3 papers
cs.LG2026
Causal Process Models: Reframing Dynamic Causal Graph Discovery as a Reinforcement Learning Problem
Turan Orujlu, Christian Gumbsch, Martin V. Butz +1
Most neural models of causality assume static causal graphs, failing to capture the dynamic and sparse nature of physical interactions where causal relationships emerge and dissolv…
cs.AI2026
Do LLMs Share Human-Like Biases? Causal Reasoning Under Prior Knowledge, Irrelevant Context, and Varying Compute Budgets
Hanna M. Dettki, Charley M. Wu, Bob Rehder
Large language models (LLMs) are increasingly used in domains where causal reasoning matters, yet it remains unclear whether their judgments reflect normative causal computation, h…
cs.AI2025
Do Large Language Models Reason Causally Like Us? Even Better?
Hanna M. Dettki, Brenden M. Lake, Charley M. Wu +1
Causal reasoning is a core component of intelligence. Large language models (LLMs) have shown impressive capabilities in generating human-like text, raising questions about whether…