DocShield 4B

--- library_name: transformers license: apache-2.0 language: - zh - en pipeline_tag: image-text-to-text tags: - forgery-detection - document-forensics - image-tampering - vision-language-model - vlm - qwen3.5-vl --- <p align="center"> <img src="docshield_showcase.png" alt="DocShield-4B showcase" width="70%"> </p> # DocShield-4B **DocShield-4B** is a forensic-grade vision-language model for **document / image forgery analysis**. It inspects an input document image, reasons over visual tampering traces and logical consistency, and produces a structured forgery-analysis report with localized tampered regions (grounding coordinates), per-region reasoning, an overall conclusion, and a fraud-risk score. It is fine-tuned from **Qwen3.5-VL-4B** with supervised training on forensic document-forgery data, and supports Qwen3.5 thinking mode. 📄 **Paper:** [arxiv.org/abs/2604.02694](https://arxiv.org/abs/2604.02694) ## Training data DocShield-4B was developed using the **RealText** forensic document datasets: - [vankey/RealText-V1](https://huggingface.co/datasets/vankey/RealText-V1) - [vankey/RealText-V2](https://huggingface.co/datasets/vankey/RealText-V2) ## Capabilities - **Visual forgery trace analysis** — crude redaction / mosaic, font & anti-aliasing inconsistency, edge halos, copy-paste artifacts, compression mismatches. - **Logical & fact-checking** — price/quantity contradictions, date conflicts, bulk-discount logic violations. - **Semantic alteration detection** — subtle spec substitutions (e.g. color, material) that bypass crude visual checks. - **Localization** — bounding-box coordinates for each tampered region with per-anomaly reasoning. - **Structured report** — conclusion (`FORGED` / authentic) + fraud-risk score. ## Model details | | | |---|---| | Base model | Qwen3.5-VL-4B | | Architecture | Qwen3_5ForConditionalGeneration (hybrid linear / full attention) | | Precision (weights) | bfloat16 | | Max new tokens | 1024 (default) | | Thinking mode | supported (`--thinking` / `--no-thinking`) | > The base model is **not** bundled here. This repository only releases the > fine-tuned DocShield-4B weights. ## Quick start Install dependencies: ```bash pip install -U transformers torch torchvision pillow qwen-vl-utils ``` > Requires a `transformers` version with native **Qwen3.5-VL (`qwen3_5`)** support. > The released weights were sav...