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Everything about Reasoning model
Large language model designed for reasoning tasks
Reasoning language models (RLMs) or large reasoning models (LRMs) are large language models that are trained to solve tasks that require several steps of reasoning. They tend to do better on logic, math, and programming tasks than standard LLMs, can revisit and revise earlier steps, make use of extra computations, and enhance performance when increasing the number of parameters, training examples, and training computations. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Reasoning modelA 5-minute orientation
- Skim a recent paper: A Deep Fusion Matching Network Semantic Reasoning ModelInfluential work since 2022
- Pick up a classic book: Mental Models In Cognitive ScienceThe most-reprinted book on the subject
- Read the landmark paper: A Universal Model of Diagnostic ReasoningCited 865 times
- Go sideways: Feedback neural networkA closely related topic
- Go sideways: OpenAI o1A closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
A Universal Model of Diagnostic Reasoning
Large Language Model Influence on Diagnostic Reasoning
Propositional reasoning by model.
A model for analogical reasoning
Key Factors in Bid Reasoning Model
R5 model for case-based reasoning
A probability model of medical reasoning and theMYCIN model
A Model Theory of Modal Reasoning
🆕 Influential since 2022
A Deep Fusion Matching Network Semantic Reasoning Model
Large Language Model Performance and Clinical Reasoning Tasks
LLMRG: Improving Recommendations through Large Language Model Reasoning Graphs
Generative Memory-Guided Semantic Reasoning Model for Image Inpainting
GraphLLM: Boosting Graph Reasoning Ability of Large Language Model
📚 Books worth reading
Mental Models In Cognitive ScienceJane Oakhill · 1996
Mental Models Theory of ReasoningKarl C. Klauer · 2005
Model-based reasoning in science and technologyLorenzo Magnani, Walter A. Carnielli · 2010
Qualitative spatial and temporal reasoningGérard Ligozat · 2011
Creating scientific conceptsNancy J. Nersessian · 2008
Bayesian epistemologyLuc Bovens, Stephan Hartmann · 2003
The Handbook On Reasoningbased Intelligent SystemsKazumi Nakamatsu · 2012- 📕Model-Based Testing Essentials - Guide to the ISTQB Certified Model-Based TesterAnne Kramer, Bruno Legeard · 2016
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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