9 citations · 17 across the 11 of their papers we have counts for
11 papers
DEAP-3DSAM: Decoder Enhanced and Auto Prompt SAM for 3D Medical Image Segmentation
Fangda Chen, Jintao Tang, Pancheng Wang +3
The Segment Anything Model (SAM) has recently demonstrated significant potential in medical image segmentation. Although SAM is primarily trained on 2D images, attempts have been m…
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…
Precise Zero-Shot Pointwise Ranking with LLMs through Post-Aggregated Global Context Information
Kehan Long, Shasha Li, Chen Xu +2
Recent advancements have successfully harnessed the power of Large Language Models (LLMs) for zero-shot document ranking, exploring a variety of prompting strategies. Comparative a…
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…
Disentangling Instructive Information from Ranked Multiple Candidates for Multi-Document Scientific Summarization
Pancheng Wang, Shasha Li, Dong Li +3
Automatically condensing multiple topic-related scientific papers into a succinct and concise summary is referred to as Multi-Document Scientific Summarization (MDSS). Currently, w…
Recommending Missed Citations Identified by Reviewers: A New Task, Dataset and Baselines
Kehan Long, Shasha Li, Pancheng Wang +3
Citing comprehensively and appropriately has become a challenging task with the explosive growth of scientific publications. Current citation recommendation systems aim to recommen…
Retrieval-augmented GPT-3.5-based Text-to-SQL Framework with Sample-aware Prompting and Dynamic Revision Chain
Chunxi Guo, Zhiliang Tian, Jintao Tang +4
Text-to-SQL aims at generating SQL queries for the given natural language questions and thus helping users to query databases. Prompt learning with large language models (LLMs) has…
MuDPT: Multi-modal Deep-symphysis Prompt Tuning for Large Pre-trained Vision-Language Models
Yongzhu Miao, Shasha Li, Jintao Tang +1
Prompt tuning, like CoOp, has recently shown promising vision recognizing and transfer learning ability on various downstream tasks with the emergence of large pre-trained vision-l…
Address Matching Based On Hierarchical Information
Chengxian Zhang, Jintao Tang, Ting Wang +1
There is evidence that address matching plays a crucial role in many areas such as express delivery, online shopping and so on. Address has a hierarchical structure, in contrast to…
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…