Unverified50% confidenceSolutionExact time
Post-processing and language model error correction are often the key to pushing from 90% to 99%, with methods including dictionary validation, regular expression rules, and language model error correction.
1
Sources
50%
Confidence
Long-term
Relevance
8/29/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedLarge language models have a miscalibration problem, often answering in a confident tone regardless of whether the answer is correct or incorrect.72% similarUnverifiedLinguists are able to identify systematic errors made by models in pragmatic reasoning, coreference resolution, register switching, and culturally context-dependent metaphor comprehension—areas where current LLMs are most prone to mistakes.70% similarUnverified纠正性反馈对语言习得至关重要，学习者只有在尝试表达、犯错并获得及时校正的循环中才能内化语言规则69% similarVerifiedThe false-positive rates of mainstream AI detection tools (such as GPTZero, Originality.ai, and Turnitin) can reach 5%–15%, and the false-positive rate is even higher for academic writing by non-native English speakers.67% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/818957API
curl https://kongchang.com/api/v1/knowledge/claims/818957MCP
get_claim(id=818957)