works on

From the 2 of 15 linked papers with an AI index.

activity
20242026
collaborators

15 papers

cs.CV2026

VTM-Nav: Harnessing Cross-Episode Experience for Object-Goal Navigation with Hierarchical Visual-Topological Memory

Xiaoran Xu, Yupeng Wu, Tianyu Xue +4

Training-free ObjectNav agents increasingly use vision-language models (VLMs), yet typically discard acquired scene knowledge after each request. We study cross-episode ObjectNav,…

cs.CV2026

PivotMerge: Bridging Heterogeneous Multimodal Pre-training via Post-Alignment Model Merging

Zibo Shao, Baochen Xiong, Xiaoshan Yang +4

The paper introduces PivotMerge, a framework for merging multimodal language models trained on heterogeneous data by separating shared cross‑modal alignment patterns from domain‑sp…

cs.CV2026

DOME: Learning Transferable Domain Variables from Sparse Supervision for Test-Time Adaptation

Xiaoran Xu, Yifan Xu, Yupeng Wu +2

Test-time adaptation (TTA) aims to align a model to shifting test domains using only unlabeled streaming data. Most existing methods implicitly infer a single global domain distrib…

cs.DC2026

Boosting Multimodal Federated Learning via Chained Modality Optimization

Zixin Zhang, Fan Qi, Shuai Li +2

Multimodal Federated Learning (MMFL) enables privacy-preserving collaborative learning across decentralized clients with heterogeneous data and modality availability. However, most…

cs.CV2026

General Covariant Action Modeling: Constructing Generalized Manifolds via Spatio-Temporal Decoupling

Huaihai Lyu, Chaofan Chen, Mingyu Cao +2

Achieving robust generalization from limited data is a central challenge in embodied intelligence. Prevailing methods fail by regressing absolute coordinates, which violates the pr…

cs.AI2026

Replacing Parameters with Preferences: Federated Alignment of Heterogeneous Vision-Language Models

Shule Lu, Yujing Wang, Hainan Zhang +5

Vision-Language Models (VLMs) have broad potential in privacy-sensitive domains such as healthcare and finance, yet strict data-sharing constraints render centralized training infe…