1 code implementation • 16 Apr 2024 • Pancheng Wang, Shasha Li, Dong Li, Kehan Long, Jintao Tang, Ting Wang
Our insights are twofold: Firstly, summary candidates can provide instructive information from both positive and negative perspectives, and secondly, selecting higher-quality candidates from multiple options contributes to producing better summaries.
1 code implementation • 4 Mar 2024 • Kehan Long, Shasha Li, Pancheng Wang, Chenlong Bao, Jintao Tang, Ting Wang
To help improve citations of full papers, we first define a novel task of Recommending Missed Citations Identified by Reviewers (RMC) and construct a corresponding expert-labeled dataset called CitationR.
no code implementations • 11 Jul 2023 • Chunxi Guo, Zhiliang Tian, Jintao Tang, Shasha Li, Zhihua Wen, Kaixuan Wang, Ting Wang
Prompt learning with large language models (LLMs) has emerged as a recent approach, which designs prompts to lead LLMs to understand the input question and generate the corresponding SQL.
1 code implementation • 20 Jun 2023 • Yongzhu Miao, Shasha Li, Jintao Tang, Ting Wang
We evaluate the effectiveness of MuDPT on few-shot vision recognition and out-of-domain generalization tasks.
no code implementations • 10 May 2023 • Chengxian Zhang, Jintao Tang, Ting Wang, Shasha Li
There is evidence that address matching plays a crucial role in many areas such as express delivery, online shopping and so on.
no code implementations • 26 Apr 2023 • Chunxi Guo, Zhiliang Tian, Jintao Tang, Pancheng Wang, Zhihua Wen, Kang Yang, Ting Wang
Text-to-SQL is a task that converts a natural language question into a structured query language (SQL) to retrieve information from a database.
1 code implementation • COLING 2022 • Pancheng Wang, Shasha Li, Kunyuan Pang, Liangliang He, Dong Li, Jintao Tang, Ting Wang
Multi-Document Scientific Summarization (MDSS) aims to produce coherent and concise summaries for clusters of topic-relevant scientific papers.