8 citations · 11 across the 5 of their papers we have counts for
6 papers
Knowledge Base Completion for Long-Tail Entities
Lihu Chen, Simon Razniewski, Gerhard Weikum
Despite their impressive scale, knowledge bases (KBs), such as Wikidata, still contain significant gaps. Language models (LMs) have been proposed as a source for filling these gaps…
SimCSE++: Improving Contrastive Learning for Sentence Embeddings from Two Perspectives
Jiahao Xu, Wei Shao, Lihui Chen +1
This paper improves contrastive learning for sentence embeddings from two perspectives: handling dropout noise and addressing feature corruption. Specifically, for the first perspe…
GLADIS: A General and Large Acronym Disambiguation Benchmark
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
Acronym Disambiguation (AD) is crucial for natural language understanding on various sources, including biomedical reports, scientific papers, and search engine queries. However, e…
Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
State-of-the-art NLP systems represent inputs with word embeddings, but these are brittle when faced with Out-of-Vocabulary (OOV) words. To address this issue, we follow the princi…
mSHINE: A Multiple-meta-paths Simultaneous Learning Framework for Heterogeneous Information Network Embedding
Xinyi Zhang, Lihui Chen
Heterogeneous information networks(HINs) become popular in recent years for its strong capability of modelling objects with abundant information using explicit network structure. N…
A Lightweight Neural Model for Biomedical Entity Linking
Lihu Chen, Gaël Varoquaux, Fabian M. Suchanek
Biomedical entity linking aims to map biomedical mentions, such as diseases and drugs, to standard entities in a given knowledge base. The specific challenge in this context is tha…