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Language models learn from web documents, some of them false, and false content can reach a model's answer to a factual question and the summaries and decisions that use it. Most data-poisoning studies add a trigger to the training data and activate it in the prompt. False documents can also change factual responses wi...
What enters an LLM's context can influence its decision even when it should not determine it, and exposure systematically shifts decisions, with effects reaching nearly 50 percentage points in closed-weight models.
The results show that grievance is measured more faithfully by reading the surrounding context, and more honestly when tested on text the lexicon did not select, as evaluated on a non-circular benchmark.
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