Fine Tuning Out-of-Vocabulary Item Recommendation with User Sequence Imagination

R Liu, H Chen, Y Bei, Q Shen… - Advances in …, 2025 - proceedings.neurips.cc
Recommending out-of-vocabulary (OOV) items is a challenging problem since the in-
vocabulary (IV) items have well-trained behavioral embeddings but the OOV items only have …

Fast peer adaptation with context-aware exploration

L Ma, Y Wang, F Zhong, SC Zhu, Y Wang - arxiv preprint arxiv …, 2024 - arxiv.org
Fast adapting to unknown peers (partners or opponents) with different strategies is a key
challenge in multi-agent games. To do so, it is crucial for the agent to probe and identify the …

UnrealZoo: Enriching Photo-realistic Virtual Worlds for Embodied AI

F Zhong, K Wu, C Wang, H Chen, H Ci, Z Li… - arxiv preprint arxiv …, 2024 - arxiv.org
We introduce UnrealZoo, a rich collection of photo-realistic 3D virtual worlds built on Unreal
Engine, designed to reflect the complexity and variability of the open worlds. Additionally, we …

Cognitive Embodied Learning for Anomaly Active Target Tracking

F Zhou, Q Wu, J Li, J Ji, H Wang, H Liang, KK Ma - 2025 - researchsquare.com
The primary challenge in active object tracking (AOT) lies in maintaining robust and accurate
tracking performance in the complex physical scenarios. Existing end-to-end frameworks …