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Linghui Meng

ACL 2026×2可解释性效率与系统检索与知识安全推理
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0 一作 · 2 篇 · ACL 2026

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2026 顶会论文

2
作者位次 #5/6ACL 2026Poster· Natural Language Processing

Compressing LLM Knowledge into Graph Representations for Text-attributed Graphs Learning

Runhuai Chen · Dian Shen · Dandan Zhang · kaihong huang · Linghui Meng · Beilun Wang

摘要

Text-attributed graphs (TAGs) require jointly modeling relational structure and node-level text. Existing GNN-LLM approaches perform by incorporating large language models at inference time for processing the text attributes, resulting in costly deployment. More fundamentally, LLM knowledge is ty...

效率与系统可解释性检索与知识OpenReview 项目页
作者位次 #5/8ACL 2026Findings· Findings of ACL

Rethinking Reasoning: A Survey on Reasoning-based Backdoors in LLM s

Man Hu · Xinyi Wu · Zhufeng Suo · Jinbo Feng · Linghui Meng · Yanhao Jia · Anh Tuan Luu · Shuai Zhao

摘要

With the rise of advanced reasoning capabilities, large language models (LLMs) are receiving increasing attention. While reasoning enhances LLMs’ performance on downstream tasks, it also introduces new threat vectors, as adversaries can leverage these capabilities to conduct backdoor attacks. Pri...

安全推理可解释性OpenReview 项目页

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