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cs.AI2026
Representation-guided in-context learning for medical image interpretation with multimodal large language models
Minda Zhao, Fangyu Hu, Yan Luo +8
Medical image interpretation is central to diagnosis and care, yet adapting general-purpose multimodal large language models (MLLMs) often requires resource-intensive domain-specif…
cs.CL2026
MedConclusion: A Benchmark for Biomedical Conclusion Generation from Structured Abstracts
Weiyue Li, Ruizhi Qian, Yi Li +5
Large language models (LLMs) are widely explored for reasoning-intensive research tasks, yet resources for testing whether they can infer scientific conclusions from structured bio…
cs.CV2026
Setting-Matched and Semantics-Scaled Benchmarking of One-Step Generative Models Against Multistep Diffusion and Flow Models
Advaith Ravishankar, Serena Liu, Mingyang Wang +11
State-of-the-art text-to-image models produce high-quality images, but inference remains expensive as generation requires several sequential ODE or denoising steps. Native one-step…