no code implementations • COLING 2022 • Yubing Ren, Yanan Cao, Fang Fang, Ping Guo, Zheng Lin, Wei Ma, Yi Liu
Transforming the large amounts of unstructured text on the Internet into structured event knowledge is a critical, yet unsolved goal of NLP, especially when addressing document-level text.
no code implementations • COLING 2022 • Qingyue Wang, Yanan Cao, Piji Li, Yanhe Fu, Zheng Lin, Li Guo
Zero-shot learning for Dialogue State Tracking (DST) focuses on generalizing to an unseen domain without the expense of collecting in domain data.
no code implementations • NAACL 2022 • Zheng Fang, Ruiqing Zhang, Zhongjun He, Hua Wu, Yanan Cao
Automatic Speech Recognition (ASR) is an efficient and widely used input method that transcribes speech signals into text.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1
no code implementations • EMNLP 2021 • Kangli Zi, Shi Wang, Yu Liu, Jicun Li, Yanan Cao, Cungen Cao
Sentence Compression (SC), which aims to shorten sentences while retaining important words that express the essential meanings, has been studied for many years in many languages, especially in English.
no code implementations • EMNLP 2021 • Zheng Fang, Yanan Cao, Tai Li, Ruipeng Jia, Fang Fang, Yanmin Shang, Yuhai Lu
To alleviate label scarcity in Named Entity Recognition (NER) task, distantly supervised NER methods are widely applied to automatically label data and identify entities.
no code implementations • EMNLP 2020 • Ruipeng Jia, Yanan Cao, Hengzhu Tang, Fang Fang, Cong Cao, Shi Wang
Sentence-level extractive text summarization is substantially a node classification task of network mining, adhering to the informative components and concise representations.
Ranked #1 on Extractive Text Summarization on CNN / Daily Mail
1 code implementation • 11 Oct 2022 • Yuanxin Liu, Fandong Meng, Zheng Lin, Jiangnan Li, Peng Fu, Yanan Cao, Weiping Wang, Jie zhou
In response to the efficiency problem, recent studies show that dense PLMs can be replaced with sparse subnetworks without hurting the performance.
1 code implementation • 10 Oct 2022 • Qingyi Si, Fandong Meng, Mingyu Zheng, Zheng Lin, Yuanxin Liu, Peng Fu, Yanan Cao, Weiping Wang, Jie zhou
To overcome this limitation, we propose a new dataset that considers varying types of shortcuts by constructing different distribution shifts in multiple OOD test sets.
1 code implementation • 10 Oct 2022 • Qingyi Si, Yuanxin Liu, Fandong Meng, Zheng Lin, Peng Fu, Yanan Cao, Weiping Wang, Jie zhou
However, these models reveal a trade-off that the improvements on OOD data severely sacrifice the performance on the in-distribution (ID) data (which is dominated by the biased samples).
1 code implementation • 2 May 2022 • Jiangnan Li, Fandong Meng, Zheng Lin, Rui Liu, Peng Fu, Yanan Cao, Weiping Wang, Jie zhou
Conversational Causal Emotion Entailment aims to detect causal utterances for a non-neutral targeted utterance from a conversation.
Ranked #1 on Causal Emotion Entailment on RECCON
no code implementations • ACL 2022 • Ruipeng Jia, Xingxing Zhang, Yanan Cao, Shi Wang, Zheng Lin, Furu Wei
In zero-shot multilingual extractive text summarization, a model is typically trained on English summarization dataset and then applied on summarization datasets of other languages.
1 code implementation • NAACL 2022 • Yuanxin Liu, Fandong Meng, Zheng Lin, Peng Fu, Yanan Cao, Weiping Wang, Jie zhou
Firstly, we discover that the success of magnitude pruning can be attributed to the preserved pre-training performance, which correlates with the downstream transferability.
no code implementations • 2 Oct 2021 • Ren Li, Yanan Cao, Qiannan Zhu, Xiaoxue Li, Fang Fang
Modeling of relation pattern is the core focus of previous Knowledge Graph Embedding works, which represents how one entity is related to another semantically by some explicit relation.
1 code implementation • 24 Sep 2021 • Ren Li, Yanan Cao, Qiannan Zhu, Guanqun Bi, Fang Fang, Yi Liu, Qian Li
However, most existing KGE works focus on the design of delicate triple modeling function, which mainly tells us how to measure the plausibility of observed triples, but offers limited explanation of why the methods can extrapolate to unseen data, and what are the important factors to help KGE extrapolate.
Ranked #9 on Link Prediction on FB15k-237
no code implementations • ACL 2021 • Ruipeng Jia, Yanan Cao, Fang Fang, Yuchen Zhou, Zheng Fang, Yanbing Liu, Shi Wang
In this paper, we conceptualize the single-document extractive summarization as a rebalance problem and present a deep differential amplifier framework.
1 code implementation • 26 Feb 2021 • Xixun Lin, Jia Wu, Chuan Zhou, Shirui Pan, Yanan Cao, Bin Wang
In this paper, we develop a novel meta-learning recommender called task-adaptive neural process (TaNP).
1 code implementation • NeurIPS 2020 • Shichao Zhu, Shirui Pan, Chuan Zhou, Jia Wu, Yanan Cao, Bin Wang
To utilize the strength of both Euclidean and hyperbolic geometries, we develop a novel Geometry Interaction Learning (GIL) method for graphs, a well-suited and efficient alternative for learning abundant geometric properties in graph.
no code implementations • 28 Mar 2020 • Hengzhu Tang, Yanan Cao, Zhen-Yu Zhang, Jiangxia Cao, Fang Fang, Shi Wang, Pengfei Yin
In this paper, we propose a Hierarchical Inference Network (HIN) to make full use of the abundant information from entity level, sentence level and document level.
Ranked #50 on Relation Extraction on DocRED
no code implementations • 31 Oct 2019 • Xiaoxue Li, Yanan Cao, Yanmin Shang, Yangxi Li, Yanbing Liu, Jianlong Tan
User identity linkage is a task of recognizing the identities of the same user across different social networks (SN).
no code implementations • 1 Feb 2019 • Zheng Fang, Yanan Cao, Dongjie Zhang, Qian Li, Zhen-Yu Zhang, Yanbing Liu
Entity linking is the task of aligning mentions to corresponding entities in a given knowledge base.
Ranked #6 on Entity Disambiguation on AIDA-CoNLL