AdaSent: Efficient Domain-Adapted Sentence Embeddings for Few-Shot
Classification

AdaSent: Efficient Domain-Adapted Sentence Embeddings for Few-Shot Classification

1 November 2023

Kexin Wang

Papers citing "AdaSent: Efficient Domain-Adapted Sentence Embeddings for Few-Shot Classification"

7 / 7 papers shown

Title
Domain Adaptation for Japanese Sentence Embeddings with Contrastive Learning based on Synthetic Sentence Generation Zihao Chen H. Handa Miho Ohsaki Kimiaki Shirahama 57 0 0 12 Mar 2025
REFINE on Scarce Data: Retrieval Enhancement through Fine-Tuning via Model Fusion of Embedding Models Ambuje Gupta Mrinal Rawat Andreas Stolcke Roberto Pieraccini RALM 19 1 0 16 Oct 2024
Efficient Few-Shot Learning Without Prompts Lewis Tunstall Nils Reimers Unso Eun Seo Jo Luke Bates Daniel Korat Moshe Wasserblat Oren Pereg VLM 34 181 0 22 Sep 2022
LexGLUE: A Benchmark Dataset for Legal Language Understanding in English Ilias Chalkidis Abhik Jana D. Hartung M. Bommarito Ion Androutsopoulos Daniel Martin Katz Nikolaos Aletras AILaw ELM 125 248 0 03 Oct 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 241 1,918 0 31 Dec 2020
Efficient Intent Detection with Dual Sentence Encoders I. Casanueva Tadas Temvcinas D. Gerz Matthew Henderson Ivan Vulić VLM 178 451 0 10 Mar 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference Timo Schick Hinrich Schütze 258 1,587 0 21 Jan 2020