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cs.LG2023★ 1 cited
How Well Does GPT-4V(ision) Adapt to Distribution Shifts? A Preliminary Investigation
Zhongyi Han, Guanglin Zhou, Rundong He +7
In machine learning, generalization against distribution shifts -- where deployment conditions diverge from the training scenarios -- is crucial, particularly in fields like climat…
cs.LG2023
Advancing Counterfactual Inference through Nonlinear Quantile Regression
Shaoan Xie, Biwei Huang, Bin Gu +2
The capacity to address counterfactual "what if" inquiries is crucial for understanding and making use of causal influences. Traditional counterfactual inference, under Pearls' cou…