activity
20212023
most citedPushing Paraphrase Away from Original Sentence: A Multi-Round Paraphrase Generation Approach

16 citations · 18 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2023

SCoRD: Subject-Conditional Relation Detection with Text-Augmented Data

Ziyan Yang, Kushal Kafle, Zhe Lin +3

We propose Subject-Conditional Relation Detection SCoRD, where conditioned on an input subject, the goal is to predict all its relations to other objects in a scene along with thei…

cs.CL2022★ 1 cited

Visual Information Guided Zero-Shot Paraphrase Generation

Zhe Lin, Xiaojun Wan

Zero-shot paraphrase generation has drawn much attention as the large-scale high-quality paraphrase corpus is limited. Back-translation, also known as the pivot-based method, is ty…

cs.CV2021

Open-Vocabulary Instance Segmentation via Robust Cross-Modal Pseudo-Labeling

Dat Huynh, Jason Kuen, Zhe Lin +2

Open-vocabulary instance segmentation aims at segmenting novel classes without mask annotations. It is an important step toward reducing laborious human supervision. Most existing…

cs.CL2021★ 1 cited

Towards Document-Level Paraphrase Generation with Sentence Rewriting and Reordering

Zhe Lin, Yitao Cai, Xiaojun Wan

Paraphrase generation is an important task in natural language processing. Previous works focus on sentence-level paraphrase generation, while ignoring document-level paraphrase ge…

cs.CL2021★ 16 cited

Pushing Paraphrase Away from Original Sentence: A Multi-Round Paraphrase Generation Approach

Zhe Lin, Xiaojun Wan

In recent years, neural paraphrase generation based on Seq2Seq has achieved superior performance, however, the generated paraphrase still has the problem of lack of diversity. In t…

cs.CL2021

Making Better Use of Bilingual Information for Cross-Lingual AMR Parsing

Yitao Cai, Zhe Lin, Xiaojun Wan

Abstract Meaning Representation (AMR) is a rooted, labeled, acyclic graph representing the semantics of natural language. As previous works show, although AMR is designed for Engli…