3 papers
cs.AI2026
Towards Reliable, Generalizable, and Specific In-Context Knowledge Editing via Multi-Objective Reinforcement Learning
Xuzhong Wang, Maiqi Jiang, Tejal Nair +3
Large Language Models (LLMs) are powerful but limited by static parametric knowledge that becomes outdated once pretraining ends. Knowledge editing addresses this problem by updati…
cs.LG2026
Is Meta-Path Attention an Explanation? Evidence of Alignment and Decoupling in Heterogeneous GNNs
Maiqi Jiang, Noman Ali, Yiran Ding +1
Meta-path-based heterogeneous graph neural networks aggregate over meta-path-induced views, and their semantic-level attention over meta-path channels is widely used as a narrative…
cs.CL2025
Dynamic Retriever for In-Context Knowledge Editing via Policy Optimization
Mahmud Wasif Nafee, Maiqi Jiang, Haipeng Chen +1
Large language models (LLMs) excel at factual recall yet still propagate stale or incorrect knowledge. In-context knowledge editing offers a gradient-free remedy suitable for black…