Certified Interface Aliases: Exact Collisions in Vision-Language Preprocessing, and When They Exist

arXiv:2609.33003 · cs.CV · Submitted 2026-09-26 · Read on arXiv

cs.CV

Submitted: 2026-09-26

Updated: 2026-09-26

Code: https://github.com/KurbanIntelligenceLab/aliasforge

Terminology

• Verifier — 36× in this paper · explained in 2 episodes
• Benchmark — 12× in this paper · explained in 2 episodes
• Accuracy — 11× in this paper · explained in 1 episode
• Regret — 11× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 5× in this paper
• Multimodal Reasoning — 4× in this paper · explained in 5 episodes
• Test-time Scaling — 4× in this paper · explained in 2 episodes
• Calibration — 2× in this paper · explained in 7 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Decode — 2× in this paper · explained in 2 episodes
• Quantization — 2× in this paper · explained in 12 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Self-consistency — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• AUC — 1× in this paper · explained in 2 episodes
• Adaptivity — 1× in this paper · explained in 1 episode
• Adversarial Robustness — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• Qwen Look Again: Guiding Vision-Language Reasoning Models to Re-attention Visual Information
• TikArt: Stabilizing Aperture-Guided Fine-Grained Visual Reasoning with Reinforcement Learning
• AVIS: Adaptive Test-Time Scaling for Vision-Language Models
• Training Vision-Language Process Reward Models for Test-Time Scaling in Multimodal Reasoning: Key Insights and Lessons Learned
• Intriguing Equivalence Structures of the Embedding Space of Vision Transformers
• A Fiber Criterion for Representation Identifiability in Supervised Learning
• Disentangling Perception and Reasoning in Multimodal LLMs via Reward Design
• Improving Visual Reasoning with Iterative Evidence Refinement
• Failing to See or Failing to Know? Attributing Errors in Vision-Language Models
• Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
• When and How Much to Imagine: Adaptive Test-Time Scaling with World Models for Visual Spatial Reasoning
• Chameleon: Adaptive Adversarial Agents for Scaling-Based Visual Prompt Injection in Multimodal AI Systems

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