LaViSA - Conjunction Scope: 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 conjunction scope category (chance 33.3); higher is better.

Metric: Per-trial accuracy (%) on the conjunction scope 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 33.3; higher is better. Source: arxiv.org. Saturation forecast: Around February 2027. 13 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.1 Pro (Preview)85#94
2Qwen 3 VL 32B Instruct78.3#585
3Gemini 3.1 Flash Lite76.3#364
4Qwen 3 VL 4B Instruct73.7#1279
5GPT-5.273#176
6Gemma 3 27B (IT)67.3#1289
7Qwen 3 VL 32B (Thinking)62.3#559
8Gemma 3 12B (IT)59.7#1837
9Qwen 3 VL 8B Instruct51.7#981
10Qwen 3 VL 8B (Thinking)46.3#887
11Qwen 3 VL 4B (Thinking)43.3#1296
12Gemma 3 4B (IT)38#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-conjunction-scope · How It Works · Data refreshed daily, snapshot 2026-11-13.