Mitigating Object Hallucination in Large Vision-Language Models via False Discovery Controlled Visual Data Splitting

arXiv:2609.38979 · cs.CV · Submitted 2026-09-30 · Read on arXiv

cs.CV

Submitted: 2026-09-30

Updated: 2026-10-01

Project page: https://changliu1993-cl.github.io/CORAL

Terminology

• Hallucination — 88× in this paper · explained in 3 episodes
• Accuracy — 33× in this paper · explained in 1 episode
• F1 Score — 26× in this paper · explained in 3 episodes
• Grounding — 23× in this paper · explained in 3 episodes
• False Discovery Rate — 20× in this paper
• Benchmark — 13× in this paper · explained in 2 episodes
• Large Vision-Language Model — 11× in this paper
• Hallucination Mitigation — 9× in this paper · explained in 2 episodes
• Ablation — 7× in this paper · explained in 1 episode
• Ablation study — 6× in this paper · explained in 1 episode
• Alignment — 6× in this paper · explained in 1 episode
• Calibration — 3× in this paper · explained in 7 episodes
• Instruction Tuning — 3× in this paper · explained in 2 episodes
• Training-Free Framework — 3× in this paper · explained in 2 episodes
• Visual Grounding — 3× in this paper · explained in 2 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Assembly of Global and Local Attention — 2× in this paper
• Consistency — 2× in this paper · explained in 3 episodes
• Distribution Shift — 2× in this paper · explained in 5 episodes
• Embeddings — 2× in this paper · explained in 2 episodes
• Feature Selection — 2× in this paper · explained in 4 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• Ablation Studies — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Adaptive Decoding — 1× in this paper · explained in 1 episode
• Alignment Techniques — 1× in this paper · explained in 1 episode
• Computational overhead — 1× in this paper · explained in 2 episodes
• Contrastive Learning — 1× in this paper · explained in 5 episodes
• Core — 1× in this paper · explained in 2 episodes
• Evaluations Caption Hallucination Assessment with Image Relevance — 1× in this paper
• Exchangeability — 1× in this paper · explained in 2 episodes
• Hallucination Detection — 1× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Polling-based Object Probing Evaluation — 1× in this paper
• Vision Transformer (ViT) — 1× in this paper · explained in 2 episodes

Sources

• A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges
• Object Hallucination in Image Captioning
• Shikra: Unleashing Multimodal LLM's Referential Dialogue Magic
• MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
• mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality
• LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
• MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts
• Evaluation and Analysis of Hallucination in Large Vision-Language Models
• Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
• Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning
• V-DPO: Mitigating Hallucination in Large Vision Language Models via Vision-Guided Direct Preference Optimization
• HallE-Control: Controlling Object Hallucination in Large Multimodal Models
• A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models
• Uncertainty-aware Language Modeling for Selective Question Answering
• A Comprehensive Information-Decomposition Analysis of Large Vision-Language Models
• Analyzing the Behavior of Visual Question Answering Models
• A Survey on Hallucination in Large Vision-Language Models
• LLaVA-OneVision: Easy Visual Task Transfer
• InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models
• Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

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