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'Context Poisoning' Enters r/artificial's Working Vocabulary — a 51-Comment Thread on Why Correcting a Model Mid-Conversation Doesn't Actually Fix It
A r/artificial thread (97 upvotes / 51 comments) popularized 'context poisoning': in a long conversation, when a model states something wrong and the user corrects it, both the error and the correction remain in context, and the original wrong claim keeps influencing downstream generations. The thread's value is not novelty — it's that a failure mode practitioners work around instinctively now has a name non-specialists are using, which changes how users describe degraded long-session behavior. For builders, it's an argument for context pruning and fresh-session restarts over in-place correction.
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