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

Research paper on how agentic debate pipelines can be constructed to reduce hallucinations in LLMs with open-source and commercial models

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.