Search Results for author: Yulong Chen

Found 21 papers, 12 papers with code

DialogSum Challenge: Summarizing Real-Life Scenario Dialogues

no code implementations INLG (ACL) 2021 Yulong Chen, Yang Liu, Yue Zhang

We propose a shared task on summarizing real-life scenario dialogues, DialogSum Challenge, to encourage researchers to address challenges in dialogue summarization, which has been less studied by the summarization community.

Common Sense Reasoning Representation Learning

Investigating Rich Feature Sources for Conceptual Representation Encoding

no code implementations COLING (CogALex) 2020 Lu Cao, Yulong Chen, Dandan Huang, Yue Zhang

Functional Magnetic Resonance Imaging (fMRI) provides a means to investigate human conceptual representation in cognitive and neuroscience studies, where researchers predict the fMRI activations with elicited stimuli inputs.

Tables as Images? Exploring the Strengths and Limitations of LLMs on Multimodal Representations of Tabular Data

no code implementations19 Feb 2024 Naihao Deng, Zhenjie Sun, Ruiqi He, Aman Sikka, Yulong Chen, Lin Ma, Yue Zhang, Rada Mihalcea

In this paper, we investigate the effectiveness of various LLMs in interpreting tabular data through different prompting strategies and data formats.

Fact Checking Question Answering

Constituency Parsing using LLMs

no code implementations30 Oct 2023 Xuefeng Bai, Jialong Wu, Yulong Chen, Zhongqing Wang, Yue Zhang

Constituency parsing is a fundamental yet unsolved natural language processing task.

Constituency Parsing

Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models

1 code implementation3 Sep 2023 Yue Zhang, Yafu Li, Leyang Cui, Deng Cai, Lemao Liu, Tingchen Fu, Xinting Huang, Enbo Zhao, Yu Zhang, Yulong Chen, Longyue Wang, Anh Tuan Luu, Wei Bi, Freda Shi, Shuming Shi

While large language models (LLMs) have demonstrated remarkable capabilities across a range of downstream tasks, a significant concern revolves around their propensity to exhibit hallucinations: LLMs occasionally generate content that diverges from the user input, contradicts previously generated context, or misaligns with established world knowledge.

Hallucination World Knowledge

Revisiting Cross-Lingual Summarization: A Corpus-based Study and A New Benchmark with Improved Annotation

1 code implementation8 Jul 2023 Yulong Chen, Huajian Zhang, Yijie Zhou, Xuefeng Bai, Yueguan Wang, Ming Zhong, Jianhao Yan, Yafu Li, Judy Li, Michael Zhu, Yue Zhang

Additionally, based on the same intuition, we propose a 2-Step method, which takes both conversation and summary as input to simulate human annotation process.

EASE: An Easily-Customized Annotation System Powered by Efficiency Enhancement Mechanisms

no code implementations23 May 2023 Naihao Deng, YiKai Liu, Mingye Chen, Winston Wu, Siyang Liu, Yulong Chen, Yue Zhang, Rada Mihalcea

Our results show that our system can meet the diverse needs of NLP researchers and significantly accelerate the annotation process.

Active Learning

UniSumm and SummZoo: Unified Model and Diverse Benchmark for Few-Shot Summarization

1 code implementation17 Nov 2022 Yulong Chen, Yang Liu, Ruochen Xu, ZiYi Yang, Chenguang Zhu, Michael Zeng, Yue Zhang

The high annotation costs and diverse demands of various summarization tasks motivate the development of few-shot summarization.

MACSum: Controllable Summarization with Mixed Attributes

1 code implementation9 Nov 2022 Yusen Zhang, Yang Liu, ZiYi Yang, Yuwei Fang, Yulong Chen, Dragomir Radev, Chenguang Zhu, Michael Zeng, Rui Zhang

We propose two simple and effective parameter-efficient approaches for the new task of mixed controllable summarization based on hard prompt tuning and soft prefix tuning.

Attribute Specificity

Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expect

1 code implementation COLING 2022 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 queries and its practical application in building natural language interfaces to database systems.


DialogSum Challenge: Results of the Dialogue Summarization Shared Task

1 code implementation8 Aug 2022 Yulong Chen, Naihao Deng, Yang Liu, Yue Zhang

We report the results of DialogSum Challenge, the shared task on summarizing real-life scenario dialogues at INLG 2022.

The Cross-lingual Conversation Summarization Challenge

2 code implementations1 May 2022 Yulong Chen, Ming Zhong, Xuefeng Bai, Naihao Deng, Jing Li, Xianchao Zhu, Yue Zhang

We propose the shared task of cross-lingual conversation summarization, \emph{ConvSumX Challenge}, opening new avenues for researchers to investigate solutions that integrate conversation summarization and machine translation.

Abstractive Dialogue Summarization Cross-Lingual Abstractive Summarization +3

A Survey on Legal Judgment Prediction: Datasets, Metrics, Models and Challenges

no code implementations11 Apr 2022 Junyun Cui, Xiaoyu Shen, Feiping Nie, Zheng Wang, Jinglong Wang, Yulong Chen

In this paper, to address the current lack of comprehensive survey of existing LJP tasks, datasets, models and evaluations, (1) we analyze 31 LJP datasets in 6 languages, present their construction process and define a classification method of LJP with 3 different attributes; (2) we summarize 14 evaluation metrics under four categories for different outputs of LJP tasks; (3) we review 12 legal-domain pretrained models in 3 languages and highlight 3 major research directions for LJP; (4) we show the state-of-art results for 8 representative datasets from different court cases and discuss the open challenges.

Graph Pre-training for AMR Parsing and Generation

2 code implementations ACL 2022 Xuefeng Bai, Yulong Chen, Yue Zhang

To our knowledge, we are the first to consider pre-training on semantic graphs.

 Ranked #1 on AMR-to-Text Generation on Bio (BLEU metric, using extra training data)

AMR Parsing AMR-to-Text Generation +1

MHSnet: Multi-head and Spatial Attention Network with False-Positive Reduction for Pulmonary Nodules Detection

no code implementations31 Jan 2022 Juanyun Mai, Minghao Wang, Jiayin Zheng, Yanbo Shao, Zhaoqi Diao, Xinliang Fu, Yulong Chen, Jianyu Xiao, Jian You, Airu Yin, Yang Yang, Xiangcheng Qiu, Jinsheng Tao, Bo wang, Hua Ji

The false positive reduction module significantly decreases the average number of candidates generated per scan by 68. 11% and the false discovery rate by 13. 48%, which is promising to reduce distracted proposals for the downstream tasks based on the detection results.

Head Detection

On Compositional Generalization of Neural Machine Translation

1 code implementation ACL 2021 Yafu Li, Yongjing Yin, Yulong Chen, Yue Zhang

Modern neural machine translation (NMT) models have achieved competitive performance in standard benchmarks such as WMT.

Domain Generalization Machine Translation +3

Semantic Representation for Dialogue Modeling

1 code implementation ACL 2021 Xuefeng Bai, Yulong Chen, Linfeng Song, Yue Zhang

Although neural models have achieved competitive results in dialogue systems, they have shown limited ability in representing core semantics, such as ignoring important entities.

Dialog Relation Extraction Dialogue Understanding +2

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