338 citations · 1.2k across the 180 of their papers we have counts for
4 papers · 2 filters
Llama2Vec: Unsupervised Adaptation of Large Language Models for Dense Retrieval
Zheng Liu, Chaofan Li, Shitao Xiao +2
Dense retrieval calls for discriminative embeddings to represent the semantic relationship between query and document. It may benefit from the using of large language models (LLMs)…
Towards Anytime Fine-tuning: Continually Pre-trained Language Models with Hypernetwork Prompt
Gangwei Jiang, Caigao Jiang, Siqiao Xue +4
Continual pre-training has been urgent for adapting a pre-trained model to a multitude of domains and tasks in the fast-evolving world. In practice, a continually pre-trained model…
C-Pack: Packed Resources For General Chinese Embeddings
Shitao Xiao, Zheng Liu, Peitian Zhang +3
We introduce C-Pack, a package of resources that significantly advance the field of general Chinese embeddings. C-Pack includes three critical resources. 1) C-MTEB is a comprehensi…
Learning to Substitute Spans towards Improving Compositional Generalization
Zhaoyi Li, Ying Wei, Defu Lian
Despite the rising prevalence of neural sequence models, recent empirical evidences suggest their deficiency in compositional generalization. One of the current de-facto solutions…