Unverified50% confidenceFactExact time
SSR (Selection-based Structured Reasoning) proposes a paradigm shift: instead of letting the model freely generate the reasoning process, it lets the model choose from preset reasoning candidates.
1
Sources
50%
Confidence
Long-term
Relevance
10/15/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedSSR abstracts recurring high-level reasoning patterns into a predefined, reusable set of natural language candidates, and the model selects the most suitable reasoning path from the candidate list in each round of interaction.75% similarUnverifiedReasoning models are more likely to augment than replace traditional programming—the model handles architectural logic while humans focus on high-level design.72% similarUnverifiedSSR's candidate set design philosophy is close to the retrieval idea in retrieval-augmented generation (RAG), namely pre-building a reasoning candidate library so the model retrieves and selects the best-matching candidate based on the current situation rather than generating from scratch.70% similarUnverifiedThe same reasoning effort parameter means reducing thinking on a model that reasons by default, but means starting to think on a model that does not reason by default, the semantics being opposite.69% similarUnverifiedReasoning models with the thinking function enabled perform significantly better than base models when handling counterintuitive questions.69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1040061API
curl https://kongchang.com/api/v1/knowledge/claims/1040061MCP
get_claim(id=1040061)