Unverified50% confidenceFactExact time
Masked language modeling (MLM) is the de facto standard pretraining objective for Transformer encoders processing longitudinal electronic medical records.
1
Sources
50%
Confidence
Long-term
Relevance
10/22/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedMultimodal large language models (MLLMs) are large-scale neural network models capable of simultaneously processing and understanding multiple modalities such as text, images, audio, and video, typically based on the Transformer architecture, and acquiring cross-modal alignment capabilities through pretraining on large-scale multimodal data.73% similarUnverifiedMainstream LLMs are based on the Transformer architecture and acquire capabilities through self-supervised learning of next-token prediction on massive text data.72% similarUnverifiedThe architecture of current MLLMs typically trains language encoders and visual encoders separately before fusing them, causing models to struggle with deep cross-modal reasoning.71% similarUnverifiedLLMs are essentially pattern-matching systems based on statistical regularities, learning through pre-training on massive code corpora what code typically follows a given context.70% similarUnverifiedLLM的预训练本质是在海量文本上进行下一词预测（Next Token Prediction），通过Transformer架构的注意力机制建立词语间语义关联70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1084397API
curl https://kongchang.com/api/v1/knowledge/claims/1084397MCP
get_claim(id=1084397)