Prof. Wray Buntine retweetledi
Google research shows developers can teach an LLM to update its beliefs by mimicking probability models.
The big point is that current AI systems are actually quite bad at picking up on subtle clues. If you ask a standard AI for flight tickets, it might guess your preference once, but it will not update its guess if you pick a different option than it expected.
They struggle to learn user preferences gradually during a conversation, usually failing to adjust their recommendations when new information comes in.
Instead of just feeding the model the final correct answer to train it, the researchers decided to train the model to copy the exact step-by-step guesses of a perfect mathematical system.
The authors tested this method using a flight booking simulation where the system had to figure out what a user secretly wanted just by watching which flights they picked over several rounds.
The study showed that models trained this way actually learned how to reason about uncertainty, performing much better at predicting what human users wanted as the conversation went on.
This proves that scientists can teach language models complex logical skills that transfer easily to entirely new situations like online shopping or booking hotels.
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Paper Link – arxiv. org/abs/2503.17523
Paper Title: "Bayesian Teaching Enables Probabilistic Reasoning in LLMs"
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