no code implementations • 7 Jan 2024 • Connie Jiang, Yiqing Xu, David Hsu
The advantages of pre-trained large language models (LLMs) are apparent in a variety of language processing tasks.
no code implementations • 21 Oct 2023 • Yuwei Zeng, Yiqing Xu
We aim to extract task knowledge from LLMs using environment feedback to create efficient reward functions for physical skills.
no code implementations • 21 Jul 2023 • Yiqing Xu, David Hsu
Tidying up a messy table may appear simple for humans, but articulating clear criteria for tidiness is challenging due to the ambiguous nature of common sense reasoning.
no code implementations • 13 Jul 2023 • Yiqing Xu, Finale Doshi-Velez, David Hsu
Inverse reinforcement learning (IRL) algorithms often rely on (forward) reinforcement learning or planning over a given time horizon to compute an approximately optimal policy for a hypothesized reward function and then match this policy with expert demonstrations.
1 code implementation • CVPRW 2023 • Marcos V. Conde, Manuel Kolmet, Tim Seizinger, Tom E. Bishop, Radu Timofte, Xiangyu Kong, Dafeng Zhang, Jinlong Wu, Fan Wang, Juewen Peng, Zhiyu Pan, Chengxin Liu, Xianrui Luo, Huiqiang Sun, Liao Shen, Zhiguo Cao, Ke Xian, Chaowei Liu, Zigeng Chen, Xingyi Yang, Songhua Liu, Yongcheng Jing, Michael Bi Mi, Xinchao Wang, Zhihao Yang, Wenyi Lian, Siyuan Lai, Haichuan Zhang, Trung Hoang, Amirsaeed Yazdani, Vishal Monga, Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao, Jens Sjölund, Thomas B. Schön, Yuxuan Zhao, Baoliang Chen, Yiqing Xu, JiXiang Niu
We present the new Bokeh Effect Transformation Dataset (BETD), and review the proposed solutions for this novel task at the NTIRE 2023 Bokeh Effect Transformation Challenge.
1 code implementation • 20 Mar 2023 • Apoorva Lal, Mac Lockhart, Yiqing Xu, Ziwen Zu
First, researchers often overestimate the strength of their IVs due to non-i. i. d.
1 code implementation • ACM 2022 • Yiqing Xu
We introduce hierarchically regularized entropy balancing as an extension to entropy balancing, a reweighting method that adjusts weights for control group units to achieve covariate balance in observational studies with binary treatments.
no code implementations • 9 Jun 2022 • Yiqing Xu, Wei Gao, David Hsu
Inverse reinforcement learning (IRL) seeks to infer a cost function that explains the underlying goals and preferences of expert demonstrations.
no code implementations • 10 Dec 2020 • Hieu Le Trung, Yiqing Xu, Wee Sun Lee
Designing a network to learn a molecule structure given its physical/chemical properties is a hard problem, but is useful for drug discovery tasks.