Author

Alessandro Abate

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Preprint Aug 2026

Q-based Variational Inverse Reinforcement Learning

Q-based Variational IRL (QVIRL), a novel Bayesian IRL method that recovers a posterior distribution over rewards from expert demonstrations via primarily learning a variational distribution over optimal Q-values, is introduced.

Ondrej Bajgar, Peter Tisnikar, Alessandro Abate et al. · 0 citations

Preprint Jul 2026

Amortising Bayesian Experimental Design for Sequential Information Gathering in LLMs

Amortised Sequential Information Gathering (ASIG), a fine-tuning approach that amortises Bayesian Experimental Design into LLM policies via a multi-turn extension of Group Relative Policy Optimisation with an Expected Information Gain reward, is introduced.

Jakob Hartmann, James Harvey, Jhonathan Navott et al. · 0 citations