AI RESEARCH
Navigating the Mirage: A Dual-Path Agentic Framework for Robust Misleading Chart Question Answering
arXiv CS.AI
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ArXi:2603.28583v1 Announce Type: cross Despite the success of Vision-Language Models (VLMs), misleading charts remain a significant challenge due to their deceptive visual structures and distorted data representations. We present ChartCynics, an agentic dual-path framework designed to unmask visual deception via a "skeptical" reasoning paradigm. Unlike holistic models, ChartCynics decouples perception from verification: a Diagnostic Vision Path captures structural anomalies (e.g., inverted axes) through strategic ROI cropping, while an OCR-Driven Data Path ensures numerical grounding.