Overview
Who this competition fits
Experienced ML researchers and engineers with strong backgrounds in NLP, information retrieval, and large language models. Best for those wanting to tackle hallucination reduction in RAG systems.
Read the original official blurb
Build retrieval-augmented generation systems that minimize hallucination across diverse question types. Part of the prestigious KDD Cup 2024.
Preparation
From registration to a first submission
- 01
Python
- 02
Large Language Models
- 03
Retrieval-Augmented Generation
- 04
NLP fundamentals
- 05
Information retrieval
- 06
Prompt engineering
Before you commit: Requires building robust retrieval-augmented generation pipelines that handle diverse question types while strictly minimizing hallucination. The evaluation penalizes hallucinated answers heavily, demanding careful calibration and retrieval quality.
Source
How this page was assembled
Competition information is structured from the official page. Scores are platform estimates for decision support; official rules take precedence.
- Official competition page
- AIcrowd
- Last checked
- Not recorded