Papers with Orchestrator

2 papers
DocAgent: A Multi-Agent System for Automated Code Documentation Generation (2025.acl-demo)

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Challenge: Existing methods for generating documentation using Large Language Models (LLMs) produce incomplete, unhelpful, or factually incorrect outputs.
Approach: They propose a novel collaborative system that uses topological code processing for incremental context building to generate documentation by agents.
Outcome: The proposed system outperforms baselines in completeness, helpfulness, and truthfulness evaluations.
OS-Symphony: A Holistic Framework for Robust and Generalist Computer-Using Agents (2026.acl-long)

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Challenge: Vision-Language Models (VLMs) lack visual-aware tutorial retrieval and historical visual context curation and pruning.
Approach: They propose a framework that integrates an orchestrator and a Reflection-Memory Agent for robust automation.
Outcome: Experimental results show that OS-Symphony delivers substantial performance gains across model scales.

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