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cs.CL2026
Can LLMs Value the Right Evidence? Evidence-Value Misalignment in Dynamic Medical Diagnosis
Kehua Feng, Yunsheng Lu, Yitong Qiao +5
A correct diagnosis reached from insufficient or misleading evidence can pose a clinical hazard, yet outcome-based accuracy may reward such lucky guesses. We call this mismatch bet…
cs.CL2026
Data Analysis in the Wild: Benchmarking Large Language Models Against Real-World Data Complexities
So Hasegawa, Shailaja Keyur Sampat, Lei Liu +1
Current benchmarks for evaluating Large Language Models (LLMs) in data analysis often fail to reflect real-world settings. They typically focus on fact retrieval from small tables…