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Gaoke Zhang

2 accepted papers

2026

QueryAligner: Customizing User Query to Match LLMs Preferences for Better Intent Recognition

AAAI 2026technical

The interpretative efficacy of large language models (LLMs) fundamentally hinges on the intricate alignment between user inputs and model-specific linguistic priors. Existing methodologies predominantly employ static input optimization strategies, failing to account for the empirically observed dive

Cited by 0SourcePDFScholar
2025

Combining Loss-aware Curriculum Learning with Incomplete Graph Neural Networks

ICASSP 2025accepted

Graph neural networks (GNNs) have achieved great success in node classification tasks. However, most graph neural networks are incomplete. For example, the reference of each article is subjectively introduced by the author in the citation network, which leads to an incomplete citation network, espec…

Cited by 0SourceScholar