Unverified50% confidenceFactExact time
纯大模型存在知识截止问题和幻觉问题两大天然缺陷，GPT-4的训练数据存在明确的截止日期
1
Sources
50%
Confidence
Long-term
Relevance
7/6/2026
First Seen
Sources
Building a RAG Q&A Workflow with Dify: A 4-Step Guide to Enterprise Knowledge Base Chatbots
bilibiliAI大模型大课堂6/30/2026
Related Claims
UnverifiedMainstream models such as GPT-4, Claude, and Gemini show significant deviation between confidence and accuracy on questions beyond their knowledge cutoff dates, multi-hop reasoning tasks, and long-tail knowledge domains.82% similarUnverifiedMainstream large language models (including GPT-4, DeepSeek, Claude, etc.) are all trained on static corpora and have a definitive knowledge cutoff date.80% similarUnverifiedGPT-4等大模型在参数规模突破某一阈值后自发涌现出逻辑推理、代码生成等未经专门训练的能力，这一现象称为涌现能力80% similarUnverifiedThe training data of mainstream models such as GPT-4 and Claude has a cutoff at a specific point in time, leaving them with no knowledge of events that occurred after that point.79% similarUnverifiedWhen OpenAI's API endpoint names remain unchanged, the underlying model weights may be silently updated; a 2023 joint study by Stanford and UC Berkeley found significant performance differences in GPT-4's responses to the same prompts across different time periods, with accuracy on certain tasks dropping sharply from 97% to 2%.73% similar
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