[2603.28583] Navigating the Mirage: A Dual-Path Agentic Framework for Robust Misleading Chart Question Answering

Computer Science > Computer Vision and Pattern Recognition arXiv:2603.28583 (cs) [Submitted on 30 Mar 2026] Title:Navigating the Mirage: A Dual-Path Agentic Framework for Robust Misleading Chart Question Answering Authors:Yanjie Zhang, Yafei Li, Rui Sheng, Zixin Chen, Yanna Lin, Huamin Qu, Lei Chen, Yushi Sun View a PDF of the paper titled Navigating the Mirage: A Dual-Path Agentic Framework for Robust Misleading Chart Question Answering, by Yanjie Zhang and 7 other authors View PDF HTML (experimental) Abstract: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. To resolve cross-modal conflicts, we introduce an Agentic Summarizer optimized via a two-stage protocol: Oracle-Informed SFT for reasoning distillation and Deception-Aware GRPO for adversarial alignment. This pipeline effectively penalizes visual traps and enforces logical consistency. Evaluations on two benchmarks show that ChartCynics achieves 74.43% and 64.55% accuracy, providing an absolute performance boost of ~29% ove...