ZeroR@CHiPSAL 2026：两阶段视觉语言适配用于尼泊尔模因分类
原标题：ZeroR@CHiPSAL 2026: Two-Stage Vision-Language Adaptation with Contrastive Learning for Nepali Meme Classification
AI 摘要
本文介绍了ZeroR团队在CHiPSAL 2026共享任务中针对尼泊尔语模因的多模态仇恨言论和情感检测系统。该系统基于Qwen3-VL-8B-Instruct模型，采用两阶段训练流程，包括LoRA微调和对比学习，最终在仇恨言论检测中排名第二（F1: 0.797），在情感分析中排名第四（F1: 0.518）。
正文节选
Computer Science > Computation and Language Title:ZeroR@CHiPSAL 2026: Two-Stage Vision-Language Adaptation with Contrastive Learning for Nepali Meme Classification View PDF HTML (experimental) Abstract:This paper presents our system for the CHiPSAL 2026 shared task on multimodal hate speech and sentiment detection in Nepali memes. We address both subtasks: binary hate speech classification and three-class sentiment analysis. Our approach adapts the Robust Adaptation of Hateful Meme D