9 citations · 9 across the 8 of their papers we have counts for
4 papers · 1 filter
Beyond Plain Demos: A Demo-centric Anchoring Paradigm for In-Context Learning in Alzheimer's Disease Detection
Puzhen Su, Haoran Yin, Yongzhu Miao +3
Detecting Alzheimer's disease (AD) from narrative transcripts challenges large language models (LLMs): pre-training rarely covers this out-of-distribution task, and all transcript…
Explicit Knowledge-Guided In-Context Learning for Early Detection of Alzheimer's Disease
Puzhen Su, Yongzhu Miao, Chunxi Guo +3
Detecting Alzheimer's Disease (AD) from narrative transcripts remains a challenging task for large language models (LLMs), particularly under out-of-distribution (OOD) and data-sca…
Identifying Knowledge Editing Types in Large Language Models
Xiaopeng Li, Shasha Li, Shangwen Wang +5
Knowledge editing has emerged as an efficient technique for updating the knowledge of large language models (LLMs), attracting increasing attention in recent years. However, there…
Multi-Document Scientific Summarization from a Knowledge Graph-Centric View
Pancheng Wang, Shasha Li, Kunyuan Pang +4
Multi-Document Scientific Summarization (MDSS) aims to produce coherent and concise summaries for clusters of topic-relevant scientific papers. This task requires precise understan…