Asymmetric Conflict and Synergy in Post-training for LLM-based Multilingual Machine Translation | NSF Public Access Repository

skip to main content

An official website of the United States government Here's how you know

Official websites use .gov

A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS

A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Citation Details

Asymmetric Conflict and Synergy in Post-training for LLM-based Multilingual Machine Translation

Award ID(s):: 2348306

PAR ID:: 10683847

Author(s) / Creator(s):: Zheng, Tong; Wen, Yan; Bao, Huiwen; Guo, Junfeng; Huang, Heng

Publisher / Repository:: The 63rd Annual Meeting of the Association for Computational Linguistics (Findings)

Date Published:: 2025-07-01

Format(s):: Medium: X

Sponsoring Org:: National Science Foundation

Free Publicly Accessible Full Text
This content will become publicly available on July 1, 2026
Conference Proceeding:
The DOI is not currently available.