Unverified50% confidenceFactExact time
The core design philosophy of TRACE is to separate expensive offline structure learning from lightweight online inference.
1
Sources
50%
Confidence
Long-term
Relevance
9/30/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedFine-tuning with real trace data more closely reflects the actual usage scenarios of the application compared to manually constructed datasets, and can reduce the performance gap of the fine-tuned model in production.64% similarUnverifiedBecause each step of graph-anchored reasoning is anchored to real nodes and edges, it can reduce the risk of the model fabricating information out of thin air.63% similarUnverified从事件监听打断点并沿调用栈逐层追溯,比盲目全局搜索效率更高且不易遗漏中间数据转换环节62% similarUnverifiedEarly large models in cross-source data research tasks were prone to missing key sources, numerical confusion, or broken inference chains, forcing agents to repeatedly supplement queries.61% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/961217API
curl https://kongchang.com/api/v1/knowledge/claims/961217MCP
get_claim(id=961217)