Profils utilisateurs correspondant à "Jacob Arkin"
 | Jacob ArkinPostdoctoral Associate, Massachusetts Institute of Technology Adresse e-mail validée de mit.edu Cité 575 fois |
Autotamp: Autoregressive task and motion planning with llms as translators and checkers
For effective human-robot interaction, robots need to understand, plan, and execute complex,
long-horizon tasks described by natural language. Recent advances in large language …
long-horizon tasks described by natural language. Recent advances in large language …
Scalable multi-robot collaboration with large language models: Centralized or decentralized systems?
A flurry of recent work has demonstrated that pre-trained large language models (LLMs) can
be effective task planners for a variety of single-robot tasks. The planning performance of …
be effective task planners for a variety of single-robot tasks. The planning performance of …
Efficient grounding of abstract spatial concepts for natural language interaction with robot manipulators
Our goal is to develop models that allow a robot to understand natural language instructions
in the context of its world representation. Contemporary models learn possible …
in the context of its world representation. Contemporary models learn possible …
Efficient grounding of abstract spatial concepts for natural language interaction with robot platforms
Our goal is to develop models that allow a robot to efficiently understand or “ground” natural
language instructions in the context of its world representation. Contemporary approaches …
language instructions in the context of its world representation. Contemporary approaches …
Multimodal estimation and communication of latent semantic knowledge for robust execution of robot instructions
The goal of this article is to enable robots to perform robust task execution following human
instructions in partially observable environments. A robot’s ability to interpret and execute …
instructions in partially observable environments. A robot’s ability to interpret and execute …
A model for verifiable grounding and execution of complex natural language instructions
Current methods of grounding natural language instructions do not include reactive or temporal
components, making these methods unsuitable for instructions describing tasks as sets …
components, making these methods unsuitable for instructions describing tasks as sets …
Prompt optimization in multi-step tasks (promst): Integrating human feedback and preference alignment
Prompt optimization aims to find the best prompt to a large language model (LLM) for a given
task. LLMs have been successfully used to help find and improve prompt candidates for …
task. LLMs have been successfully used to help find and improve prompt candidates for …
Real-time natural language corrections for assistive robotic manipulators
We propose a generalizable natural language interface that allows users to provide corrective
instructions to an assistive robotic manipulator in real-time. This work is motivated by the …
instructions to an assistive robotic manipulator in real-time. This work is motivated by the …
An intelligence architecture for grounded language communication with field robots
For humans and robots to collaborate effectively as teammates in unstructured environments,
robots must be able to construct semantically rich models of the environment, …
robots must be able to construct semantically rich models of the environment, …
Selective Downregulation of JAK2 and JAK3 by an ATP-Competitive pan-JAK Inhibitor
PF-956980 has been used previously as a JAK3-selective chemical probe in numerous cell-based
experiments. Here, we report that not only is PF-956980 a pan-JAK ATP-competitive …
experiments. Here, we report that not only is PF-956980 a pan-JAK ATP-competitive …