1 citations · 1 across the 5 of their papers we have counts for
Showing 2026 · cs.LGShow all
2 papers · 2 filters
cs.LG2026
Benchmarking and Enhancing Agentic Causal Discovery
Pingchuan Ma, Rui Ding, Shuai Wang
LLM agents can now run causal discovery algorithms on a dataset and report what comes out. Whether they do more than that, such as noticing where an algorithm went wrong and fixing…
cs.LG2026
Test Time Training for Supervised Causal Learning
Zizhen Deng, Jiaru Zhang, Rui Ding +5
Supervised Causal Learning (SCL) has shown promise in causal discovery by framing it as a supervised learning problem. However, it suffers from significant out-of-distribution gene…