SEA is introduced, a reference-free metric that measures how economically a sketch preserves class-defining visual elements while maintaining semantic recognizability and enables fine-grained evaluation of sketch understanding in vision-language models (VLMs).
In this paper, our goal is to represent text embeddings as sketches for three main reasons. First, to visualize text representation and to explore their potential their potential for AI explainability. Second, to investigate the potential benefits of the sketch-based representation for information retrieval. Third, to...
This study examines when sketch input is useful for MLLM-generated chart annotations across variation in chart type and caption type, and presents AnnoSketch, a database of annotation sketches collected across 160 chart-caption pairs from the conditions in which sketch guidance proved most beneficial.
Yoon-Gu Oh, Seon Gyeom Kim, J. Choi et al.· 0 citations
SIG is introduced, a structured grid-based schema that explicitly represents object layouts, inter-object relations, and physically grounded priors that demonstrates the generalizability of SIG across diverse scenarios and multiple MLLMs, and systematically examines how data sample selection influences SIG-based ICL.
Guan-Lin Wu, Bo-Yan Su, Yang Zhao et al.· IEEE Transactions on Pattern...· 0 citations
This work introduces VisualWorldBench, a taxonomy-grounded multi-task benchmark built on a hierarchical taxonomy of 21,291 leaf-node classes across 8 visual domains, with 32,541 evaluation instances whose ground-truth labels cover 15,479 categories across four complementary tasks.
ReVA is proposed, a region-aware VQA model that employs a frozen CLIP ViT-L/14 Vision Transformer (ViT) and a Qwen2.5-7B-Instruct large language model (LLM) connected through a dual bridge that aligns both whole-image and region-level representations with the LLM's embedding space.
A novel self-supervised framework that enables granular control over image generation through a visual abstraction set that provides a richer, more flexible paradigm for creative design compared to state-of-the-art baselines across diverse styles and compositions is introduced.
Amir Hertz, Noah Snavely, Google DeepMind· 0 citations
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