Papers with automated multi-agent framework

2 papers
MEDAL: A Framework for Benchmarking LLMs as Multilingual Open-Domain Dialogue Evaluators (2026.findings-eacl)

Copied to clipboard

Challenge: Existing meta-evaluation benchmarks are static, outdated, and lacking in multilingual coverage.
Approach: They propose a framework for curating more representative open-domain dialogue evaluation benchmarks . they leverage several LLMs to generate user-chatbot multilingual dialogues conditioned on varied seed contexts based on a state-of-the-art LLM .
Outcome: The proposed framework exploits state-of-the-art LLMs to perform multilingual evaluations of open-domain chatbots.
Tracing the Roots: A Multi-Agent Framework for Uncovering Data Lineage in Post-Training LLMs (2026.acl-long)

Copied to clipboard

Challenge: High-quality post-training data is the primary engine driving LLM capabilities . datasets are often treated as isolated artifacts, overlooking their true developmental context .
Approach: They propose a framework to reconstruct the evolutionary graph of dataset development using data lineage.
Outcome: The proposed framework characterizes domain-specific structural patterns in Math-oriented datasets and general-domain corpora.

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