LaViSA - Verb Phrase Attachment: leaderboard

LaViSA (2026) shows a vision-language model a structurally ambiguous sentence and a generated image, and asks which of two or three disambiguated readings the image depicts. This board is per-trial accuracy in percent on the verb phrase attachment category (chance 50); higher is better.

Metric: Per-trial accuracy (%) on the verb phrase attachment category; task: pick which disambiguated reading of a structurally ambiguous sentence a generated image depicts (2 or 3 readings per sentence, 100 sentences per category); chance 50; higher is better. Source: arxiv.org. Saturation forecast: Estimated already saturated. 13 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview)97#94
2GPT-5.295#176
3Gemini 3.1 Flash Lite93.5#364
4Qwen 3 VL 32B (Thinking)92.5#559
5Qwen 3 VL 32B Instruct86#585
6Qwen 3 VL 8B (Thinking)86#887
7Qwen 3 VL 4B Instruct82.5#1279
8Qwen 3 VL 4B (Thinking)79#1296
9Qwen 3 VL 8B Instruct71#981
10Gemma 3 12B (IT)67.5#1837
11Gemma 3 27B (IT)65#1289
12Gemma 3 4B (IT)52.5#3831

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=lavisa-verb-phrase-attachment · How It Works · Data refreshed daily, snapshot 2026-11-13.