12 papers
Towards Effective Federated Multimodal Graph Learning via Navigating Multifaceted Heterogeneity
Yinlin Zhu, Di Wu, Yi Zhang +5
Multimodal-attributed graphs (MAGs), where nodes carry heterogeneous semantic content across multiple modalities while edges encode relational dependencies, have been widely adopte…
CLARE: Continual Learning for Vision-Language-Action Models via Autonomous Adapter Routing and Expansion
Ralf Römer, Yi Zhang, Yuming Li +1
To teach robots complex manipulation tasks, a common approach is to fine-tune a pre-trained vision-language-action model (VLA) on task-specific data. However, since this recipe upd…
Autonomy Reshapes How Personalization Affects Privacy Concerns and Trust in LLM Agents
Zhiping Zhang, Yi Evie Zhang, Freda Shi +1
LLM agents require personal information for personalization in order to effectively act on users' behalf, but this raises privacy concerns that can discourage data sharing, limitin…
ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders
Ofer Meshi, Krisztian Balog, Sally Goldman +5
The promise of LLM-based user simulators to improve conversational AI is hindered by a critical "realism gap," leading to systems that are optimized for simulated interactions, but…
Choosing How to Remember: Adaptive Memory Structures for LLM Agents
Mingfei Lu, Mengjia Wu, Feng Liu +8
Memory is critical for enabling large language model (LLM) based agents to maintain coherent behavior over long-horizon interactions. However, existing agent memory systems suffer…
MM-OpenFGL: A Comprehensive Benchmark for Multimodal Federated Graph Learning
Xunkai Li, Yuming Ai, Yinlin Zhu +7
Multimodal-attributed graphs (MMAGs) provide a unified framework for modeling complex relational data by integrating heterogeneous modalities with graph structures. While centraliz…