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cs.AI2026
Pitfalls in Evaluating Interpretability Agents
Tal Haklay, Nikhil Prakash, Sana Pandey +5
Automated interpretability systems aim to reduce the need for human labor and scale analysis to increasingly large models and diverse tasks. Recent efforts toward this goal leverag…
cs.AI2023★ 2 cited
Modeling Boundedly Rational Agents with Latent Inference Budgets
Athul Paul Jacob, Abhishek Gupta, Jacob Andreas
We study the problem of modeling a population of agents pursuing unknown goals subject to unknown computational constraints. In standard models of bounded rationality, sub-optimal…