FedFST is a spectral-aware framework that mitigates dual spectral forgetting in Federated Graph Continual Learning, and comprises Historical High-Frequency Knowledge Restoration to reconstruct and preserve high-frequency inconsistency knowledge, and Historical Low-Frequency Semantic Transfer to stabilize low-frequency...
Hanyao Guo, Zihan Tan, Wen-Ke Huang et al.· Proceedings of the 32nd ACM...· 0 citations
Federated Graph Learning (FGL) enables privacy-preserving GNN training over distributed graph data, yet dynamic task streams in Federated Graph Continual Learning (FGCL) inevitably lead to catastrophic forgetting. From a spectral perspective, this forgetting manifests as two fundamental challenges: high-frequency incon...
Hanyao Guo, Zihan Tan, Wenke Huang et al.· Proceedings of the 32nd ACM...· 0 citations
It is suggested that LLMs differ not only in baseline risk disposition, but also in the risk signals they respond to and the flexibility with which they adjust, providing a behavioural basis for auditing risk-sensitive decision-making in interactive settings.
Xuan-Kun Rong, Wenke Huang, Bo Du et al.· arXiv.org· 0 citations
Federated Learning (FL) has demonstrated a promising future in privacy-friendly collaboration but it faces the data heterogeneity problem. Knowledge Distillation (KD) can serve as an effective method to address this issue. However, challenges arise from the unreliability of existing distillation methods in multi-domain...
Yue Yuan, Wenke Huang, Frank Wan et al.· Neural Information Processin...· 1 citation
Switch-Reasoner is proposed, a GRPO-based framework that learns to adaptively select reasoning modes for MLLMs and introduces a dual-level regulation mechanism that balances the overall use of Thinking Mode and Direct Mode while providing sample-level supervision based on the relative benefit of the two choices.
Yiyang Fang, Pei Fu, Jinjie Li et al.· arXiv.org· 0 citations
DecisionQE is introduced, a questionnaire-based framework for measuring each model's persuasive and compliant tendencies across multiple decision scenarios, and the Werewolf game is used as an interactive testbed to study their effects on social influence and group outcomes under asymmetric information.
Wen-Wen He, Wen-Ke Huang, Wei Yang Bryan Lim et al.· 0 citations
The core of SSVAL is Visual Anchor Prompt Injection (VAPI), which introduces prompts that absorb rich knowledge from external VFMs during training, enabling them to serve as stable visual anchors that mitigate representation deviation during inference.
Qian-Long Yang, Bowen Ye, Xianda Guo et al.· 0 citations
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