Your Outliers! Investigating the Negative Impact of Outliers on Active Learning for Visual Question Answering

Siddharth Karamcheti, Ranjay Krishna, Li Fei-Fei +1

Active learning promises to alleviate the massive data needs of supervised machine learning: it has successfully improved sample efficiency by an order of magnitude on traditional…

cs.AI2021

Targeted Data Acquisition for Evolving Negotiation Agents

Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar +1

Successful negotiators must learn how to balance optimizing for self-interest and cooperation. Yet current artificial negotiation agents often heavily depend on the quality of the…

cs.RO2021

Learning Visually Guided Latent Actions for Assistive Teleoperation

Siddharth Karamcheti, Albert J. Zhai, Dylan P. Losey +1

It is challenging for humans -- particularly those living with physical disabilities -- to control high-dimensional, dexterous robots. Prior work explores learning embedding functi…

cs.CL2021

ELLA: Exploration through Learned Language Abstraction

Suvir Mirchandani, Siddharth Karamcheti, Dorsa Sadigh

Building agents capable of understanding language instructions is critical to effective and robust human-AI collaboration. Recent work focuses on training these agents via reinforc…