Categories: AI/ML News

Researchers teach an AI to write better chart captions

Chart captions that explain complex trends and patterns are important for improving a reader’s ability to comprehend and retain the data being presented. For people with visual disabilities, the information in a caption often provides their only means of understanding the chart.

RecA: A new finetuning method that doesn’t use image captions.

https://arxiv.org/abs/2509.07295 "We introduce Reconstruction Alignment (RecA), a resource-efficient post-training method that leverages visual understanding encoder embeddings as dense "text prompts," providing rich supervision without captions. Concretely, RecA conditions a UMM on its own visual understanding embeddings and optimizes it to reconstruct the input image with a self-supervised reconstruction loss, thereby…

September 14, 2025

In "Image"

VeCLIP: Improving CLIP Training via Visual-enriched Captions

Paper abstract: Large-scale web-crawled datasets are fundamental for the success of pre-training vision-language models, such as CLIP. However, the inherent noise and potential irrelevance of web-crawled AltTexts pose challenges in achieving precise image-text alignment. Existing methods utilizing large language models (LLMs) for caption rewriting have shown promise on small, curated…

March 6, 2024

In "FAANG"