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20172022
most citedProgPrompt: Generating Situated Robot Task Plans using Large Language Models

44 citations · 111 across the 8 of their papers we have counts for

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7 papers · 1 filter

cs.CL20221 cited

Generalization Differences between End-to-End and Neuro-Symbolic Vision-Language Reasoning Systems

Wang Zhu, Jesse Thomason, Robin Jia

For vision-and-language reasoning tasks, both fully connectionist, end-to-end methods and hybrid, neuro-symbolic methods have achieved high in-distribution performance. In which ou…

cs.CL202117 cited

Language Grounding with 3D Objects

Jesse Thomason, Mohit Shridhar, Yonatan Bisk +2

Seemingly simple natural language requests to a robot are generally underspecified, for example "Can you bring me the wireless mouse?" Flat images of candidate mice may not provide…

cs.CL202014 cited

RMM: A Recursive Mental Model for Dialog Navigation

Homero Roman Roman, Yonatan Bisk, Jesse Thomason +2

Language-guided robots must be able to both ask humans questions and understand answers. Much existing work focuses only on the latter. In this paper, we go beyond instruction foll…

cs.CL2020

Experience Grounds Language

Yonatan Bisk, Ari Holtzman, Jesse Thomason +9

Language understanding research is held back by a failure to relate language to the physical world it describes and to the social interactions it facilitates. Despite the incredibl…

cs.CL2019

Vision-and-Dialog Navigation

Jesse Thomason, Michael Murray, Maya Cakmak +1

Robots navigating in human environments should use language to ask for assistance and be able to understand human responses. To study this challenge, we introduce Cooperative Visio…

cs.CL2019

Improving Grounded Natural Language Understanding through Human-Robot Dialog

Jesse Thomason, Aishwarya Padmakumar, Jivko Sinapov +6

Natural language understanding for robotics can require substantial domain- and platform-specific engineering. For example, for mobile robots to pick-and-place objects in an enviro…