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VL-Compositionality

Benchmarks This repository contains a collection of evaluation benchmarks used to assess the compositional understanding of Vision-Language Models (VLMs), as presented in the paper Cross-Modal Masked Compositional Concept Modeling for Enhancing Visio-Linguistic Compositionality.

PaperDataset

How to run

ltb · vl-compositionality
$ npm i -g lettokenburn-cli
$ ltb bench info vl-compositionality

External harness. No Harbor adapter has been generated for this benchmark yet. `ltb bench info` prints the known links.

Runs happen on your machine with your own subscription; only the score summary is pushed. CLI docs

Scores

0 sourced entries

No sourced scores recorded yet.

Every number links to where it was published. Low-confidence rows are muted and need per-cell verification.

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About

VL-Compositionality-Benchmarks

This repository contains a collection of evaluation benchmarks used to assess the compositional understanding of Vision-Language Models (VLMs), as presented in the paper Cross-Modal Masked Compositional Concept Modeling for Enhancing Visio-Linguistic Compositionality. Official GitHub Repository: hiker-lw/MACCO

Dataset Summary

These benchmarks are designed to evaluate how well models like CLIP capture object relations…