2 papers
cs.CL2026
Consistent but Miscalibrated: Evaluating LLM Limitations for Risk Communication in Natural Language
Diego Cerda-Mardini, Sarath Chandar, Sreenath Madathil
LLMs are increasingly deployed as post-hoc explainers of AI-generated outputs, yet it remains unclear whether they can reliably communicate probabilistic information in natural lan…
cs.CL2026
Humans and LLMs Diverge on Probabilistic Inferences
Gaurav Kamath, Sreenath Madathil, Sebastian Schuster +2
Human reasoning often involves working over limited information to arrive at probabilistic conclusions. In its simplest form, this involves making an inference that is not strictly…