# JarviX: A LLM No code Platform for Tabular Data Analysis and Optimization

arXiv: https://arxiv.org/abs/2312.02213 · HTML: https://mlsanity.com/paper/2312.02213/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 18 references that are in the map.
- First posted on arXiv 3 Dec 2023.

## Builds on (most cited first, 6 of 6)

- [Scaling Instruction-Finetuned Language Models](https://mlsanity.com/paper/2210.11416/) (2022)
- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures](https://mlsanity.com/paper/1601.00770/) (2016)
- [ChatDB: Augmenting LLMs with Databases as Their Symbolic Memory](https://mlsanity.com/paper/2306.03901/) (2023)
- [Generate & Rank: A Multi-task Framework for Math Word Problems](https://mlsanity.com/paper/2109.03034/) (2021)
- [XNLI: Explaining and Diagnosing NLI-based Visual Data Analysis](https://mlsanity.com/paper/2301.10385/) (2023)

## Built on by (most cited first, 10 of 10)

- [Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Survey](https://mlsanity.com/paper/2402.17944/) (2024)
- [AutoReproduce: Automatic AI Experiment Reproduction with Paper Lineage](https://mlsanity.com/paper/2505.20662/) (2025)
- [LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs](https://mlsanity.com/paper/2408.08656/) (2024)
- [A Survey on Large Language Model-based Agents for Statistics and Data Science](https://mlsanity.com/paper/2412.14222/) (2024)
- [LightVA: Lightweight Visual Analytics with LLM Agent-Based Task Planning and Execution](https://mlsanity.com/paper/2411.05651/) (2024)
- [Large Language Models for Constructing and Optimizing Machine Learning Workflows: A Survey](https://mlsanity.com/paper/2411.10478/) (2024)
- [Tab-MIA: A Benchmark Dataset for Membership Inference Attacks on Tabular Data in LLMs](https://mlsanity.com/paper/2507.17259/) (2025)
- [Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation](https://mlsanity.com/paper/2501.16692/) (2025)
- [SLEGO: A Collaborative Data Analytics System with LLM Recommender for Diverse Users](https://mlsanity.com/paper/2406.11232/) (2024)
- [Linking Heterogeneous Data with Coordinated Agent Flows for Social Media Analysis](https://mlsanity.com/paper/2510.26172/) (2025)

## Abstract (arXiv)

In this study, we introduce JarviX, a sophisticated data analytics framework. JarviX is designed to employ Large Language Models (LLMs) to facilitate an automated guide and execute high-precision data analyzes on tabular datasets. This framework emphasizes the significance of varying column types, capitalizing on state-of-the-art LLMs to generate concise data insight summaries, propose relevant analysis inquiries, visualize data effectively, and provide comprehensive explanations for results drawn from an extensive data analysis pipeline. Moreover, JarviX incorporates an automated machine learning (AutoML) pipeline for predictive modeling. This integration forms a comprehensive and automated optimization cycle, which proves particularly advantageous for optimizing machine configuration. The efficacy and adaptability of JarviX are substantiated through a series of practical use case studies.