66 citations · 74 across the 6 of their papers we have counts for
4 papers · 1 filter
Text Representation Distillation via Information Bottleneck Principle
Yanzhao Zhang, Dingkun Long, Zehan Li +1
Pre-trained language models (PLMs) have recently shown great success in text representation field. However, the high computational cost and high-dimensional representation of PLMs…
Language Models are Universal Embedders
Xin Zhang, Zehan Li, Yanzhao Zhang +4
In the large language model (LLM) revolution, embedding is a key component of various systems, such as retrieving knowledge or memories for LLMs or building content moderation filt…
Towards General Text Embeddings with Multi-stage Contrastive Learning
Zehan Li, Xin Zhang, Yanzhao Zhang +3
We present GTE, a general-purpose text embedding model trained with multi-stage contrastive learning. In line with recent advancements in unifying various NLP tasks into a single f…
Challenging Decoder helps in Masked Auto-Encoder Pre-training for Dense Passage Retrieval
Zehan Li, Yanzhao Zhang, Dingkun Long +1
Recently, various studies have been directed towards exploring dense passage retrieval techniques employing pre-trained language models, among which the masked auto-encoder (MAE) p…