Refinement Symmetry in Multimodal Transformers

arXiv:2609.32669 · cs.AI, cs.CV · Submitted 2026-09-26 · Read on arXiv

cs.AI, cs.CV

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• Accuracy — 77× in this paper · explained in 1 episode
• Benchmark — 21× in this paper · explained in 2 episodes
• Calibration — 17× in this paper · explained in 7 episodes
• Consistency — 13× in this paper · explained in 3 episodes
• Aggregation — 10× in this paper · explained in 1 episode
• Tokenization — 9× in this paper · explained in 2 episodes
• Transformer — 8× in this paper · explained in 2 episodes
• Alignment — 6× in this paper · explained in 1 episode
• Additivity — 5× in this paper · explained in 1 episode
• Embeddings — 5× in this paper · explained in 2 episodes
• Robustness — 5× in this paper · explained in 5 episodes
• Quantization — 3× in this paper · explained in 12 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 2× in this paper
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Homogeneity — 2× in this paper · explained in 2 episodes
• CVF International Conference on Computer Vision — 1× in this paper
• Clustering — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Exchangeability — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• In International Conference on Learning Representations — 1× in this paper
• Jensen–Shannon Divergence (JSD) — 1× in this paper · explained in 2 episodes
• LoRA Fine-Tuning — 1× in this paper · explained in 3 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Score Function — 1× in this paper · explained in 4 episodes
• Sparse Attention — 1× in this paper · explained in 5 episodes
• Verification — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• Hyperbolic contractivity and the Hilbert metric on probability measures
• Gemma 2: Improving Open Language Models at a Practical Size
• Audio Flamingo 3: Advancing Audio Intelligence with Fully Open Large Audio Language Models
• nD-RoPE: A Generalized RoPE for n-Dimensional Position Embedding
• VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling
• RoFormer: Enhanced Transformer with Rotary Position Embedding
• On the Regularity of Attention
• Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
• Qwen2.5-Omni Technical Report

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