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ClinEnv reveals that LLMs struggle significantly with management decisions in clinical scenarios, achieving only 0.17 F1 for these critical actions despite better performance in diagnosis.
Fusing image features with semantic segmentation and geographic clustering unlocks substantial gains in worldwide image geo-localization, surpassing prior methods by up to 16.58% at the street level.
LLMs in medical diagnosis are alarmingly prone to jumping to conclusions, often answering before seeing all the evidence, but strategically delaying the question and evidence presentation can boost accuracy by up to 62.6%.
