MachinoAI explainer / AI Agents
The Rise and Potential of Large Language Model Based Agents: A Survey
The Rise and Potential of Large Language Model Based Agents: A Survey explores complete agent landscape.
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Abstract
Complete agent landscape
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Introduction
Foundational work on LLM-based agents and Complete agent landscape.
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Problem
Addresses how language models can extend beyond single-turn generation through Complete agent landscape.
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Methodology
The paper operationalizes Complete agent landscape through a structured agent mechanism.
Figure notes
Visual evidence
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Architecture
The system connects an LLM with state, control, tools, memory, environments, interfaces, or other agents.
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Dataset
Uses task-specific datasets, environments, benchmarks, or interaction traces appropriate to the research question.
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Training
Uses the training or inference adaptation documented by the primary source; undisclosed details are not inferred.
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Experiments
Evaluates the proposed mechanism against relevant baselines in the target setting.
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Baselines
Compares against the underlying model, simpler control strategies, or prior agent mechanisms.
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Results
Reports evidence for the proposed contribution within its stated benchmark or environment.
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Conclusion
Contributes a reusable pattern for building or evaluating LLM-based agents.
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References
Primary source: https://arxiv.org/abs/2309.07864
Source trail
Primary papers, implementation pages, and external source records used to ground this explainer.
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