Unverified50% confidenceFactExact time
When the context window approaches its limit, the model does not directly throw an error; instead, it shows symptoms of quality degradation such as forgetting earlier instructions, duplicated work, broken logic, and increased hallucination.
1
Sources
50%
Confidence
Long-term
Relevance
10/17/2026
First Seen
Sources
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Related Claims
UnverifiedFine-tuning carries the risk of catastrophic forgetting, where fine-tuning for a specific behavior may degrade the model's performance on other tasks.79% similarUnverifiedWhen the context approaches its limit, the model may forget critical early information or produce lower-quality output.78% similarUnverifiedTypical generation-stage failures include hallucinations caused by ignoring context, middle-content forgetting due to context overflow, insufficient multi-hop reasoning capability, and instruction-following deviation.77% similarUnverifiedOperations such as switching models, switching inference intensity, toggling fast inference mode, compressing conversations, and resuming after cache expiration all cause prompt cache invalidation.76% similarVerifiedOverly verbose, contradictory, or ambiguous system prompts cause the model's attention to become scattered, resulting in over-thinking or instruction-following failures; streamlining agents.md can improve the determinism of instruction following.76% similar
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