Zobrazeno 1 - 10
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pro vyhledávání: '"Choi, Jason"'
Autor:
Xia, Xingpeng, Choi, Jason J., Agrawal, Ayush, Sreenath, Koushil, Tomlin, Claire J., Bansal, Somil
Learning-based approaches have recently shown notable success in legged locomotion. However, these approaches often lack accountability, necessitating empirical tests to determine their effectiveness. In this work, we are interested in designing a le
Externí odkaz:
http://arxiv.org/abs/2409.16301
Autor:
Senel, Lütfi Kerem, Fetahu, Besnik, Yoshida, Davis, Chen, Zhiyu, Castellucci, Giuseppe, Vedula, Nikhita, Choi, Jason, Malmasi, Shervin
Recommender systems are widely used to suggest engaging content, and Large Language Models (LLMs) have given rise to generative recommenders. Such systems can directly generate items, including for open-set tasks like question suggestion. While the w
Externí odkaz:
http://arxiv.org/abs/2406.05255
Learning-based approaches are emerging as an effective approach for safety filters for black-box dynamical systems. Existing methods have relied on certificate functions like Control Barrier Functions (CBFs) and Hamilton-Jacobi (HJ) reachability valu
Externí odkaz:
http://arxiv.org/abs/2402.05279
Autor:
Choi, Jason J., Castañeda, Fernando, Jung, Wonsuhk, Zhang, Bike, Tomlin, Claire J., Sreenath, Koushil
As the use of autonomous robots expands in tasks that are complex and challenging to model, the demand for robust data-driven control methods that can certify safety and stability in uncertain conditions is increasing. However, the practical implemen
Externí odkaz:
http://arxiv.org/abs/2311.13824
Many Natural Language Generation (NLG) tasks aim to generate a single output text given an input prompt. Other settings require the generation of multiple texts, e.g., for Synthetic Traffic Generation (STG). This generation task is crucial for traini
Externí odkaz:
http://arxiv.org/abs/2311.12534
Autor:
Choi, Jason J., Lee, Donggun, Li, Boyang, How, Jonathan P., Sreenath, Koushil, Herbert, Sylvia L., Tomlin, Claire J.
Control invariant sets are crucial for various methods that aim to design safe control policies for systems whose state constraints must be satisfied over an indefinite time horizon. In this article, we explore the connections among reachability, con
Externí odkaz:
http://arxiv.org/abs/2310.17180
Customers interacting with product search engines are increasingly formulating information-seeking queries. Frequently Asked Question (FAQ) retrieval aims to retrieve common question-answer pairs for a user query with question intent. Integrating FAQ
Externí odkaz:
http://arxiv.org/abs/2306.03411
Open-domain conversational search (ODCS) aims to provide valuable, up-to-date information, while maintaining natural conversations to help users refine and ultimately answer information needs. However, creating an effective and robust ODCS agent is c
Externí odkaz:
http://arxiv.org/abs/2304.02233
Autor:
Castañeda, Fernando, Choi, Jason J., Jung, Wonsuhk, Zhang, Bike, Tomlin, Claire J., Sreenath, Koushil
Learning-based control has recently shown great efficacy in performing complex tasks for various applications. However, to deploy it in real systems, it is of vital importance to guarantee the system will stay safe. Control Barrier Functions (CBFs) o
Externí odkaz:
http://arxiv.org/abs/2208.10733
Learned models and policies can generalize effectively when evaluated within the distribution of the training data, but can produce unpredictable and erroneous outputs on out-of-distribution inputs. In order to avoid distribution shift when deploying
Externí odkaz:
http://arxiv.org/abs/2206.10524