Generate, Discriminate and Contrast: A Semi-Supervised Sentence
Representation Learning Framework

Generate, Discriminate and Contrast: A Semi-Supervised Sentence Representation Learning Framework

30 October 2022

Yiming Chen

Bin Wang

Zuozhu Liu

Haizhou Li

Papers citing "Generate, Discriminate and Contrast: A Semi-Supervised Sentence Representation Learning Framework"

8 / 8 papers shown

Title
How Well Do Text Embedding Models Understand Syntax? Yan Zhang Zhaopeng Feng Zhiyang Teng Zuozhu Liu Haizhou Li 35 3 0 14 Nov 2023
Statistical Depth for Ranking and Characterizing Transformer-Based Text Embeddings Parker Seegmiller S. Preum 31 3 0 23 Oct 2023
R^3: On-device Real-Time Deep Reinforcement Learning for Autonomous Robotics Zexin Li Aritra Samanta Yufei Li Andrea Soltoggio Hyoseung Kim Cong Liu 22 6 0 29 Aug 2023
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 34 6 0 22 May 2023
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models Nandan Thakur Nils Reimers Andreas Rucklé Abhishek Srivastava Iryna Gurevych VLM 231 966 0 17 Apr 2021
Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts Soravit Changpinyo P. Sharma Nan Ding Radu Soricut VLM 273 1,081 0 17 Feb 2021
The Pile: An 800GB Dataset of Diverse Text for Language Modeling Leo Gao Stella Biderman Sid Black Laurence Golding Travis Hoppe ... Horace He Anish Thite Noa Nabeshima Shawn Presser Connor Leahy AIMat 253 1,986 0 31 Dec 2020
Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks Nandan Thakur Nils Reimers Johannes Daxenberger Iryna Gurevych 205 241 0 16 Oct 2020