78 citations · 184 across the 13 of their papers we have counts for
13 papers
DSL-R1: From SQL to DSL for Training Retrieval Agents across Structured and Unstructured Data with Reinforcement Learning
Yunhai Hu, Junwei Zhou, Yumo Cao +8
Effective retrieval in complex domains requires bridging the gap between structured metadata and unstructured content. Existing systems typically isolate these capabilities, relyin…
Demonstrating Multi-Suction Item Picking at Scale via Multi-Modal Learning of Pick Success
Che Wang, Jeroen van Baar, Chaitanya Mitash +6
This work demonstrates how autonomously learning aspects of robotic operation from sparsely-labeled, real-world data of deployed, engineered solutions at industrial scale can provi…
Adapting Image-based RL Policies via Predicted Rewards
Weiyao Wang, Xinyuan Fang, Gregory D. Hager
Image-based reinforcement learning (RL) faces significant challenges in generalization when the visual environment undergoes substantial changes between training and deployment. Un…
Domain Adaptation of Visual Policies with a Single Demonstration
Weiyao Wang, Gregory D. Hager
Deploying machine learning algorithms for robot tasks in real-world applications presents a core challenge: overcoming the domain gap between the training and the deployment enviro…
VIHE: Virtual In-Hand Eye Transformer for 3D Robotic Manipulation
Weiyao Wang, Yutian Lei, Shiyu Jin +2
In this work, we introduce the Virtual In-Hand Eye Transformer (VIHE), a novel method designed to enhance 3D manipulation capabilities through action-aware view rendering. VIHE aut…
Pediatric Otoscopy Video Screening with Shift Contrastive Anomaly Detection
Weiyao Wang, Aniruddha Tamhane, Christine Santos +4
Ear related concerns and symptoms represents the leading indication for seeking pediatric healthcare attention. Despite the high incidence of such encounters, the diagnostic proces…
Learn Proportional Derivative Controllable Latent Space from Pixels
Weiyao Wang, Marin Kobilarov, Gregory D. Hager
Recent advances in latent space dynamics model from pixels show promising progress in vision-based model predictive control (MPC). However, executing MPC in real time can be challe…
Nothing But Geometric Constraints: A Model-Free Method for Articulated Object Pose Estimation
Qihao Liu, Weichao Qiu, Weiyao Wang +2
We propose an unsupervised vision-based system to estimate the joint configurations of the robot arm from a sequence of RGB or RGB-D images without knowing the model a priori, and…
How You Act Tells a Lot: Privacy-Leakage Attack on Deep Reinforcement Learning
Xinlei Pan, Weiyao Wang, Xiaoshuai Zhang +3
Machine learning has been widely applied to various applications, some of which involve training with privacy-sensitive data. A modest number of data breaches have been studied, in…
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets
Yunchen Pu, Shuyang Dai, Zhe Gan +5
A new generative adversarial network is developed for joint distribution matching. Distinct from most existing approaches, that only learn conditional distributions, the proposed m…
Adversarial Symmetric Variational Autoencoder
Yunchen Pu, Weiyao Wang, Ricardo Henao +4
A new form of variational autoencoder (VAE) is developed, in which the joint distribution of data and codes is considered in two (symmetric) forms: () from observed data fed thr…
Symmetric Variational Autoencoder and Connections to Adversarial Learning
Liqun Chen, Shuyang Dai, Yunchen Pu +3
A new form of the variational autoencoder (VAE) is proposed, based on the symmetric Kullback-Leibler divergence. It is demonstrated that learning of the resulting symmetric VAE (sV…
Triangle Generative Adversarial Networks
Zhe Gan, Liqun Chen, Weiyao Wang +5
A Triangle Generative Adversarial Network (-GAN) is developed for semi-supervised cross-domain joint distribution matching, where the training data consists of samples from each…