19 citations · 32 across the 9 of their papers we have counts for
Showing cs.AIShow all
2 papers · 1 filter
cs.AI2025
Learning Reasoning Rewards from Expert Demonstrations with Inverse Reinforcement Learning
Claudio Fanconi, Nicolás Astorga, Mihaela van der Schaar
Teaching large language models (LLMs) to reason during post-training typically relies on reinforcement learning with explicit outcome- or process-based reward functions. However, i…
cs.AI2025
Cascaded Language Models for Cost-effective Human-AI Decision-Making
Claudio Fanconi, Mihaela van der Schaar
A challenge in human-AI decision-making is to balance three factors: the correctness of predictions, the cost of knowledge and reasoning complexity, and the confidence about whethe…