DocShield: Towards AI Document Safety via Evidence-Grounded Agentic Reasoning
The rapid progress of generative AI has enabled increasingly realistic text-centric image forgeries, posing major challenges to document safety. Existing forensic methods mainly rely on visual cues and lack evidence-based reasoning to reveal subtle text manipulations. Detection, localization, and explanation are often treated as isolated tasks, limiting reliability and interpretability. To tackle these challenges, we propose DocShield, the first unified framework formulating text-centric forgery
Record details
Published: 3 April 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Agents & autonomy
Retrieved: 14 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
Cognitive Comparability and the Limits of Governance: Evaluating Authority Under Radical Capability Asymmetry
arXiv · 3 April 2026
Coupled Control, Structured Memory, and Verifiable Action in Agentic AI (SCRAT -- Stochastic Control with Retrieval and Auditable Trajectories): A Comparative Perspective from Squirrel Locomotion and Scatter-Hoarding
arXiv · 3 April 2026
TraceGuard: Structured Multi-Dimensional Monitoring as a Collusion-Resistant Control Protocol
arXiv · 5 April 2026
The Persistent Vulnerability of Aligned AI Systems
arXiv · 31 March 2026
RAAP: Retrieval-Augmented Affordance Prediction with Cross-Image Action Alignment
arXiv · 31 March 2026
DIRECT: Video Mashup Creation via Hierarchical Multi-Agent Planning and Intent-Guided Editing
arXiv · 6 April 2026
How to cite this record
ethics.ai (3 April 2026), “DocShield: Towards AI Document Safety via Evidence-Grounded Agentic Reasoning,” evidence record 6415, https://ethics.ai/record/6415 (originally published by arXiv).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.