ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2404.12897
  4. Cited By
Enabling Natural Zero-Shot Prompting on Encoder Models via
  Statement-Tuning

Enabling Natural Zero-Shot Prompting on Encoder Models via Statement-Tuning

19 April 2024
A. Elshabrawy
Yongix Huang
Iryna Gurevych
Alham Fikri Aji
ArXivPDFHTML

Papers citing "Enabling Natural Zero-Shot Prompting on Encoder Models via Statement-Tuning"

3 / 3 papers shown
Title
Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End
  Question Answering
Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering
Priyanka Sen
Alham Fikri Aji
Amir Saffari
LRM
97
61
0
04 Oct 2022
Making Pre-trained Language Models Better Few-shot Learners
Making Pre-trained Language Models Better Few-shot Learners
Tianyu Gao
Adam Fisch
Danqi Chen
241
1,913
0
31 Dec 2020
Exploiting Cloze Questions for Few Shot Text Classification and Natural
  Language Inference
Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inference
Timo Schick
Hinrich Schütze
258
1,584
0
21 Jan 2020
1