Unverified50% confidenceFactExact time
SSR 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.
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50%
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Long-term
Relevance
10/15/2026
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UnverifiedSSR (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.75% similarUnverifiedStreaming inference involves inference optimization techniques such as speculative decoding and continuous batching.70% similarUnverifiedTraditional base large language models adopt a transductive paradigm, directly giving answers to queries by intuition, in a process akin to highly complex pattern matching.70% similarUnverifiedWhen a large language model calls tools, it needs to place the names, descriptions, and parameter schemas of all available tools into the context, from which the model selects the most appropriate one during inference.70% similarUnverifiedDecision-type tasks in NLP are classified as text classification or natural language inference, which are suited for BERT-series Encoder-only models, where inference computation scales linearly with sequence length69% similar
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