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Shenglin Ben

2 accepted papers

2026

DAPrompt: Dual Alignment Prompt of Structure and Semantics for Few-shot Graph Learning

AAAI 2026technical

Few-shot graph learning remains a fundamental yet challenging problem, especially under heterophilic graph settings where connected nodes are likely to belong to different classes. In such scenarios, two key challenges arise: (1) unreliable or noisy graph structures that hinder effective message pas

Cited by 0SourcePDFScholar
2026

TermGPT: Multi-Level Contrastive Fine-Tuning for Terminology Adaptation in Legal and Financial Domains

AAAI 2026technical

Large language models (LLMs) have demonstrated impressive performance in text generation tasks; however, their embedding spaces often suffer from the isotropy problem, resulting in poor discrimination of domain-specific terminology, particularly in legal and financial contexts. This weakness in term

Cited by 0SourcePDFScholar