24 citations · 159 across the 20 of their papers we have counts for
5 papers · 1 filter
Language Models as Agent Models
Jacob Andreas
Language models (LMs) are trained on collections of documents, written by individual human agents to achieve specific goals in an outside world. During training, LMs have access on…
Hierarchical Phrase-based Sequence-to-Sequence Learning
Bailin Wang, Ivan Titov, Jacob Andreas +1
We describe a neural transducer that maintains the flexibility of standard sequence-to-sequence (seq2seq) models while incorporating hierarchical phrases as a source of inductive b…
ObSynth: An Interactive Synthesis System for Generating Object Models from Natural Language Specifications
Alex Gu, Tamara Mitrovska, Daniela Velez +2
We introduce ObSynth, an interactive system leveraging the domain knowledge embedded in large language models (LLMs) to help users design object models from high level natural lang…
Identifying concept libraries from language about object structure
Catherine Wong, William P. McCarthy, Gabriel Grand +5
Our understanding of the visual world goes beyond naming objects, encompassing our ability to parse objects into meaningful parts, attributes, and relations. In this work, we lever…
Correcting Robot Plans with Natural Language Feedback
Pratyusha Sharma, Balakumar Sundaralingam, Valts Blukis +5
When humans design cost or goal specifications for robots, they often produce specifications that are ambiguous, underspecified, or beyond planners' ability to solve. In these case…