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Buffer of Thoughts(BoT)
Maintains a dynamic buffer of reusable thought patterns for analogical reasoning
๐ฏ 30-Second Overview
Pattern: Thought-augmented reasoning that collects diverse approaches in a buffer, distills patterns, and creates reusable templates
Why: Builds reasoning expertise over time by learning from diverse thought processes and creating reusable knowledge structures
Key Insight: Generate diverse thoughts โ Buffer storage โ Distill patterns โ Create templates โ Apply to new problems
โก Quick Implementation
๐ Do's & Don'ts
๐ฆ When to Use
Use When
- โข Problems requiring creative reasoning approaches
- โข Domains where experience accumulation helps
- โข Multi-step reasoning with reusable patterns
- โข When building reasoning expertise over time
- โข Complex problem-solving requiring diverse perspectives
Avoid When
- โข Simple, one-off reasoning tasks
- โข Domains with well-established procedures
- โข Memory-constrained environments
- โข Real-time applications requiring immediate response
- โข Problems with no reusable reasoning patterns
๐ Key Metrics
๐ก Top Use Cases
References & Further Reading
Deepen your understanding with these curated resources
Academic Papers
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models (Yang et al., 2024)
Skeleton-of-Thought: Large Language Models Can Do Parallel Decoding (Ning et al., 2023)
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models (Wei et al., 2022)
Tree of Thoughts: Deliberate Problem Solving with Large Language Models (Yao et al., 2023)
Contribute to this collection
Know a great resource? Submit a pull request to add it.
Buffer of Thoughts(BoT)
Maintains a dynamic buffer of reusable thought patterns for analogical reasoning
๐ฏ 30-Second Overview
Pattern: Thought-augmented reasoning that collects diverse approaches in a buffer, distills patterns, and creates reusable templates
Why: Builds reasoning expertise over time by learning from diverse thought processes and creating reusable knowledge structures
Key Insight: Generate diverse thoughts โ Buffer storage โ Distill patterns โ Create templates โ Apply to new problems
โก Quick Implementation
๐ Do's & Don'ts
๐ฆ When to Use
Use When
- โข Problems requiring creative reasoning approaches
- โข Domains where experience accumulation helps
- โข Multi-step reasoning with reusable patterns
- โข When building reasoning expertise over time
- โข Complex problem-solving requiring diverse perspectives
Avoid When
- โข Simple, one-off reasoning tasks
- โข Domains with well-established procedures
- โข Memory-constrained environments
- โข Real-time applications requiring immediate response
- โข Problems with no reusable reasoning patterns
๐ Key Metrics
๐ก Top Use Cases
References & Further Reading
Deepen your understanding with these curated resources
Academic Papers
Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models (Yang et al., 2024)
Skeleton-of-Thought: Large Language Models Can Do Parallel Decoding (Ning et al., 2023)
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models (Wei et al., 2022)
Tree of Thoughts: Deliberate Problem Solving with Large Language Models (Yao et al., 2023)
Contribute to this collection
Know a great resource? Submit a pull request to add it.