Editing Visual Grounding (section)

== <span style="color: #FFFFFF;">Analyzing</span> ==
{| class="wikitable"
|+ Visual Grounding Benchmarks (RefCOCO val)
! Model !! val Accuracy !! testA (people) !! testB (objects) !! Speed
|-
| TransVG || 81.0% || 82.7% || 78.4% || Fast
|-
| MDETR || 86.8% || 89.6% || 81.4% || Moderate
|-
| Grounding DINO || 90.6% || 92.5% || 86.7% || Moderate
|-
| Qwen2-VL (7B) || 91.4% || 93.2% || 87.8% || Moderate
|-
| GPT-4o (with tools) || ~89% || ~91% || ~85% || Slow (API)
|}

'''Failure modes''': Attribute confusion — "the large red ball" may ground to a small red ball or a large blue ball. Relational grounding failures — "the ball to the left of the box" requires spatial reasoning that models handle inconsistently. Overcrowded scenes — models struggle when many similar objects are present. Out-of-vocabulary objects — even open-vocabulary models fail on rare, unusual objects.
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