5 items tagged with "Evaluation"
MICCAI 2026 presentation on MIS-Ground, a factorial benchmark that isolates the language-side brittleness behind 3D medical spatial grounding, and MIS-SemSam, a training-free semantic-sampling decode rule that lifts Qwen3-VL-32B by 13.06% to 66.5% overall, the best open-weights result and above Gemini 3 Flash.
MICCAI 2026 poster: MIS-Ground tests 3D anatomical spatial grounding across CT, MRI, views, coordinates, prompts, and terminology. MIS-SemSam changes the token-selection rule and raises Qwen3-VL-32B accuracy from 53.4% to 66.5%.
Scorio Trace, Lite, Math, and GPQA contain 1.4 million repeated reasoning attempts for evaluation, ranking, answer selection, and token-level confidence analysis.
MIS-Ground is a controlled factorial benchmark that isolates the language-side brittleness behind 3D medical spatial grounding in vision-language models. MIS-SemSam, a training-free semantic-sampling decode rule, lifts Qwen3-VL-32B by 13.06% to 66.5% overall, the best open-weights result and above Gemini 3 Flash.
A principled Bayesian framework that replaces Pass@k with posterior estimates, credible intervals, and stable rankings for LLM evaluation