1 code implementation • 17 Nov 2023 • Lihan Zha, Yuchen Cui, Li-Heng Lin, Minae Kwon, Montserrat Gonzalez Arenas, Andy Zeng, Fei Xia, Dorsa Sadigh
DROC is able to respond to a sequence of online language corrections that address failures in both high-level task plans and low-level skill primitives.
no code implementations • 14 Jun 2023 • Minae Kwon, Hengyuan Hu, Vivek Myers, Siddharth Karamcheti, Anca Dragan, Dorsa Sadigh
We additionally illustrate our approach with a robot on 2 carefully designed surfaces.
1 code implementation • 27 Feb 2023 • Minae Kwon, Sang Michael Xie, Kalesha Bullard, Dorsa Sadigh
During training, the LLM evaluates an RL agent's behavior against the desired behavior described by the prompt and outputs a corresponding reward signal.
1 code implementation • 19 Dec 2022 • Mina Lee, Megha Srivastava, Amelia Hardy, John Thickstun, Esin Durmus, Ashwin Paranjape, Ines Gerard-Ursin, Xiang Lisa Li, Faisal Ladhak, Frieda Rong, Rose E. Wang, Minae Kwon, Joon Sung Park, Hancheng Cao, Tony Lee, Rishi Bommasani, Michael Bernstein, Percy Liang
To evaluate human-LM interaction, we develop a new framework, Human-AI Language-based Interaction Evaluation (HALIE), that defines the components of interactive systems and dimensions to consider when designing evaluation metrics.
1 code implementation • Science 2022 • Anton Bakhtin, Noam Brown, Emily Dinan, Gabriele Farina, Colin Flaherty, Daniel Fried, Andrew Goff, Jonathan Gray, Hengyan Hu, Athul Paul Jacob, Mojtaba Komeili, Karthik Konath, Minae Kwon, Adam Lerer, Mike Lewis, Alexander H. Miller, Sash Mitts, Aditya Renduchintala, Stephen Roller, Dirk Rowe, Weiyan Shi, Joe Spisak, Alexander Wei, David Wu, Hugh Zhang, Markus Zijlstra
Despite much progress in training AI systems to imitate human language, building agents that use language to communicate intentionally with humans in interactive environments remains a major challenge.
no code implementations • 14 Jun 2021 • Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh
This trend additionally holds when comparing agents using our targeted data acquisition framework to variants of agents trained with a mix of supervised learning and reinforcement learning, or to agents using tailored reward functions that explicitly optimize for utility and Pareto-optimality.
no code implementations • 10 Feb 2021 • Zhangjie Cao, Minae Kwon, Dorsa Sadigh
The ability for robots to transfer their learned knowledge to new tasks -- where data is scarce -- is a fundamental challenge for successful robot learning.
Transfer Reinforcement Learning
Robotics
no code implementations • 13 Jan 2020 • Minae Kwon, Erdem Biyik, Aditi Talati, Karan Bhasin, Dylan P. Losey, Dorsa Sadigh
Overall, we extend existing rational human models so that collaborative robots can anticipate and plan around suboptimal human behavior during HRI.
1 code implementation • CONLL 2020 • Robert D. Hawkins, Minae Kwon, Dorsa Sadigh, Noah D. Goodman
To communicate with new partners in new contexts, humans rapidly form new linguistic conventions.