Papers with DocAgent

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

Copied to clipboard

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.
DocAgent: An Agentic Framework for Multi-Modal Long-Context Document Understanding (2025.emnlp-main)

Copied to clipboard

Challenge: Existing approaches to document understanding are limited due to limited context length or fail to fully leverage multi-modal information.
Approach: They propose a multi-agent framework for long-context document understanding that imitates human reading practice.
Outcome: The proposed framework surpasses human-level benchmarks on long-context document understanding while maintaining a short context length.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations