9 citations · 18 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…
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…
Prompting GPT-3.5 for Text-to-SQL with De-semanticization and Skeleton Retrieval
Chunxi Guo, Zhiliang Tian, Jintao Tang +4
Text-to-SQL is a task that converts a natural language question into a structured query language (SQL) to retrieve information from a database. Large language models (LLMs) work we…
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…