Framework: Multi-Agent LLMs For Conversational Task-Solving (MALLM)
-
Updated
Jan 22, 2026 - Python
Framework: Multi-Agent LLMs For Conversational Task-Solving (MALLM)
Research-backed methodology for multi-AI collaborative decision-making with structured debate, consensus synthesis, and bias reduction
Neurips paper code - Evaluating and enhancing Large Language Models (LLMs) using mathematical datasets through innovative Multi-Agent Debate Architecture, without traditional fine-tuning or Retrieval-Augmented Generation techniques. This project explores advanced strategies to boost LLM capabilities in mathematical reasoning.
Research paper on how agentic debate pipelines can be constructed to reduce hallucinations in LLMs with open-source and commercial models
Add a description, image, and links to the multi-agent-debate topic page so that developers can more easily learn about it.
To associate your repository with the multi-agent-debate topic, visit your repo's landing page and select "manage topics."