123 citations · 335 across the 26 of their papers we have counts for
4 papers · 1 filter
Text Embeddings by Weakly-Supervised Contrastive Pre-training
Liang Wang, Nan Yang, Xiaolong Huang +5
This paper presents E5, a family of state-of-the-art text embeddings that transfer well to a wide range of tasks. The model is trained in a contrastive manner with weak supervision…
Learning Diverse Document Representations with Deep Query Interactions for Dense Retrieval
Zehan Li, Nan Yang, Liang Wang +1
In this paper, we propose a new dense retrieval model which learns diverse document representations with deep query interactions. Our model encodes each document with a set of gene…
SimLM: Pre-training with Representation Bottleneck for Dense Passage Retrieval
Liang Wang, Nan Yang, Xiaolong Huang +5
In this paper, we propose SimLM (Similarity matching with Language Model pre-training), a simple yet effective pre-training method for dense passage retrieval. It employs a simple…
SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Models
Liang Wang, Wei Zhao, Zhuoyu Wei +1
Knowledge graph completion (KGC) aims to reason over known facts and infer the missing links. Text-based methods such as KGBERT (Yao et al., 2019) learn entity representations from…