Cover Image

Detecting Data Contamination in Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Janicki, Juliusz, Chamezopoulos, Savvas, Kanoulas, Evangelos, Tsatsaronis, Georgios
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Optimizing Numerical Estimation and Operational Efficiency in the Legal Domain through Large Language Models
by: Huang, Jia-Hong, et al.
Published: (2024)

Data Contamination Quiz: A Tool to Detect and Estimate Contamination in Large Language Models
by: Golchin, Shahriar, et al.
Published: (2023)

A Survey on Recent Advances in Conversational Data Generation
by: Soudani, Heydar, et al.
Published: (2024)

Knowledge-Enhanced Conversational Recommendation via Transformer-based Sequential Modelling
by: Zou, Jie, et al.
Published: (2024)

Spectral Tempering for Embedding Compression in Dense Passage Retrieval
by: Li, Yongkang, et al.
Published: (2026)

Reasoning Multimodal Large Language Model: Data Contamination and Dynamic Evaluation
by: Liu, Ming, et al.
Published: (2025)

Trustworthy AI: Securing Sensitive Data in Large Language Models
by: Feretzakis, Georgios, et al.
Published: (2024)

Towards Data Contamination Detection for Modern Large Language Models: Limitations, Inconsistencies, and Oracle Challenges
by: Samuel, Vinay, et al.
Published: (2024)

An Open Source Data Contamination Report for Large Language Models
by: Li, Yucheng, et al.
Published: (2023)

Investigating Data Contamination in Modern Benchmarks for Large Language Models
by: Deng, Chunyuan, et al.
Published: (2023)

SubSearch: Intermediate Rewards for Unsupervised Guided Reasoning in Complex Retrieval
by: Petcu, Roxana, et al.
Published: (2026)

Evaluation of Large Language Models for Anomaly Detection in Autonomous Vehicles
by: Loukas, Petros, et al.
Published: (2025)

Detecting Data Contamination from Reinforcement Learning Post-training for Large Language Models
by: Tao, Yongding, et al.
Published: (2025)

DVD: A Robust Method for Detecting Variant Contamination in Large Language Model Evaluation
by: Liang, Renzhao, et al.
Published: (2026)

A Proof-of-Concept for Explainable Disease Diagnosis Using Large Language Models and Answer Set Programming
by: Gemou, Ioanna, et al.
Published: (2025)

Evading Data Contamination Detection for Language Models is (too) Easy
by: Dekoninck, Jasper, et al.
Published: (2024)

Learning to Ask: Conversational Product Search via Representation Learning
by: Zou, Jie, et al.
Published: (2024)

AdEval: Alignment-based Dynamic Evaluation to Mitigate Data Contamination in Large Language Models
by: Fan, Yang
Published: (2025)

Gradient Weight-normalized Low-rank Projection for Efficient LLM Training
by: Huang, Jia-Hong, et al.
Published: (2024)

Time Travel in LLMs: Tracing Data Contamination in Large Language Models
by: Golchin, Shahriar, et al.
Published: (2023)

PaCoST: Paired Confidence Significance Testing for Benchmark Contamination Detection in Large Language Models
by: Zhang, Huixuan, et al.
Published: (2024)

Sensitivity of Small Language Models to Fine-tuning Data Contamination
by: Scaria, Nicy, et al.
Published: (2025)

A Novel Automatic Framework for Speaker Drift Detection in Synthesized Speech
by: Huang, Jia-Hong, et al.
Published: (2026)

Dynamic Benchmarking of Reasoning Capabilities in Code Large Language Models Under Data Contamination
by: Chen, Simin, et al.
Published: (2025)

On the Complexity of Winner Determination and Strategic Control in Conditional Approval Voting
by: Markakis, Evangelos, et al.
Published: (2022)

QFMTS: Generating Query-Focused Summaries over Multi-Table Inputs
by: Zhang, Weijia, et al.
Published: (2024)

Investigating Data Contamination for Pre-training Language Models
by: Jiang, Minhao, et al.
Published: (2024)

VLM-RRT: Vision Language Model Guided RRT Search for Autonomous UAV Navigation
by: Ye, Jianlin, et al.
Published: (2025)

Data Contamination Can Cross Language Barriers
by: Yao, Feng, et al.
Published: (2024)

Generalization or Memorization: Data Contamination and Trustworthy Evaluation for Large Language Models
by: Dong, Yihong, et al.
Published: (2024)

Pretraining Data Exposure in Large Language Models: A Survey of Membership Inference, Data Contamination, and Security Implications
by: Tong, Ziyi, et al.
Published: (2026)

Query Decomposition for RAG: Balancing Exploration-Exploitation
by: Petcu, Roxana, et al.
Published: (2025)

Improving the Robustness of Dense Retrievers Against Typos via Multi-Positive Contrastive Learning
by: Sidiropoulos, Georgios, et al.
Published: (2024)

A Multimodal Dense Retrieval Approach for Speech-Based Open-Domain Question Answering
by: Sidiropoulos, Georgios, et al.
Published: (2024)

Categorical semantics of compositional reinforcement learning
by: Bakirtzis, Georgios, et al.
Published: (2022)

Deep Positive-Unlabeled Anomaly Detection for Contaminated Unlabeled Data
by: Takahashi, Hiroshi, et al.
Published: (2024)

RADAR: Mechanistic Pathways for Detecting Data Contamination in LLM Evaluation
by: Kattamuri, Ashish, et al.
Published: (2025)

Anomaly Detection with Adaptive and Aggressive Rejection for Contaminated Training Data
by: Lee, Jungi, et al.
Published: (2025)

The Heap: A Contamination-Free Multilingual Code Dataset for Evaluating Large Language Models
by: Katzy, Jonathan, et al.
Published: (2025)

Beyond Surface-Level Similarity: Hierarchical Contamination Detection for Synthetic Training Data in Foundation Models
by: Mehta, Sushant
Published: (2025)