Unverified50% confidenceFactExact time
The context windows of large models are limited, ultra-long texts need to be processed in segments, and implicit contradictions across segments may still be missed.
1
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50%
Confidence
Long-term
Relevance
10/25/2026
First Seen
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Related Claims
UnverifiedIn large-context-window scenarios, the risk of prompt injection is amplified, because the model must read a large amount of external material at once, and malicious instructions may be scattered in different positions within the long text and be harder to find via keyword filtering.76% similarUnverifiedA model's context window has a physical upper limit and cannot ingest all information from an entire large codebase at once, which may result in code changes that are locally optimal but globally incorrect.75% similarUnverifiedThe process by which a model compresses high-dimensional semantic representations into a discrete token sequence is lossy—fine-grained semantic information, uncertainty distributions, and contextual associations are flattened when converted to text.75% similarUnverified本地模型的上下文窗口往往比旗舰API模型更有限，臃肿的指令会浪费算力并稀释关键信息73% similar
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