Research
Papers
A curated digest of recent prompt-engineering, agentic, and AI-security research. Each paper: a 3-sentence TL;DR, why it matters for practitioners, and how to put it to work.
3 papers in Techniques
- Techniques May 2023 arXiv: 2305.10601
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Generalizes chain-of-thought by having the model explore multiple reasoning branches, score each, and prune. Dramatically better on puzzle-like problems (24, crosswords, creative writing with constraints) at the cost of 5-10x the tokens.
- Techniques Mar 2022 arXiv: 2307.11760
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Sample the model N times at nonzero temperature, take the mode of the final answers. Cheapest known reliability upgrade for discrete-answer tasks -- easily doubles accuracy on math reasoning at the cost of N-x compute.
- Techniques Jan 2022 arXiv: 2201.11903
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Appending "let's think step by step" or showing worked-example reasoning in the prompt dramatically improves LLM accuracy on math and multi-step problems. The paper that named and formalized chain-of-thought. Still the cited reference for CoT despite being from 2022.