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stat.ME2024
A general framework for probabilistic model uncertainty
Vik Shirvaikar, Stephen G. Walker, Chris Holmes
Existing approaches to model uncertainty typically either compare models using a quantitative model selection criterion or evaluate posterior model probabilities having set a prior…
cs.LG2024
A Critical Review of Causal Reasoning Benchmarks for Large Language Models
Linying Yang, Vik Shirvaikar, Oscar Clivio +1
Numerous benchmarks aim to evaluate the capabilities of Large Language Models (LLMs) for causal inference and reasoning. However, many of them can likely be solved through the retr…