Unverified50% confidenceFactExact time
Native large models are constrained by context window size and tend to forget early information when handling ultra-long tasks.
1
Sources
50%
Confidence
Long-term
Relevance
9/18/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedEarly large language models were prone to forgetting prior context or hallucinating in long-context scenarios.79% similarUnverifiedContext window limitations cause the model to prefer breaking large tasks into smaller chunks to avoid exceeding its capacity in a single generation.78% similarUnverified早期模型上下文窗口较小（4K–8K Token），长任务中较早的指令和中间状态会被挤出窗口导致遗忘78% similarVerifiedEven models with a million-token context face an attention dilution problem when handling large codebases—when the context is too long, the model's attention to early content drops significantly.76% similar
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