AI Reasoning Model
(Redirected from CoT-Based Model)
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An AI Reasoning Model is a reasoning model that performs chain-of-thought reasoning to solve complex reasoning tasks (through neural computation).
- AKA: Reasoning AI Model, Chain-of-Thought Model, CoT-Based Model.
- Context:
- It can typically execute AI Reasoning Steps through ai reasoning internal monologue.
- It can typically generate AI Reasoning Chains via ai reasoning intermediate states.
- It can typically solve AI Reasoning Mathematical Problems using ai reasoning symbolic manipulation.
- It can typically perform AI Reasoning Logical Inferences through ai reasoning deductive patterns.
- It can typically demonstrate AI Reasoning Emergent Capability at ai reasoning scale thresholds.
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- It can often surpass AI Reasoning Benchmark Saturation on ai reasoning mathematical competitions.
- It can often exceed AI Reasoning Human Performance in ai reasoning complex benchmarks.
- It can often enable AI Reasoning Multi-Step Solutions through ai reasoning chain generation.
- It can often support AI Reasoning Counterfactual Analysis via ai reasoning scenario exploration.
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- It can range from being a Basic AI Reasoning Model to being an Advanced AI Reasoning Model, depending on its ai reasoning complexity level.
- It can range from being a Narrow-Domain AI Reasoning Model to being a General-Domain AI Reasoning Model, depending on its ai reasoning application scope.
- It can range from being a Small-Scale AI Reasoning Model to being a Large-Scale AI Reasoning Model, depending on its ai reasoning parameter count.
- It can range from being a Zero-Shot AI Reasoning Model to being a Few-Shot AI Reasoning Model, depending on its ai reasoning prompting method.
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- It can integrate with Chain-of-Thought Reasoning Technique for ai reasoning technique implementation.
- It can connect to AI Benchmark Saturation Phenomenon for ai reasoning performance ceilings.
- It can interface with International Math Olympiad Benchmark for ai reasoning capability evaluation.
- It can communicate with Long-Horizon Reasoning System for ai reasoning extended tasks.
- It can synchronize with AI Scaling Paradigm for ai reasoning capability growth.
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- Example(s):
- OpenAI o1 Model (2024) implementing ai reasoning chain generation for ai reasoning mathematical proofs.
- Google PaLM Model demonstrating ai reasoning multi-step capability on ai reasoning BIG-bench tasks.
- Anthropic Claude Model using ai reasoning systematic protocol for ai reasoning problem decomposition.
- DeepMind Gemini Model featuring ai reasoning multimodal understanding with ai reasoning visual reasoning.
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- Counter-Example(s):
- Traditional Language Model, which lacks ai reasoning explicit chains.
- Classification Model, which performs direct prediction without ai reasoning intermediate steps.
- Retrieval Model, which uses external knowledge rather than ai reasoning internal processes.
- See: Reasoning Model, Chain-of-Thought Reasoning Technique, AI Benchmark Saturation Phenomenon, International Math Olympiad Benchmark, Long-Horizon Reasoning System, Complex Reasoning Task, Reasoning LLM-based AI Model.