activity
20242026
most citedGenerating Negative Samples for Multi-Modal Recommendation

1 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2026

RelAfford6D: Relational 6D Affordance Graphs for Constraint-Driven Robotic Manipulation

Guodong Zhang, Qichen He, Wenyuan Xie +6

Bridging abstract semantics and precise physical control remains a fundamental challenge in open-world robotic manipulation. While recent data-driven policies show promise, their r…

cs.RO2026

Recovering Hidden Reward in Diffusion-Based Policies

Yanbiao Ji, Qiuchang Li, Yuting Hu +7

This paper introduces EnergyFlow, a framework that unifies generative action modeling with inverse reinforcement learning by parameterizing a scalar energy function whose gradient…

cs.RO2025

Dejavu: Towards Experience Feedback Learning for Embodied Intelligence

Shaokai Wu, Yanbiao Ji, Qiuchang Li +7

Embodied agents face a fundamental limitation: once deployed in real-world environments, they cannot easily acquire new knowledge to improve task performance. In this paper, we pro…

cs.IR2025★ 1 cited

Generating Negative Samples for Multi-Modal Recommendation

Yanbiao Ji, Dan Luo, Chang Liu +6

Multi-modal recommender systems (MMRS) have gained significant attention due to their ability to leverage information from various modalities to enhance recommendation quality. How…

eess.IV2024★ 1 cited

Discretized Gaussian Representation for Tomographic Reconstruction

Shaokai Wu, Yuxiang Lu, Yapan Guo +9

Computed Tomography (CT) enables detailed cross-sectional imaging but continues to face challenges in balancing reconstruction quality and computational efficiency. While deep lear…