Unverified50% confidenceFactExact time
Jev 1.14 introduces the Box bounding box type, allowing the model to directly output structured coordinate data rather than natural language descriptions.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/15/2026
First Seen
Valid until: 1/13/2027
Sources
Related Entities
Related Claims
UnverifiedAbstract concepts encoded inside the model can bridge distributional gaps better than surface features.64% similarUnverifiedThe hallucination-free output of promptable classifiers like Jev benefits from the closed nature of the classification task — the output space is restricted to preset categories, and the model cannot generate free text.63% similarUnverifiedA classifier maps input to one of a finite set of predefined categories with a fixed, closed candidate space; a generative language model predicts the next token from the entire vocabulary at each step, with an open candidate space, building output autoregressively.62% similarUnverifiedFor scenarios that are just routine text generation, the benefits brought by the 262k context and the Box type are limited; while needs such as layout parsing, receipt recognition, and interface automation are worth evaluating Jev 1.14.62% similarUnverified大语言模型能基于统计模式识别协议结构特征（如帧头、长度字段、命令码、校验和），本质是对已知协议模式的泛化而非真正理解61% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1034534API
curl https://kongchang.com/api/v1/knowledge/claims/1034534MCP
get_claim(id=1034534)