Agent Workflow Memory — interactive visual explainer | Rudrite Research

Researchers Wang et al. introduced Agent Workflow Memory, a method enabling AI agents to learn reusable workflows from past trajectories, reducing steps needed for new tasks. The approach works offline from training data or online without labels, feeding workflows back into memory. An interactive visual explainer of the arXiv 2024 paper is available online.

Agent Workflow Memory Agents that learn the recipe, not the run: induce reusable workflows from past trajectories — offline from a training set, or online with no labels at all — feed them back into memory, and solve new tasks in fewer steps. Wang et al. · arXiv 2024 · Reasoning & RL. Read the paper ↗ https://arxiv.org/abs/2409.07429 A free, interactive, animated visual explainer of Agent Workflow Memory — every exhibit computed from the real formulas, with verbatim quotes from the source. Questions - What is Agent Workflow Memory? - Agents that learn the recipe, not the run: induce reusable workflows from past trajectories — offline from a training set, or online with no labels at all — feed them back into memory, and solve new tasks in fewer steps. - Who published Agent Workflow Memory, and where? - Wang et al. — arXiv 2024 arXiv:2409.07429 . - Where can I find a visual explainer of Agent Workflow Memory? - Right here — a free, interactive, animated walkthrough of the whole paper, with exhibits computed from the real formulas and verbatim quotes from the source. Related explainers DeepSeek-R1 /deepseek-r1 ZeRO: Zero Redundancy Optimizer /zero Chain-of-Thought Prompting Elicits Reasoning in Large Language Models /chain-of-thought Training language models to follow instructions with human feedback /instructgpt Direct Preference Optimization: Your Language Model is Secretly a Reward Model /dpo DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models /deepseekmath Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters /test-time-compute Constitutional AI: Harmlessness from AI Feedback /constitutional-ai