36 citations · 40 across the 5 of their papers we have counts for
5 papers
Creating and Repairing Robot Programs in Open-World Domains
Claire Schlesinger, Arjun Guha, Joydeep Biswas
Using Large Language Models (LLMs) to produce robot programs from natural language has allowed for robot systems that can complete a higher diversity of tasks. However, LLM-generat…
NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals
Jaden Fiotto-Kaufman, Alexander R. Loftus, Eric Todd +17
We introduce NNsight and NDIF, technologies that work in tandem to enable scientific study of the representations and computations learned by very large neural networks. NNsight is…
Robo-Instruct: Simulator-Augmented Instruction Alignment For Finetuning Code LLMs
Zichao Hu, Junyi Jessy Li, Arjun Guha +1
Code LLMs have shown promising results with converting tasks in natural language to programs that can be executed by service robots. We are interested in finetuning small, speciali…
Understanding How CodeLLMs (Mis)Predict Types with Activation Steering
Francesca Lucchetti, Arjun Guha
Large Language Models (LLMs) are widely used by software engineers for programming tasks. However, research shows that LLMs often lack a deep understanding of program semantics. Ev…
Deploying and Evaluating LLMs to Program Service Mobile Robots
Zichao Hu, Francesca Lucchetti, Claire Schlesinger +5
Recent advancements in large language models (LLMs) have spurred interest in using them for generating robot programs from natural language, with promising initial results. We inve…