3 papers
cs.CL2026
ChartFI: Benchmarking Faithfulness and Insightfulness of Chart Descriptions from Multimodal Large Language Models
Fen Wang, Zekai Shao, Qiman Kang +5
Chart descriptions are essential for accessibility, cross-modal retrieval, and assisting readers in extracting insights from complex visualizations. As multimodal large language mo…
cs.IR2026
UniScale: Synergistic Entire Space Data and Model Scaling for Search Ranking
Liren Yu, Caiyuan Li, Feiyi Dong +5
Recent advances in Large Language Models (LLMs) have inspired a surge of scaling research in industrial search, advertising, and recommendation systems. However, existing approache…
cs.CV2026
Towards Clinically Interpretable Ophthalmic VQA via Spatially-Grounded Lesion Evidence
Xingyue Wang, Bo Liu, Meng Wang +4
Visual Question Answering (VQA) holds great promise for clinical support, particularly in ophthalmology, where retinal fundus photography is essential for diagnosis. However, ophth…