Work

Statement-Tuning Enables Efficient Cross-lingual Generalization in Encoder-only Models

Year: 2025

Type: conference-paper

Abstract: Ahmed Elshabrawy, Thanh-Nhi Nguyen, Yeeun Kang, Lihan Feng, Annant Jain, Faadil Abdullah Shaikh, Jonibek Mansurov, Mohamed Fazli Mohamed Imam, Jesus-German Ortiz-Barajas, Rendi Chevi, Alham Fikri Aji. Findings of the Association for Computational Linguistics: ACL 2025. 2025.

DOI: 10.18653/v1/2025.findings-acl.835

Authors: Ahmed Elshabrawy, Thanh-Nhi Nguyen, Yeeun Kang, Lihan Feng, Annant Jain, Faadil Abdullah Shaikh, Jonibek Mansurov, Mohamed Fazli Mohamed Imam, Jesus-German Ortiz-Barajas, Rendi Chevi, Alham Fikri Aji

Institutions: Vietnam National University Ho Chi Minh City, Ho Chi Minh City University of Science, University of Information Technology, Yale University, New York University Shanghai, Indian Institute of Technology Bombay

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

OpenAlex ID: W4412888026

FWCI: 1.059

Cites:

Cited by: 1

Related to: 10