A Sentence is Worth 128 Pseudo Tokens: A Semantic-Aware Contrastive
Learning Framework for Sentence Embeddings

A Sentence is Worth 128 Pseudo Tokens: A Semantic-Aware Contrastive Learning Framework for Sentence Embeddings

11 March 2022

Linqi Song

Papers citing "A Sentence is Worth 128 Pseudo Tokens: A Semantic-Aware Contrastive Learning Framework for Sentence Embeddings"

6 / 6 papers shown

Title
A Comprehensive Survey of Sentence Representations: From the BERT Epoch to the ChatGPT Era and Beyond Abhinav Ramesh Kashyap Thang-Tung Nguyen Viktor Schlegel Stefan Winkler See-Kiong Ng Soujanya Poria AI4TS 3DV SSL 37 6 0 22 May 2023
Unsupervised Sentence Representation Learning with Frequency-induced Adversarial Tuning and Incomplete Sentence Filtering Bing Wang Ximing Li Zhiyao Yang Yuanyuan Guan Jiayin Li Sheng-sheng Wang 35 6 0 15 May 2023
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,858 0 18 Apr 2021
COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining Yu Meng Chenyan Xiong Payal Bajaj Saurabh Tiwary Paul N. Bennett Jiawei Han Xia Song 125 203 0 16 Feb 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 243 1,924 0 31 Dec 2020
Language Models as Knowledge Bases? Fabio Petroni Tim Rocktaschel Patrick Lewis A. Bakhtin Yuxiang Wu Alexander H. Miller Sebastian Riedel KELM AI4MH 428 2,588 0 03 Sep 2019