Unverified95% confidenceFactTime unknown
大语言模型的原生能力边界由训练数据的模态和格式决定,标准LLM的输入输出均为纯文本Token序列,天然无法处理PDF、DOCX、XLSX等二进制文件格式
1
Sources
95%
Confidence
Long-term
Relevance
5/31/2026
First Seen
Sources
Related Entities
Related Claims
Unverified模型的格式方言源于指令微调阶段训练数据的格式差异,被模型深度内化形成强烈格式偏好,难以通过运行时提示词完全覆盖78% similarUnverified经过指令微调和RLHF训练的模型在遵循格式规范方面表现更好,有时反而会生成格式更完美的虚假引用70% similarUnverifiedLayoutLM在FUNSD表单理解、RVL-CDIP文档分类等基准测试上大幅超越纯文本模型70% similarUnverifiedThe capability boundaries of intent recognition systems are determined by manually written rules and have limited scalability, whereas large language models, through pretraining on massive text, can handle new tasks that were not explicitly programmed, achieving a paradigm shift from rule-driven to data-driven approaches.70% similarUnverified标准Llama模型本质上是纯文本模型,无法直接处理发票扫描件或PDF截图68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/12904API
curl https://kongchang.com/api/v1/knowledge/claims/12904MCP
get_claim(id=12904)