activity
20192022
most citedTexSmart: A Text Understanding System for Fine-Grained NER and Enhanced Semantic Analysis

20 citations · 43 across the 12 of their papers we have counts for

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Showing cs.CLShow all

14 papers · 1 filter

cs.CL2022

Learning a Grammar Inducer from Massive Uncurated Instructional Videos

Songyang Zhang, Linfeng Song, Lifeng Jin +4

Video-aided grammar induction aims to leverage video information for finding more accurate syntactic grammars for accompanying text. While previous work focuses on building systems…

cs.CL2022

Distant finetuning with discourse relations for stance classification

Lifeng Jin, Kun Xu, Linfeng Song +1

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 ind…

cs.CL2021

Connect-the-Dots: Bridging Semantics between Words and Definitions via Aligning Word Sense Inventories

Wenlin Yao, Xiaoman Pan, Lifeng Jin +3

Word Sense Disambiguation (WSD) aims to automatically identify the exact meaning of one word according to its context. Existing supervised models struggle to make correct predictio…

cs.CL2021

Exophoric Pronoun Resolution in Dialogues with Topic Regularization

Xintong Yu, Hongming Zhang, Yangqiu Song +3

Resolving pronouns to their referents has long been studied as a fundamental natural language understanding problem. Previous works on pronoun coreference resolution (PCR) mostly f…

cs.CL2021

Conversational Semantic Role Labeling

Kun Xu, Han Wu, Linfeng Song +3

Semantic role labeling (SRL) aims to extract the arguments for each predicate in an input sentence. Traditional SRL can fail to analyze dialogues because it only works on every sin…

cs.CL2021

Structural Information Preserving for Graph-to-Text Generation

Linfeng Song, Ante Wang, Jinsong Su +4

The task of graph-to-text generation aims at producing sentences that preserve the meaning of input graphs. As a crucial defect, the current state-of-the-art models may mess up or…