244 citations · 300 across the 19 of their papers we have counts for
7 papers · 1 filter
UniSumm and SummZoo: Unified Model and Diverse Benchmark for Few-Shot Summarization
Yulong Chen, Yang Liu, Ruochen Xu +4
The high annotation costs and diverse demands of various summarization tasks motivate the development of few-shot summarization. However, despite the emergence of many summarizatio…
MACSum: Controllable Summarization with Mixed Attributes
Yusen Zhang, Yang Liu, Ziyi Yang +6
Controllable summarization allows users to generate customized summaries with specified attributes. However, due to the lack of designated annotations of controlled summaries, exis…
DialogSum Challenge: Results of the Dialogue Summarization Shared Task
Yulong Chen, Naihao Deng, Yang Liu +1
We report the results of DialogSum Challenge, the shared task on summarizing real-life scenario dialogues at INLG 2022. Four teams participate in this shared task and three submit…
Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expect
Naihao Deng, Yulong Chen, Yue Zhang
Text-to-SQL has attracted attention from both the natural language processing and database communities because of its ability to convert the semantics in natural language into SQL…
The Cross-lingual Conversation Summarization Challenge
Yulong Chen, Ming Zhong, Xuefeng Bai +4
We propose the shared task of cross-lingual conversation summarization, \emph{ConvSumX Challenge}, opening new avenues for researchers to investigate solutions that integrate conve…
Graph Pre-training for AMR Parsing and Generation
Xuefeng Bai, Yulong Chen, Yue Zhang
Abstract meaning representation (AMR) highlights the core semantic information of text in a graph structure. Recently, pre-trained language models (PLMs) have advanced tasks of AMR…
AdaPrompt: Adaptive Model Training for Prompt-based NLP
Yulong Chen, Yang Liu, Li Dong +4
Prompt-based learning, with its capability to tackle zero-shot and few-shot NLP tasks, has gained much attention in community. The main idea is to bridge the gap between NLP downst…