3 accepted papers
Reliable causal inference is essential for making decisions in high-stakes areas like medicine, economics, and public policy. However, it remains unclear whether large language models (LLMs) can handle rigorous and trustworthy \textit{statistical causal inference}. Current benchmarks usually involve…
Large language models (LLMs) have advanced the automation of data science workflows. Yet it remains unclear whether they can critically leverage external domain knowledge as human data scientists do in practice. To answer this question, we introduce AssistedDS (Assisted Data Science), a benchmark de
Detecting small instances within complex backgrounds presents significant challenges for Remote Sensing Object Detection (RSOD). While complex deep networks can enhance feature representation, they often lead to considerable computational burdens. Previous research has proposed dual-stream learning…