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20202025
most citedUnsupervised Sentence Textual Similarity with Compositional Phrase Semantics

4 citations · 13 across the 7 of their papers we have counts for

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7 papers · 1 filter

cs.CL20222 cited

MICO: A Multi-alternative Contrastive Learning Framework for Commonsense Knowledge Representation

Ying Su, Zihao Wang, Tianqing Fang +3

Commonsense reasoning tasks such as commonsense knowledge graph completion and commonsense question answering require powerful representation learning. In this paper, we propose to…

cs.CL20224 cited

Unsupervised Sentence Textual Similarity with Compositional Phrase Semantics

Zihao Wang, Jiaheng Dou, Yong Zhang

Measuring Sentence Textual Similarity (STS) is a classic task that can be applied to many downstream NLP applications such as text generation and retrieval. In this paper, we focus…

cs.CL2022

Query2Particles: Knowledge Graph Reasoning with Particle Embeddings

Jiaxin Bai, Zihao Wang, Hongming Zhang +1

Answering complex logical queries on incomplete knowledge graphs (KGs) with missing edges is a fundamental and important task for knowledge graph reasoning. The query embedding met…

cs.CL20214 cited

Benchmarking the Combinatorial Generalizability of Complex Query Answering on Knowledge Graphs

Zihao Wang, Hang Yin, Yangqiu Song

Complex Query Answering (CQA) is an important reasoning task on knowledge graphs. Current CQA learning models have been shown to be able to generalize from atomic operators to more…

cs.CL2020

Semi-Supervised Bilingual Lexicon Induction with Two-way Interaction

Xu Zhao, Zihao Wang, Hao Wu +1

Semi-supervision is a promising paradigm for Bilingual Lexicon Induction (BLI) with limited annotations. However, previous semisupervised methods do not fully utilize the knowledge…

cs.CL2020

A Relaxed Matching Procedure for Unsupervised BLI

Xu Zhao, Zihao Wang, Hao Wu +1

Recently unsupervised Bilingual Lexicon Induction (BLI) without any parallel corpus has attracted much research interest. One of the crucial parts in methods for the BLI task is th…