Cover Image

Exploring LLM Agents for Cleaning Tabular Machine Learning Datasets

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bendinelli, Tommaso, Dox, Artur, Holz, Christian
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GECOBench: A Gender-Controlled Text Dataset and Benchmark for Quantifying Biases in Explanations
by: Wilming, Rick, et al.
Published: (2024)

A Comprehensive Benchmark of Machine and Deep Learning Across Diverse Tabular Datasets
by: Shmuel, Assaf, et al.
Published: (2024)

EXACT: Towards a platform for empirically benchmarking Machine Learning model explanation methods
by: Clark, Benedict, et al.
Published: (2024)

A Data-Centric Perspective on Evaluating Machine Learning Models for Tabular Data
by: Tschalzev, Andrej, et al.
Published: (2024)

Learning Without Augmenting: Unsupervised Time Series Representation Learning via Frame Projections
by: Demirel, Berken Utku, et al.
Published: (2025)

LLM Embeddings for Deep Learning on Tabular Data
by: Koloski, Boshko, et al.
Published: (2025)

CleanAgent: Automating Data Standardization with LLM-based Agents
by: Qi, Danrui, et al.
Published: (2024)

FairAgent: Democratizing Fairness-Aware Machine Learning with LLM-Powered Agents
by: Dai, Yucong, et al.
Published: (2025)

TabArena: A Living Benchmark for Machine Learning on Tabular Data
by: Erickson, Nick, et al.
Published: (2025)

Improving LLM Group Fairness on Tabular Data via In-Context Learning
by: Cherepanova, Valeriia, et al.
Published: (2024)

TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents
by: Cai, Yifu, et al.
Published: (2025)

Cleaning Maintenance Logs with LLM Agents for Improved Predictive Maintenance
by: Dimidov, Valeriu, et al.
Published: (2025)

Tabular Data: Is Deep Learning all you need?
by: Zabërgja, Guri, et al.
Published: (2024)

Measuring and Mitigating Bias for Tabular Datasets with Multiple Protected Attributes
by: Duong, Manh Khoi, et al.
Published: (2024)

AutoML-Med: A Framework for Automated Machine Learning in Medical Tabular Data
by: Francia, Riccardo, et al.
Published: (2025)

LATTLE: LLM Attention Transplant for Transfer Learning of Tabular Data Across Disparate Domains
by: Kowsar, Ibna, et al.
Published: (2025)

RAG-Enhanced Collaborative LLM Agents for Drug Discovery
by: Lee, Namkyeong, et al.
Published: (2025)

Exploring Transformer Placement in Variational Autoencoders for Tabular Data Generation
by: Silva, Aníbal, et al.
Published: (2026)

Vision-based Deep Learning Analysis of Unordered Biomedical Tabular Datasets via Optimal Spatial Cartography
by: Mostafa, Sakib, et al.
Published: (2026)

Kernel-Level Energy-Efficient Neural Architecture Search for Tabular Dataset
by: La, Hoang-Loc, et al.
Published: (2025)

WISCA: A Consensus-Based Approach to Harmonizing Interpretability in Tabular Datasets
by: Banegas-Luna, Antonio Jesús, et al.
Published: (2025)

ML-Agent: Reinforcing LLM Agents for Autonomous Machine Learning Engineering
by: Liu, Zexi, et al.
Published: (2025)

Tabular Data Augmentation for Machine Learning: Progress and Prospects of Embracing Generative AI
by: Cui, Lingxi, et al.
Published: (2024)

XAI4LLM. Let Machine Learning Models and LLMs Collaborate for Enhanced In-Context Learning in Healthcare
by: Nazary, Fatemeh, et al.
Published: (2024)

Measuring LLM Sensitivity in Transformer-based Tabular Data Synthesis
by: R, Maria F. Davila, et al.
Published: (2025)

TAGAL: Tabular Data Generation using Agentic LLM Methods
by: Ronval, Benoît, et al.
Published: (2025)

Automatic Demonstration Selection for LLM-based Tabular Data Classification
by: Han, Shuchu, et al.
Published: (2025)

Learning to Clean: Reinforcement Learning for Noisy Label Correction
by: Heidari, Marzi, et al.
Published: (2025)

TabularMath: Evaluating Computational Extrapolation in Tabular Learning via Program-Verified Synthesis
by: Cheng, Zerui, et al.
Published: (2026)

Helix 1.0: An Open-Source Framework for Reproducible and Interpretable Machine Learning on Tabular Scientific Data
by: Aguilar-Bejarano, Eduardo, et al.
Published: (2025)

A Survey on Deep Tabular Learning
by: Somvanshi, Shriyank, et al.
Published: (2024)

Tabular and Deep Learning for the Whittle Index
by: Relaño, Francisco Robledo, et al.
Published: (2024)

Agentic Unlearning: When LLM Agent Meets Machine Unlearning
by: Wang, Bin, et al.
Published: (2026)

Reinforcement Learning for Machine Learning Engineering Agents
by: Yang, Sherry, et al.
Published: (2025)

Embodiment-Induced Coordination Regimes in Tabular Multi-Agent Q-Learning
by: Atif, Muhammad Ahmed, et al.
Published: (2026)

Imitation Learning Datasets: A Toolkit For Creating Datasets, Training Agents and Benchmarking
by: Gavenski, Nathan, et al.
Published: (2024)

Multi-Agent Debate: A Unified Agentic Framework for Tabular Anomaly Detection
by: Wang, Pinqiao, et al.
Published: (2026)

CLIMB: Class-imbalanced Learning Benchmark on Tabular Data
by: Liu, Zhining, et al.
Published: (2025)

Learning Relational Tabular Data without Shared Features
by: Wu, Zhaomin, et al.
Published: (2025)

Few-shot Cross-country Generalization of Tabular Machine Learning and Foundation Models for Childhood Anemia Prediction under Distribution Shift
by: Brima, Yusuf, et al.
Published: (2026)