Author

S. Singh

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#artificial intelligence May 2026

Semantic Context-aware mOdality fUsion Transformer (SCOUT): A Context-Aware Multimodal Transformer for Concept-Grounded Pathology Report Generation

The results suggest that progressive contextual conditioning is effective across heterogeneous pathology report generation settings and provides a flexible framework for integrating domain knowledge into vision-language models for computational pathology.

S. Singh, Saarthak Kapse, J. Saltz et al. · arXiv.org · 1 citation

Jul 2026

Pathologist Attention-Aligned Report Generation for Prostate Histopathology

This paper finetune two report generation models with an attention-alignment loss that regularizes the model attention over image patches to match the distribution of pathologist attention, providing stronger visual support for the generated reports by highlighting the regions that most influence the output.

Ruo-Yu Xue, S. Singh, Souradeep Chakraborty et al. · arXiv.org · 0 citations

#artificial intelligence Preprint Sep 2026

Benchmarking Vision-Language Models for Automated Pathology Diagnosis and Report Generation

A clinically curated Pan-Asia WSI--report dataset is introduced and the REG 2025 benchmark is established as a benchmark for evaluating WSI-based structured report generation and vision-language understanding in computational pathology, providing insights for the design of clinically grounded multimodal pathology model...

Yu-Mi Lee, Harim Oh, Hyo-yun Kim et al. · 0 citations