Copertina

AdEval: Alignment-based Dynamic Evaluation to Mitigate Data Contamination in Large Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Fan, Yang
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computation and Language Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

LatestEval: Addressing Data Contamination in Language Model Evaluation through Dynamic and Time-Sensitive Test Construction
di: Li, Yucheng, et al.
Pubblicazione: (2023)

EvalMORAAL: Interpretable Chain-of-Thought and LLM-as-Judge Evaluation for Moral Alignment in Large Language Models
di: Mohammadi, Hadi, et al.
Pubblicazione: (2025)

CriticEval: Evaluating Large Language Model as Critic
di: Lan, Tian, et al.
Pubblicazione: (2024)

TreeEval: Benchmark-Free Evaluation of Large Language Models through Tree Planning
di: Li, Xiang, et al.
Pubblicazione: (2024)

FedEval-LLM: Federated Evaluation of Large Language Models on Downstream Tasks with Collective Wisdom
di: He, Yuanqin, et al.
Pubblicazione: (2024)

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

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

Likelihood-based Mitigation of Evaluation Bias in Large Language Models
di: Oi, Masanari, et al.
Pubblicazione: (2024)

LexInstructEval: Lexical Instruction Following Evaluation for Large Language Models
di: Ren, Huimin, et al.
Pubblicazione: (2025)

WalledEval: A Comprehensive Safety Evaluation Toolkit for Large Language Models
di: Gupta, Prannaya, et al.
Pubblicazione: (2024)

CMoralEval: A Moral Evaluation Benchmark for Chinese Large Language Models
di: Yu, Linhao, et al.
Pubblicazione: (2024)

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

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

FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models
di: Yu, Zhuohao, et al.
Pubblicazione: (2024)

IndicEval: A Bilingual Indian Educational Evaluation Framework for Large Language Models
di: Bharti, Saurabh, et al.
Pubblicazione: (2026)

ViLLM-Eval: A Comprehensive Evaluation Suite for Vietnamese Large Language Models
di: Nguyen, Trong-Hieu, et al.
Pubblicazione: (2024)

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

GenderAlign: An Alignment Dataset for Mitigating Gender Bias in Large Language Models
di: Zhang, Tao, et al.
Pubblicazione: (2024)

EpiK-Eval: Evaluation for Language Models as Epistemic Models
di: Prato, Gabriele, et al.
Pubblicazione: (2023)

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

EduEval: A Hierarchical Cognitive Benchmark for Evaluating Large Language Models in Chinese Education
di: Ma, Guoqing, et al.
Pubblicazione: (2025)

StrucText-Eval: Evaluating Large Language Model's Reasoning Ability in Structure-Rich Text
di: Gu, Zhouhong, et al.
Pubblicazione: (2024)

Unveiling Trust in Multimodal Large Language Models: Evaluation, Analysis, and Mitigation
di: Zhang, Yichi, et al.
Pubblicazione: (2025)

Recent Advances in Large Langauge Model Benchmarks against Data Contamination: From Static to Dynamic Evaluation
di: Chen, Simin, et al.
Pubblicazione: (2025)

NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity Classes
di: Fan, Lizhou, et al.
Pubblicazione: (2023)

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

MTQ-Eval: Multilingual Text Quality Evaluation for Language Models
di: Pokharel, Rhitabrat, et al.
Pubblicazione: (2025)

Alignment Tuning for Large Language Models: A Data-Centric Lens on Alignment Data Pipelines
di: Song, Hwanjun
Pubblicazione: (2026)

CoreEval: Automatically Building Contamination-Resilient Datasets with Real-World Knowledge toward Reliable LLM Evaluation
di: Zhao, Jingqian, et al.
Pubblicazione: (2025)

Data Advisor: Dynamic Data Curation for Safety Alignment of Large Language Models
di: Wang, Fei, et al.
Pubblicazione: (2024)

BenHalluEval: A Multi-Task Hallucination Evaluation Framework for Large Language Models on Bengali
di: Adib, Shefayat E Shams, et al.
Pubblicazione: (2026)

R-Eval: A Unified Toolkit for Evaluating Domain Knowledge of Retrieval Augmented Large Language Models
di: Tu, Shangqing, et al.
Pubblicazione: (2024)

Multi-LogiEval: Towards Evaluating Multi-Step Logical Reasoning Ability of Large Language Models
di: Patel, Nisarg, et al.
Pubblicazione: (2024)

Hal-Eval: A Universal and Fine-grained Hallucination Evaluation Framework for Large Vision Language Models
di: Jiang, Chaoya, et al.
Pubblicazione: (2024)

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

ArxEval: Evaluating Retrieval and Generation in Language Models for Scientific Literature
di: Sinha, Aarush, et al.
Pubblicazione: (2025)

SciSafeEval: A Comprehensive Benchmark for Safety Alignment of Large Language Models in Scientific Tasks
di: Li, Tianhao, et al.
Pubblicazione: (2024)

MHSafeEval: Role-Aware Interaction-Level Evaluation of Mental Health Safety in Large Language Models
di: Lee, Suhyun, et al.
Pubblicazione: (2026)

Moral Persuasion in Large Language Models: Evaluating Susceptibility and Ethical Alignment
di: Huang, Allison, et al.
Pubblicazione: (2024)

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