2 papers
cs.CL2026
Combating Instruction Conflict via Energy-Driven Latent Conflict Detection
Mingyu Ma, Yuxin Wu, Jingbo Wang +3
Large Language Models (LLMs) are increasingly deployed with hierarchical instructions, yet they remain vulnerable to conflicts in which user directives override system-level constr…
cs.LG2026
PACE: Propagation-Aware Collaborative Correction for One-Shot Personalized Federated Graph Learning
Ruizhe Huang, Chengran Li, Xiaochuan Shi
Client heterogeneity creates both an opportunity and a risk in personalized federated graph learning. Knowledge held by other subgraphs may complement a receiver's Local model, but…