Search Results for author: Linfeng Song

Found 46 papers, 21 papers with code

Variational Graph Autoencoding as Cheap Supervision for AMR Coreference Resolution

no code implementations ACL 2022 Irene Li, Linfeng Song, Kun Xu, Dong Yu

Coreference resolution over semantic graphs like AMRs aims to group the graph nodes that represent the same entity.

Coreference Resolution

Rich Syntactic and Semantic Information Helps Unsupervised Text Style Transfer

no code implementations INLG (ACL) 2020 Hongyu Gong, Linfeng Song, Suma Bhat

Text style transfer aims to change an input sentence to an output sentence by changing its text style while preserving the content.

Style Transfer Text Style Transfer +1

Instance-adaptive training with noise-robust losses against noisy labels

no code implementations EMNLP 2021 Lifeng Jin, Linfeng Song, Kun Xu, Dong Yu

In order to alleviate the huge demand for annotated datasets for different tasks, many recent natural language processing datasets have adopted automated pipelines for fast-tracking usable data.

RAST: Domain-Robust Dialogue Rewriting as Sequence Tagging

no code implementations EMNLP 2021 Jie Hao, Linfeng Song, LiWei Wang, Kun Xu, Zhaopeng Tu, Dong Yu

The task of dialogue rewriting aims to reconstruct the latest dialogue utterance by copying the missing content from the dialogue context.

Dialogue Rewriting Text Generation

Distant finetuning with discourse relations for stance classification

no code implementations27 Apr 2022 Lifeng Jin, Kun Xu, Linfeng Song, Dong Yu

Approaches for the stance classification task, an important task for understanding argumentation in debates and detecting fake news, have been relying on models which deal with individual debate topics.

Classification Stance Classification

End-to-End AMR Coreference Resolution

1 code implementation ACL 2021 Qiankun Fu, Linfeng Song, Wenyu Du, Yue Zhang

Although parsing to Abstract Meaning Representation (AMR) has become very popular and AMR has been shown effective on the many sentence-level downstream tasks, little work has studied how to generate AMRs that can represent multi-sentence information.

Coreference Resolution Text Summarization

JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs

1 code implementation Findings (ACL) 2021 Pei Ke, Haozhe Ji, Yu Ran, Xin Cui, LiWei Wang, Linfeng Song, Xiaoyan Zhu, Minlie Huang

Existing pre-trained models for knowledge-graph-to-text (KG-to-text) generation simply fine-tune text-to-text pre-trained models such as BART or T5 on KG-to-text datasets, which largely ignore the graph structure during encoding and lack elaborate pre-training tasks to explicitly model graph-text alignments.

Graph Reconstruction KG-to-Text Generation +3

Domain-Adaptive Pretraining Methods for Dialogue Understanding

no code implementations ACL 2021 Han Wu, Kun Xu, Linfeng Song, Lifeng Jin, Haisong Zhang, Linqi Song

Language models like BERT and SpanBERT pretrained on open-domain data have obtained impressive gains on various NLP tasks.

Dialogue Understanding

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 +1

Conversational Semantic Role Labeling

no code implementations11 Apr 2021 Kun Xu, Han Wu, Linfeng Song, Haisong Zhang, Linqi Song, Dong Yu

Semantic role labeling (SRL) aims to extract the arguments for each predicate in an input sentence.

Coreference Resolution Dialogue Understanding +2

Video-aided Unsupervised Grammar Induction

1 code implementation NAACL 2021 Songyang Zhang, Linfeng Song, Lifeng Jin, Kun Xu, Dong Yu, Jiebo Luo

We investigate video-aided grammar induction, which learns a constituency parser from both unlabeled text and its corresponding video.

Optical Character Recognition

Enhanced Aspect-Based Sentiment Analysis Models with Progressive Self-supervised Attention Learning

1 code implementation5 Mar 2021 Jinsong Su, Jialong Tang, Hui Jiang, Ziyao Lu, Yubin Ge, Linfeng Song, Deyi Xiong, Le Sun, Jiebo Luo

In aspect-based sentiment analysis (ABSA), many neural models are equipped with an attention mechanism to quantify the contribution of each context word to sentiment prediction.

Aspect-Based Sentiment Analysis

TexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis

no code implementations31 Dec 2020 Haisong Zhang, Lemao Liu, Haiyun Jiang, Yangming Li, Enbo Zhao, Kun Xu, Linfeng Song, Suncong Zheng, Botong Zhou, Jianchen Zhu, Xiao Feng, Tao Chen, Tao Yang, Dong Yu, Feng Zhang, Zhanhui Kang, Shuming Shi

This technique report introduces TexSmart, a text understanding system that supports fine-grained named entity recognition (NER) and enhanced semantic analysis functionalities.

Named Entity Recognition NER

Robust Dialogue Utterance Rewriting as Sequence Tagging

1 code implementation29 Dec 2020 Jie Hao, Linfeng Song, LiWei Wang, Kun Xu, Zhaopeng Tu, Dong Yu

The task of dialogue rewriting aims to reconstruct the latest dialogue utterance by copying the missing content from the dialogue context.

Dialogue Rewriting Text Generation

Semantic Role Labeling Guided Multi-turn Dialogue ReWriter

no code implementations EMNLP 2020 Kun Xu, Haochen Tan, Linfeng Song, Han Wu, Haisong Zhang, Linqi Song, Dong Yu

For multi-turn dialogue rewriting, the capacity of effectively modeling the linguistic knowledge in dialog context and getting rid of the noises is essential to improve its performance.

Dialogue Rewriting Semantic Role Labeling

ZPR2: Joint Zero Pronoun Recovery and Resolution using Multi-Task Learning and BERT

no code implementations ACL 2020 Linfeng Song, Kun Xu, Yue Zhang, Jianshu Chen, Dong Yu

Zero pronoun recovery and resolution aim at recovering the dropped pronoun and pointing out its anaphoric mentions, respectively.

Multi-Task Learning

Coordinated Reasoning for Cross-Lingual Knowledge Graph Alignment

no code implementations23 Jan 2020 Kun Xu, Linfeng Song, Yansong Feng, Yan Song, Dong Yu

Existing entity alignment methods mainly vary on the choices of encoding the knowledge graph, but they typically use the same decoding method, which independently chooses the local optimal match for each source entity.

Entity Alignment

Neural Simile Recognition with Cyclic Multitask Learning and Local Attention

1 code implementation19 Dec 2019 Jiali Zeng, Linfeng Song, Jinsong Su, Jun Xie, Wei Song, Jiebo Luo

Simile recognition is to detect simile sentences and to extract simile components, i. e., tenors and vehicles.

Sentence Classification

Graph-based Neural Sentence Ordering

1 code implementation16 Dec 2019 Yongjing Yin, Linfeng Song, Jinsong Su, Jiali Zeng, Chulun Zhou, Jiebo Luo

Sentence ordering is to restore the original paragraph from a set of sentences.

Sentence Ordering

Tackling Graphical NLP problems with Graph Recurrent Networks

1 code implementation13 Jul 2019 Linfeng Song

How to properly model graphs is a long-existing and important problem in NLP area, where several popular types of graphs are knowledge graphs, semantic graphs and dependency graphs.

Knowledge Graphs Machine Reading Comprehension +3

Neural Collective Entity Linking Based on Recurrent Random Walk Network Learning

1 code implementation20 Jun 2019 Mengge Xue, Weiming Cai, Jinsong Su, Linfeng Song, Yubin Ge, Yubao Liu, Bin Wang

However, most neural collective EL methods depend entirely upon neural networks to automatically model the semantic dependencies between different EL decisions, which lack of the guidance from external knowledge.

Entity Disambiguation Entity Linking +1

Progressive Self-Supervised Attention Learning for Aspect-Level Sentiment Analysis

1 code implementation ACL 2019 Jialong Tang, Ziyao Lu, Jinsong Su, Yubin Ge, Linfeng Song, Le Sun, Jiebo Luo

In aspect-level sentiment classification (ASC), it is prevalent to equip dominant neural models with attention mechanisms, for the sake of acquiring the importance of each context word on the given aspect.

Aspect-Based Sentiment Analysis

Semantic Neural Machine Translation using AMR

1 code implementation TACL 2019 Linfeng Song, Daniel Gildea, Yue Zhang, Zhiguo Wang, Jinsong Su

It is intuitive that semantic representations can be useful for machine translation, mainly because they can help in enforcing meaning preservation and handling data sparsity (many sentences correspond to one meaning) of machine translation models.

Machine Translation Translation

N-ary Relation Extraction using Graph-State LSTM

no code implementations EMNLP 2018 Linfeng Song, Yue Zhang, Zhiguo Wang, Daniel Gildea

Cross-sentence $n$-ary relation extraction detects relations among $n$ entities across multiple sentences.

Relation Extraction

Exploring Graph-structured Passage Representation for Multi-hop Reading Comprehension with Graph Neural Networks

no code implementations6 Sep 2018 Linfeng Song, Zhiguo Wang, Mo Yu, Yue Zhang, Radu Florian, Daniel Gildea

Multi-hop reading comprehension focuses on one type of factoid question, where a system needs to properly integrate multiple pieces of evidence to correctly answer a question.

Multi-Hop Reading Comprehension Question Answering

N-ary Relation Extraction using Graph State LSTM

2 code implementations28 Aug 2018 Linfeng Song, Yue Zhang, Zhiguo Wang, Daniel Gildea

Cross-sentence $n$-ary relation extraction detects relations among $n$ entities across multiple sentences.

Relation Extraction

Sequence-to-sequence Models for Cache Transition Systems

1 code implementation ACL 2018 Xiaochang Peng, Linfeng Song, Daniel Gildea, Giorgio Satta

In this paper, we present a sequence-to-sequence based approach for mapping natural language sentences to AMR semantic graphs.

AMR Parsing Hard Attention +1

Leveraging Context Information for Natural Question Generation

1 code implementation NAACL 2018 Linfeng Song, Zhiguo Wang, Wael Hamza, Yue Zhang, Daniel Gildea

The task of natural question generation is to generate a corresponding question given the input passage (fact) and answer.

Question Generation

A Graph-to-Sequence Model for AMR-to-Text Generation

1 code implementation ACL 2018 Linfeng Song, Yue Zhang, Zhiguo Wang, Daniel Gildea

The problem of AMR-to-text generation is to recover a text representing the same meaning as an input AMR graph.

 Ranked #1 on Graph-to-Sequence on LDC2015E86: (using extra training data)

AMR-to-Text Generation Graph-to-Sequence +1

A Unified Query-based Generative Model for Question Generation and Question Answering

no code implementations4 Sep 2017 Linfeng Song, Zhiguo Wang, Wael Hamza

In the QG task, a question is generated from the system given the passage and the target answer, whereas in the QA task, the answer is generated given the question and the passage.

Question Answering Question Generation

$k$-Nearest Neighbor Augmented Neural Networks for Text Classification

no code implementations25 Aug 2017 Zhiguo Wang, Wael Hamza, Linfeng Song

However, it lacks the capacity of utilizing instance-level information from individual instances in the training set.

Classification General Classification +2

Question Generation from a Knowledge Base with Web Exploration

no code implementations12 Oct 2016 Linfeng Song, Lin Zhao

Question generation from a knowledge base (KB) is the task of generating questions related to the domain of the input KB.

Question Generation

AMR-to-text generation as a Traveling Salesman Problem

no code implementations EMNLP 2016 Linfeng Song, Yue Zhang, Xiaochang Peng, Zhiguo Wang, Daniel Gildea

The task of AMR-to-text generation is to generate grammatical text that sustains the semantic meaning for a given AMR graph.

AMR-to-Text Generation Text Generation +2

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