First unified survey formalizing Pretraining Data Exposure across exposure levels and reviewing attack, defense, and contamination methods for LLMs.
Varbench: Robust language model benchmarking through dynamic variable perturbation.ArXiv, abs/2406.17681, 2024b
3 Pith papers cite this work, alongside 1 external citations. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
Introduces the Oracle benchmark of 96 black-box environments across 6 task types to measure integrated reasoning in LLMs through interactive function discovery, with o3 leading but all models showing planning weaknesses on hard instances.
Interactive evaluation of AI must be reframed as a distinct paradigm that maps interaction trajectories to judgments on process, recoverability, coordination, robustness, and system performance, supported by a two-axis taxonomy and design principles.
citing papers explorer
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Pretraining Data Exposure in Large Language Models: A Survey of Membership Inference, Data Contamination, and Security Implications
First unified survey formalizing Pretraining Data Exposure across exposure levels and reviewing attack, defense, and contamination methods for LLMs.
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Investigating Advanced Reasoning of Large Language Models via Black-Box Environment Interaction
Introduces the Oracle benchmark of 96 black-box environments across 6 task types to measure integrated reasoning in LLMs through interactive function discovery, with o3 leading but all models showing planning weaknesses on hard instances.
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Interactive Evaluation Requires a Design Science
Interactive evaluation of AI must be reframed as a distinct paradigm that maps interaction trajectories to judgments on process, recoverability, coordination, robustness, and system performance, supported by a two-axis taxonomy and design principles.