Reliability Challenges in Diffusion Vision-Language Models

arXiv:2609.01318 · cs.CV, cs.CL · Submitted 2026-09-01 · Read on arXiv

cs.CV, cs.CL

Submitted: 2026-09-01

Updated: 2026-09-01

Code: https://github.com/Atabuzzaman/Reliability_dLVLM

Terminology

• Hallucination — 64× in this paper · explained in 4 episodes
• Accuracy — 42× in this paper · explained in 1 episode
• Diffusion Model — 14× in this paper · explained in 8 episodes
• Diffusion Models — 11× in this paper · explained in 6 episodes
• Grounding — 9× in this paper · explained in 3 episodes
• Selection Bias — 7× in this paper · explained in 4 episodes
• AUC — 5× in this paper · explained in 2 episodes
• Benchmark — 5× in this paper · explained in 2 episodes
• Benchmarking — 5× in this paper · explained in 4 episodes
• Failure Modes — 5× in this paper · explained in 3 episodes
• Vision-language models — 5× in this paper · explained in 2 episodes
• Instruction Tuning — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Robustness — 3× in this paper · explained in 5 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Hallucination Detection — 2× in this paper · explained in 2 episodes
• Aggregation — 1× in this paper · explained in 1 episode
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Positional Bias — 1× in this paper · explained in 2 episodes
• Sycophancy — 1× in this paper · explained in 4 episodes
• Temporal Reasoning — 1× in this paper · explained in 2 episodes
• Test-time Scaling — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Visual Grounding — 1× in this paper · explained in 2 episodes

Sources

• Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling
• Qwen2.5-VL Technical Report
• Dimple: Discrete Diffusion Multimodal Large Language Model with Parallel Decoding
• GPT-4o System Card
• LLaDA-MoE: A Sparse MoE Diffusion Language Model
• Dream-VL & Dream-VLA: Open Vision-Language and Vision-Language-Action Models with Diffusion Language Model Backbone
• Dream 7B: Diffusion Large Language Models
• mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality

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