Abstract: We introduce a visual analysis method for multiple causal graphs with different outcome variables, namely, multi-outcome causal graphs. Multi-outcome causal graphs are important in ...

Large language models excel at function- and file-level code generation, yet generating complete repositories from scratch remains a fundamental challenge. This process demands coherent and reliable ...

An explosion of user-generated data from online social networks motivates analysis to extract deep insights from this data’s graph at scale, even of social, temporal, spatial, and topical connections.

Podcaster Tim Pool's chart significantly overstated the difference in crime rates between Democrat-led and Republican-led cities.

Abstract: Graph representation learning (GRL) has become a new learning paradigm, supporting a wide range of tasks such as node classification, link prediction, and graph classification. However, the ...

We evaluate DeepCode on the PaperBench benchmark (released by OpenAI), a rigorous testbed requiring AI agents to independently reproduce 20 ICML 2024 papers from scratch. The benchmark comprises 8,316 ...