2.3k citations · 2.5k across the 27 of their papers we have counts for
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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…
On the Opportunities and Risks of Foundation Models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli +111
AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.…
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…
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…
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…
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…